c4bd11c5c880d8c72af33c01ac1b4b5fe0fae33b 2020-09-23T13:24:28 Percent Occurrence Tidal Currant Exceeds 1.0 m/s spexp-ti0 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Tidal Currant Exceeds | National Percentage of time (over the whole 59days) that speed exceeds threshold Percentage of time (over the whole 59days) that speed exceeds threshold 155.0 -45.0 110.0 -6.0 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Aspexp-ti0 7fc63414a544958ac05badcd80f7e3d20dc101a8 2020-09-23T13:24:28 Percent Occurrence Tidal Currant Exceeds 1.5 m/s spexp-ti1 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Tidal Currant Exceeds | National Percentage of time (over the whole 59days) that speed exceeds threshold Percentage of time (over the whole 59days) that speed exceeds threshold 155.0 -45.0 110.0 -6.0 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Aspexp-ti1 fce9b4a54bff25e9f6ae37e6b9ba32946ab8d0e9 2020-09-23T13:24:28 Percent Occurrence Tidal Currant Exceeds 2.0 m/s spexp-ti2 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Tidal Currant Exceeds | National Percentage of time (over the whole 59days) that speed exceeds threshold Percentage of time (over the whole 59days) that speed exceeds threshold 155.0 -45.0 110.0 -6.0 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Aspexp-ti2 6460fa70d63722049b97a00cc58b797a878157f8 2020-09-23T13:24:28 National Tidal Model Outline features tidalModelOutline Tidal Energy | Context Layers "Outline of the National Tidal Model grid " "Outline of the National Tidal Model grid " 154.977544 -44.602387 110.465775 -6.848585 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3AtidalModelOutline http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3AtidalModelOutline&style=velocityElevPolygons d1aa4cff566bbe4bc773ea2ee29d097a2ffca3f1 2020-09-23T13:24:28 Sea Surface Temperature Trend RMSE - 1993-2013 Oceans | Ocean Temperature | Sea Surface Temperature WCS GeoTIFF trendRMSE_31July2014 Multiple Use | Sea Surface Temperature The physical climate defines a significant portion of the habitats in which biological communities and species reside. It is important to quantify these environmental conditions, and how they have changed, as this will inform future efforts to study many natural systems. We present the results of a statistical summary of the variability in sea surface temperature (SST) time-series data for the waters surrounding Australia, from 1993 to 2013. We partition variation in the SST series into annual trends, inter-annual trends, and a number of components of random variation. We utilise satellite data and validate the statistical summary from these data to summaries of data from long-term monitoringstations and from the global drifter program. The spatially dense results show clear trends that associate with oceanographic features. Noteworthy oceanographic features include: average warming was greatest off southern West Australia and off eastern Tasmania where the warming was around 0.6 C per decade for a twenty year study period, and; insubstantial warming in areas dominated by the East Australian Current but this area did exhibit high levels of inter-annual variability (long-term trend increases and decreases but does not increase on average). The results of the analyses can be directly incorporated into (biogeographic) models that explain variation in biological data where both biological and environmental data are on a fine scale. The physical climate defines a significant portion of the habitats in which biological communities and species reside. It is important to quantify these environmental conditions, and how they have changed, as this will inform future efforts to study many natural systems. We present the results of a statistical summary of the variability in sea surface temperature (SST) time-series data for the waters surrounding Australia, from 1993 to 2013. We partition variation in the SST series into annual trends, inter-annual trends, and a number of components of random variation. We utilise satellite data and validate the statistical summary from these data to summaries of data from long-term monitoringstations and from the global drifter program. The spatially dense results show clear trends that associate with oceanographic features. Noteworthy oceanographic features include: average warming was greatest off southern West Australia and off eastern Tasmania where the warming was around 0.6 C per decade for a twenty year study period, and; insubstantial warming in areas dominated by the East Australian Current but this area did exhibit high levels of inter-annual variability (long-term trend increases and decreases but does not increase on average). The results of the analyses can be directly incorporated into (biogeographic) models that explain variation in biological data where both biological and environmental data are on a fine scale. 160.9839974357248 -46.9798988032319 107.97999945148223 -7.955899841787632 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://www.marlin.csiro.au/geonetwork/srv/eng/search#!b8f48127-495e-42e6-8d53-db3c56ee3a7f 367166575dfa1bc51883259e03cf0249ca25eac5 2020-09-23T13:24:28 Annual Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The annual mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The annual mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg.nc a9a6c45b3c03d89ecf12fc73ad0004832fee391e 2020-09-23T13:24:28 (Month 01) January Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg01 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The January mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The January mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg01 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg01.nc 1e71c496d3b441beee9c72c46de11adc4b96d0e5 2020-09-23T13:24:28 (Month 02) February Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg02 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The February mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The February mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg02 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg02.nc 0d78c45d5a88f6e4020f285e7c31b6d4bce7456f 2020-09-23T13:24:28 (Month 03) March Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg03 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The March mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The March mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg03 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg03.nc b8b1d15b4e9cffaef26af05721c699a12f88f403 2020-09-23T13:24:29 (Month 04) April Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg04 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The April mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The April mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg04 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg04.nc 2bebb513194a94f238944b12e3983a9950b47379 2020-09-23T13:24:29 (Month 05) May Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg05 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The May mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The May mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg05 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg05.nc cc288e886da719dedb8a4b00168928d30146339a 2020-09-23T13:24:29 (Month 06) June Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg06 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The June mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The June mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg06 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg06.nc f0b1c457837d5adf590b304f052722944fa2fc07 2020-09-23T13:24:29 (Month 07) July Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg07 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The July mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The July mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg07 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg07.nc bd6bee70371d8925fe7e3361894cc35ff4bdd085 2020-09-23T13:24:29 (Month 08) August Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg08 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The August mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The August mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg08 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg08.nc 2b2fe04598ac113d5b17bfbe7cc34c045dbd1b9b 2020-09-23T13:24:29 (Month 09) September Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg09 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The September mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The September mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg09 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg09.nc c1950bb87e8c551b9aedb918a34aa89ba0163cc6 2020-09-23T13:24:29 (Month 10) October Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg10 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The October mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The October mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg10 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg10.nc 9eaecdffde3b2c849014106bf7473bb6187afed8 2020-09-23T13:24:29 (Month 11) November Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg11 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The November mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The November mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg11 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg11.nc cb877f9878328d1fb39863ad0b1306a6ba563222 2020-09-23T13:24:29 (Month 12) December Mean Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg12 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Monthly Means The December mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The December mean wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg12 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg12.nc 8dd57062c64985fd5e8fb7f73cc16d193e1c7eaa 2020-09-23T13:24:29 Monthly Variability of Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_avg_mv WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The monthly variability of wave energy flux provides a convenient measure of the variability of the mean monthly wave energy flux over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The monthly variability of wave energy flux provides a convenient measure of the variability of the mean monthly wave energy flux over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_avg_mv http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_avg_mv.nc beddcab2c3e7376e04bbcff0a2a21dfde839dac7 2020-09-23T13:24:30 Maximum Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_max WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The maximum wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The maximum wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_max http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_max.nc cc9ecc9e7473eaab85fa7d3ad9aed053a8cf4a3a 2020-09-23T13:24:30 Minimum Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_min WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The minimum wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The minimum wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_min http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_min.nc 218182636ee181f2179718a9aaf116dc9e87fb0b 2020-09-23T13:24:30 10th Percentile of Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_p10 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The 10th percentile of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 10th percentile of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_p10 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_p10.nc 87a210b51e6b33108705e735e770ef5a435f3f1b 2020-09-23T13:24:30 50th Percentile of Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_p50 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The 50th percentile of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 50th percentile of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_p50 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_p50.nc e2dc32a79a6159a63c82c056faaea224fbf37dd0 2020-09-23T13:24:30 90th Percentile of Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_p90 WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The 90th percentile of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 90th percentile of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_p90 http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_p90.nc ee5495a4d381e09383bb817c01295c5d1a67b80d 2020-09-23T13:24:30 Standard Deviation of Wave Energy Flux Earth Science | Oceans | Ocean Waves ww3.aus_4m.CgE_std WCS GeoTIFF Wave Energy Resource | Wave Energy Flux | Statistics The standard deviation of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The standard deviation of wave energy flux is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Wave energy flux, or wave power density, CgE, is a measure of the available power in the wave field, calculated as the kilowatts per meter (kW/m) of wave crest width. CgE is a spectrally derived time-series. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.CgE_std http://oa-gis.csiro.au/data/CgE/ww3.aus_4m.CgE_std.nc 76bc7f662414d9814e63b2c70453349623ce58c9 2020-09-23T13:24:30 Annual Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg WCS GeoTIFF Wave Energy Resource | Wave Direction | Statistics The annual mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The annual mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg.nc fe9591f84c2fc7b146730a0a3bba9f5c82492380 2020-09-23T13:24:30 (Month 01) January Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg01 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The January mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The January mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg01 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg01.nc 785bc024917485f4670fee9d78dff33206e9c4c2 2020-09-23T13:24:30 (Month 02) February Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg02 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The February mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The February mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg02 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg02.nc dfa5e19891a5943e36ffb429174018f68d2db998 2020-09-23T13:24:30 (Month 03) March Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg03 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The March mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The March mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg03 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg03.nc a9315d3133d7602019fdaf2ea3cdc610ed699b55 2020-09-23T13:24:31 (Month 04) April Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg04 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The April mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The April mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg04 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg04.nc 5bbb4023bf128e7aa3fc3ad7d1cb537f5f653aaa 2020-09-23T13:24:31 (Month 05) May Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg05 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The May mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The May mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg05 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg05.nc f5685f86726caaeafaf87a96de6a2a191382c770 2020-09-23T13:24:31 (Month 06) June Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg06 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The June mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The June mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg06 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg06.nc f4de55fb5f707bc84853374f35ac6560aa2a20c0 2020-09-23T13:24:31 (Month 07) July Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg07 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The July mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The July mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg07 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg07.nc b0cfd3e9ba894edc18a512ba1250f285e38c4ef0 2020-09-23T13:24:31 (Month 08) August Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg08 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The August mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The August mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg08 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg08.nc 067cfc4e3810a39f9a0405498649d9b3bfe08797 2020-09-23T13:24:31 (Month 09) September Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg09 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The September mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The September mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg09 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg09.nc d2fa9e721ef645740ca9e6a381f0792f4e6bf0de 2020-09-23T13:24:31 (Month 10) October Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg10 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The October mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The October mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg10 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg10.nc 639519c23e6d3fdacc63ddef45e4603172b9dc61 2020-09-23T13:24:31 (Month 11) November Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg11 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The November mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The November mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg11 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg11.nc 1e89c245c01bdeb9249c5c97ca81184a94532c5e 2020-09-23T13:24:31 (Month 12) December Mean Wave Direction Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Wave Speed/Direction ww3.aus_4m.dir_avg12 WCS GeoTIFF Wave Energy Resource | Wave Direction | Monthly Means The December mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The December mean wave direction is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. Mean wave direction, Dm, is obtained by averaging the mean wave angle over all frequencies with a weighting function defined by the wave spectrum, and is defined as the direction from which the wave field approaches. Units are in degrees clockwise measured from true north. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.dir_avg12 http://oa-gis.csiro.au/data/dir/ww3.aus_4m.dir_avg12.nc b1deffe18d4872bc98e8aafda829aa5a136fd362 2020-09-23T13:24:31 Annual Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg WCS GeoTIFF Wave Energy Resource | Wave Height | Statistics The annual mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The annual mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg.nc a73f5ec1442b2d520b0c601df661907764e7c0b5 2020-09-23T13:24:31 (Month 01) January Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg01 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The January mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The January mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg01 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg01.nc 73b34e110248c37cad11c12b85548114f2d45e40 2020-09-23T13:24:32 (Month 02) February Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg02 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The February mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The February mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg02 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg02.nc 763bcb630dacb69171f7c901664eecb6f967b000 2020-09-23T13:24:32 (Month 03) March Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg03 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The March mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The March mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg03 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg03.nc 3924044cc48e81adaa20252c18ae02ac15e2671b 2020-09-23T13:24:32 (Month 04) April Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg04 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The April mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The April mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg04 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg04.nc 1de5ac442e4111a49fbed0b7d6ae2a2b0937e416 2020-09-23T13:24:32 (Month 05) May Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg05 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The May mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The May mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg05 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg05.nc 009e87e4aff5d67af5baa5ab2412006d233b5820 2020-09-23T13:24:32 (Month 06) June Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg06 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The June mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The June mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg06 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg06.nc 228ef13f05039f334aa56d0f6173a9ffeac6f3ea 2020-09-23T13:24:32 (Month 07) July Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg07 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The July mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The July mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg07 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg07.nc c453352ca3b1b688b0413d4badb62b055969c729 2020-09-23T13:24:32 (Month 08) August Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg08 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The August mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The August mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg08 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg08.nc 69cc01a5acedb2078b1de6ba89b2f047c301ad7b 2020-09-23T13:24:32 (Month 09) September Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg09 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The September mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The September mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg09 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg09.nc 529dc543711feecebf3444c0f1eecb90a567b552 2020-09-23T13:24:32 (Month 10) October Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg10 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The October mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The October mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg10 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg10.nc 4e1fbf57076af3cd7568e2db1ce60b2ed023e307 2020-09-23T13:24:32 (Month 11) November Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg11 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The November mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The November mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg11 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg11.nc ce6de435f6ad80a4b74511fc69fd330d40e12ce8 2020-09-23T13:24:33 (Month 12) December Mean Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg12 WCS GeoTIFF Wave Energy Resource | Wave Height | Monthly Means The December mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The December mean significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg12 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg12.nc 816afec46beb9345508c72e6cbbfb64e48550264 2020-09-23T13:24:33 Monthly Variability of Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_avg_mv WCS GeoTIFF Wave Energy Resource | Wave Height | Statistics The monthly variability of significant wave height provides a convenient measure of the variability of the mean monthly wave height over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The monthly variability of significant wave height provides a convenient measure of the variability of the mean monthly wave height over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_avg_mv http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_avg_mv.nc 1cbe6a022a2ab20f87224683d10f74df15de1c4b 2020-09-23T13:24:33 Minimum Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_min WCS GeoTIFF Wave Energy Resource | Wave Height | Statistics The minimum significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The minimum significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_min http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_min.nc 331f56979930aeb51b0d62c431184fa1922210ec 2020-09-23T13:24:33 10th Percentile of Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_p10 WCS GeoTIFF Wave Energy Resource | Wave Height | Statistics The 10th percentile of significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 10th percentile of significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_p10 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_p10.nc d8c8d19bc0cadaf5786dda01e88e7a882d75bd36 2020-09-23T13:24:33 90th Percentile of Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_p90 WCS GeoTIFF Wave Energy Resource | Wave Height | Statistics The 90th percentile of significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 90th percentile of significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_p90 http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_p90.nc 32ded9d3ca55d6a739e2914bd8f68ac356980cc8 2020-09-23T13:24:33 Standard Deviation of Significant Wave Height Earth Science | Oceans | Ocean Waves Earth Science | Oceans | Ocean Waves | Significant Wave Height Earth Science | Oceans | Ocean Waves | Wave Height ww3.aus_4m.hs_std WCS GeoTIFF Wave Energy Resource | Wave Height | Statistics The standard deviation of significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The standard deviation of significant wave height is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. Significant wave height, Hs, represents the average height of the upper third of the waves in the wave-field, and roughly corresponds to the mean wave height as described by a trained observer. Hs is a spectrally derived time-series, calculated as Hs = 4√m0 , where m0 is the zero-th moment of the wave spectrum. More details can be found in the the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.hs_std http://oa-gis.csiro.au/data/hs/ww3.aus_4m.hs_std.nc 60dcca9549d2f24ac354bea21de6e0922044d042 2020-09-23T13:24:33 Annual Mean Directionality Coefficient ww3.aus_4m.jdc_avg WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The annual mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The annual mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.nc ebc715d2eb76add56ce12056a6fc8c84681af514 2020-09-23T13:24:33 (Month 01) January Mean Directionality Coefficient ww3.aus_4m.jdc_avg.01 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The January mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The January mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.01 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.01.nc 65540f082d707fd5249e744867587a24f6a197c8 2020-09-23T13:24:33 (Month 02) February Mean Directionality Coefficient ww3.aus_4m.jdc_avg.02 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The February mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The February mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.02 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.02.nc cef04e02f4f1f9dd2339e1bb34cae055cc15c7e9 2020-09-23T13:24:33 (Month 03) March Mean Directionality Coefficient ww3.aus_4m.jdc_avg.03 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The March mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The March mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.03 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.03.nc 4bf2c4f1a3e8483c7d57aa4814c4099b85f31d9c 2020-09-23T13:24:34 (Month 04) April Mean Directionality Coefficient ww3.aus_4m.jdc_avg.04 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The April mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The April mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.04 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.04.nc 189e9391de764a970f7edb414a87dbded882db39 2020-09-23T13:24:34 (Month 05) May Mean Directionality Coefficient ww3.aus_4m.jdc_avg.05 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The May mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The May mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.05 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.05.nc 220590a30ceaa68378a7bf8e5cd03444164f44a9 2020-09-23T13:24:34 (Month 06) June Mean Directionality Coefficient ww3.aus_4m.jdc_avg.06 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The June mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The June mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.06 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.06.nc b223b1285512b3db225e4ee9c88fb684dd96c99e 2020-09-23T13:24:34 (Month 07) July Mean Directionality Coefficient ww3.aus_4m.jdc_avg.07 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The July mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The July mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.07 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.07.nc 818b42060c842a072131e95e0efe311c0bb7c580 2020-09-23T13:24:34 (Month 08) August Mean Directionality Coefficient ww3.aus_4m.jdc_avg.08 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The August mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The August mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.08 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.08.nc ac4a389fa02947b2c06b58ac7cf5554611d8c2b0 2020-09-23T13:24:34 (Month 09) September Mean Directionality Coefficient ww3.aus_4m.jdc_avg.09 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The September mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The September mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.09 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.09.nc cf196c74d7af118237b3c9e82a4af5c0fcacf91e 2020-09-23T13:24:34 (Month 10) October Mean Directionality Coefficient ww3.aus_4m.jdc_avg.10 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The October mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The October mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.10 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.10.nc af1882ed9c1666d4a8fb4c94c1ba071689259009 2020-09-23T13:24:34 (Month 11) November Mean Directionality Coefficient ww3.aus_4m.jdc_avg.11 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The November mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The November mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.11 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.11.nc 7d729f2fbe3cfabf320b62e2ccb91796c3e8bfb6 2020-09-23T13:24:34 (Month 12) December Mean Directionality Coefficient ww3.aus_4m.jdc_avg.12 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Monthly Means The December mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The December mean directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg.12 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg.12.nc 4cdeeb7e95ba841dbfd3011924637a2d7880562e 2020-09-23T13:24:34 Monthly Variability of Directionality Coefficient ww3.aus_4m.jdc_avg_mv WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The monthly variability of directionality coefficient provides a convenient measure of the variability of the mean monthly directionality coefficient over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The monthly variability of directionality coefficient provides a convenient measure of the variability of the mean monthly directionality coefficient over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_avg_mv http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_avg_mv.nc b37d2ba95aca7edb1635b177461bec24009d8e8b 2020-09-23T13:24:35 Maximum Directionality Coefficient ww3.aus_4m.jdc_max WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The maximum directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The maximum directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_max http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_max.nc 942a3195ee312b261849d7905c8c6cfdab22368c 2020-09-23T13:24:35 Minimum Directionality Coefficient ww3.aus_4m.jdc_min WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The minimum directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The minimum directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_min http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_min.nc 3090f99511e293b43162d12cb9fe3af7f097f67f 2020-09-23T13:24:35 10th Percentile of Directionality Coefficient ww3.aus_4m.jdc_p10 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The 10th percentile of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 10th percentile of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_p10 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_p10.nc 88799413d48ad242ae74c30e6be2eaf07a82d42b 2020-09-23T13:24:35 50th Percentile of Directionality Coefficient ww3.aus_4m.jdc_p50 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The 50th percentile of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 50th percentile of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_p50 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_p50.nc http://oa-gis.csiro.au/images/layers/cb_ww3.aus_4m.jdc_p50.png 4c2ef9c86936a956db8b03b8c67883464ca14d95 2020-09-23T13:24:35 90th Percentile of Directionality Coefficient ww3.aus_4m.jdc_p90 WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The 90th percentile of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 90th percentile of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_p90 http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_p90.nc 1d3514d8eacbd8779e3a94b0b16ae129b826ccd5 2020-09-23T13:24:35 Standard Deviation of Directionality Coefficient ww3.aus_4m.jdc_std WCS GeoTIFF Wave Energy Resource | Wave Directionality Coefficient | Statistics The standard deviation of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The standard deviation of directionality coefficient is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionality coefficient is the fraction of directionally resolved wave power Jm to the omnidirectional wave power (or total wave power, CgE). An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). Note, accurate determination of directionality coefficient and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of directionality coefficient whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate directionality coefficient are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jdc_std http://oa-gis.csiro.au/data/jdc/ww3.aus_4m.jdc_std.nc b48439073d9bbeb12850d750c04f545f37e52a0e 2020-09-23T13:24:35 Annual Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The annual mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The annual mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.nc 413e4cfd6069c0956b22c6f1e2f93e985d7acb9d 2020-09-23T13:24:35 (Month 01) January Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg.01 WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The January mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The January mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.01 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.01.nc c33ff93d5c0548d3eb58b8e259715bf225714857 2020-09-23T13:24:35 (Month 02) February Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg.02 WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The February mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The February mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.02 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.02.nc 8de51247bd7d7d4cfb7bbdf5ba82021ad1773a3b 2020-09-23T13:24:35 (Month 03) March Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg.03 WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The March mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The March mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.03 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.03.nc 461b63d17e7caf6eb1c78e597f3ff1c27de9cfed 2020-09-23T13:24:36 (Month 04) April Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg.04 WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The April mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The April mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using April data from April 1980 to April 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.04 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.04.nc 2fed432991f8d79a2370e25ba9cc96cae2fbabac 2020-09-23T13:24:36 (Month 05) May Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg.05 WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The May mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The May mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using May data from May 1980 to May 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.05 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.05.nc a08cd99bd5a57b33ad7777d916ffdb24825f7868 2020-09-23T13:24:36 (Month 06) June Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg.06 WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The June mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The June mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using June data from June 1980 to June 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.06 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.06.nc 39c127e6913787c7686e32d31752a9c1b4085bfb 2020-09-23T13:24:36 (Month 07) July Mean Maximum Directionally Resolved Wave Power ww3.aus_4m.jm_avg.07 WCS GeoTIFF Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The July mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The July mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using July data from July 1980 to July 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.07 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.07.nc cb8f084230dda1e29f1ad7e6a25c35c89b755dd8 2020-09-23T13:24:36 (Month 08) August Mean Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The August mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The August mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using August data from August 1980 to August 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.08 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.08.nc b368b29707f5ae19e8799e10b7f0a4d01d89a6a4 2020-09-23T13:24:36 (Month 09) September Mean Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The September mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The September mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using September data from September 1980 to September 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.09 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.09.nc d4f1f023fde02bf37729b1a9f0b28f2f66d50b6c 2020-09-23T13:24:36 (Month 10) October Mean Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The October mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The October mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using October data from October 1980 to October 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.10 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.10.nc 666337b737bf4cb27d273c7f1c5d31f7f8b6b9ba 2020-09-23T13:24:36 (Month 11) November Mean Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The November mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The November mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using November data from November 1980 to November 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.11 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.11.nc 396c7a35d551be30891112299dd9af898a2a44d5 2020-09-23T13:24:36 (Month 12) December Mean Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Monthly Means The December mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The December mean maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using December data from December 1980 to December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg.12 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg.12.nc ccbf730b027141995c3914c6da0b68058e7bbee6 2020-09-23T13:24:36 Monthly Variability of Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The monthly variability of maximum directionally resolved wave power provides a convenient measure of the variability of the mean monthly maximum directionally resolved wave power over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The monthly variability of maximum directionally resolved wave power provides a convenient measure of the variability of the mean monthly maximum directionally resolved wave power over a typical year. It is determined as maximum range of the mean monthly annual cycle calculated from the CAWCR global wave hindcast. The mean monthly annual cycles were determined using the archived hourly 4’ Australian grid from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_avg_mv http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_avg_mv.nc 3d05cd97ed1754ee0a0b405256f982b328395ea0 2020-09-23T13:24:36 Maximum of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The maximum of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The maximum of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_max http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_max.nc 9cbacf672e2fd6aaad82de89ab53f050ada45ecd 2020-09-23T13:24:37 Minimum of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The minimum of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The minimum of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_min http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_min.nc 4bdc4f90e1aa1615a185a06f2f7d0dc4db62a9a1 2020-09-23T13:24:37 10th Percentile of Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The 10th percentile of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 10th percentile of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_p10 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_p10.nc 3a041b1efb042558a79552b9b5bbb8befaee3a6c 2020-09-23T13:24:37 50th Percentile of Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The 50th percentile of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 50th percentile of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_p50 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_p50.nc 2eb6a19b12f4c49413469edfb16f32a7c6dadc16 2020-09-23T13:24:37 90th Percentile of Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The 90th percentile of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The 90th percentile of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_p90 http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_p90.nc cc571315d92587078d9d6d63722ecdc58d80a185 2020-09-23T13:24:37 Standard Deviation of Maximum Directionally Resolved Wave Power Wave Energy Resource | Maximum Directionally Resolved Wave Power | Statistics The standard deviation of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The standard deviation of maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The directionally resolved wave power propagating in direction 0, J0, can be calculated by resolving the wave power of each component in direction 0. An equation describing its calculation can be found in the the atlas report (Hemer et al., 2016). J0 is determined at for 0 at 15° intervals, and the maximum directionally resolved wave power, Jm, represents the maximum time-averaged wave power propagating in a single direction. Note, accurate determination of J0 and Jm require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. These data provide estimates of Jm whereby spectra are reconstructed using archived gridded wave partition data, with a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. For consistency in this estimate, the omnidirectional wave power is determined from the reconstructed spectra, and not the archived CgE presented elsewhere. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jm_std http://oa-gis.csiro.au/data/jm/ww3.aus_4m.jm_std.nc 1e1fce18507dddfd943de41985372c82019bf4cb 2020-09-23T13:24:37 Annual Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Statistics The annual mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The annual mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using data from 1st January 1980 to 31st December 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jthm_avg http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.nc e4436536d9ce4f82ed8c5d0b6f1c0bc90c3cc346 2020-09-23T13:24:37 (Month 01) January Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The January mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The January mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using January data from January 1980 to January 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jthm_avg.01 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.01.nc 62d8a575e09d2c54cee6eda7530060d1276ad330 2020-09-23T13:24:37 (Month 02) February Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The February mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The February mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using February data from February 1980 to February 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jthm_avg.02 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.02.nc 4d7de470af87df835815ed402ed8db32535fc3ed 2020-09-23T13:24:37 (Month 03) March Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The March mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. The March mean direction of the maximum directionally resolved wave power is derived from the CAWCR global wave hindcast, using data from the archived hourly 4’ Australian grid, using March data from March 1980 to March 2010. The direction of the maximum directionally resolved wave power is 0j and is used as the characteristic direction of the sea-state. Note, accurate determination of the directionally resolved wave power, J0, and its maximum, Jm, and hence 0j require spectral data, which was not archived at all grid points of the CAWCR wave hindcast. Here, we provide estimates of Jm using spectra reconstructed with archived gridded wave partition data, assuming a Pierson-Moskowitz spectra fit to each partition, with assumed spreading, and superimposed to produce a reconstructed spectra. Further details of the method used to estimate Jm are provided in the atlas report (Hemer et al., 2016). For further information on the CAWCR wave hindcast, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information. Input data: NCEP CFSv2 surface winds and sea ice, http://cfs.ncep.noaa.gov. Wave model used: WaveWatch III, http://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml The Centre for Australian Weather and Climate Research (CAWCR) is a partnership between the Bureau of Meteorology and CSIRO. Hindcast modelling undertaken as part of the PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) Project 4.3 "High resolution wind-wave climate and projections of change in the Pacific region for coastal hazard assessments" in 2012, funded by DCCEE and AusAID and undertaken jointly by CSIRO and the BoM. This dataset was produced as part of the Australian Renewable Energy Agency – CSIRO Oceans and Atmosphere Flagship co-funded Australian Wave Energy Atlas Project. Bureau of Meteorology Australia CSIRO Australia 175.00038146972656 -49.999998331069946 100.0 3.000264883041382 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=awavea2019%3Aww3.aus_4m.jthm_avg.03 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.03.nc