2332ac78f1ed0c62321cf33063f19dd82e3ae712 2020-09-23T13:24:37 (Month 04) April Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The April 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 April data from April 1980 to April 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 April 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 April data from April 1980 to April 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.04 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.04.nc cfd8386e4743db07fee495566178cd1f3aa0ef1d 2020-09-23T13:24:38 (Month 05) May Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The May 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 May data from May 1980 to May 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 May 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 May data from May 1980 to May 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.05 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.05.nc 671faa63cd0e91ec24e51e686d8e8c22973bca96 2020-09-23T13:24:38 (Month 06) June Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The June 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 June data from June 1980 to June 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 June 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 June data from June 1980 to June 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.06 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.06.nc 410f37124da4cc1a428eb74502ec6f5794e5d177 2020-09-23T13:24:38 (Month 07) July Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The July 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 July data from July 1980 to July 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 July 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 July data from July 1980 to July 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.07 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.07.nc df99d085d9a751a14eeafc2aad760bd85d1b1106 2020-09-23T13:24:38 (Month 08) August Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The August 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 August data from August 1980 to August 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 August 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 August data from August 1980 to August 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.08 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.08.nc 088b678f10adaec4f62f050cf9402ec16d80d8af 2020-09-23T13:24:20 Australian Ship Reporting System - Shipping Summaries 1999-2011 Multiple Use | Shipping 179.699999999988 -77.699999999999 -179.3 57.0000000000014 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://www.marlin.csiro.au/geonetwork/srv/eng/search#!b8135966-33c6-4a1c-bcbc-d797c2a1155f a70dbd5d7cd12630c00cbdafd1e0bb4800926503 2020-09-23T13:24:20 2D and 3D surveys 1961-2010 Oceans Solid Earth | Natural Resources | Petroleum Multiple Use | Seismic Surveys This data set is a summary of seismic survey transects from 1961 to 2015. The data was summarised to 0.1 deg grids and the number of km of the grid surveyed over a 5 year period was calculated. Geoscience Australia is releasing its 2014 version of the Marine Seismic Surveys Shape and Kml files. These files have been updated to include recent openfile surveys. The spatial files have been created from a cleansed, updated collection of p190 navigation files. This navigation collection has grown from the checking of navigation submitted to the GA Repository under the Offshore Petroleum and Greenhouse Gas Storage Regulations http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_f5f24293-c9c1-6ed9-e044-00144fdd4fa6/Marine+Seismic+Survey+Shape+and+Kml+Files+-+2014+Version This data contains geographical information in shapefiles that represent 2D and 3D seismic surveys from 1961 to 2013.They represent most of the seismic surveys shot around Australia. According to Mike Sexton (pers. comm., 2013; GA) 3D surveys are modern surveys that shoot with multiple cables, acquiring many times more data than a 2D survey. The cables have no impact on the environment. Over time, seismic surveys have used a variety of sources commencing with dynamite in the 1960s (usually 50 lbs, but sometimes 200 lbs). The shot spacing was usually of the order of 200 m. Since then, electrical discharges (sparkers), gas-exploders, vibratory sources and air guns have been used. The shot interval has been reduced to about 20 m. This data set is a summary of seismic survey transects from 1961 to 2015. The data was summarised to 0.1 deg grids and the number of km of the grid surveyed over a 5 year period was calculated. Geoscience Australia is releasing its 2014 version of the Marine Seismic Surveys Shape and Kml files. These files have been updated to include recent openfile surveys. The spatial files have been created from a cleansed, updated collection of p190 navigation files. This navigation collection has grown from the checking of navigation submitted to the GA Repository under the Offshore Petroleum and Greenhouse Gas Storage Regulations http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_f5f24293-c9c1-6ed9-e044-00144fdd4fa6/Marine+Seismic+Survey+Shape+and+Kml+Files+-+2014+Version This data contains geographical information in shapefiles that represent 2D and 3D seismic surveys from 1961 to 2013.They represent most of the seismic surveys shot around Australia. According to Mike Sexton (pers. comm., 2013; GA) 3D surveys are modern surveys that shoot with multiple cables, acquiring many times more data than a 2D survey. The cables have no impact on the environment. Over time, seismic surveys have used a variety of sources commencing with dynamite in the 1960s (usually 50 lbs, but sometimes 200 lbs). The shot spacing was usually of the order of 200 m. Since then, electrical discharges (sparkers), gas-exploders, vibratory sources and air guns have been used. The shot interval has been reduced to about 20 m. Geoscience Australia (GA) 177.635498046875 -57.3535041809082 102.143989562988 -0.650499939918518 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://www.marlin.csiro.au/geonetwork/srv/eng/search#!17249677-2be0-43a0-a9b5-da01e0be3fa7 3cc43753c5a1abdf254b6524500020ffe58abcdf 2020-09-23T13:24:20 Sea Surface Temperature Long Term Trend SE - 1993-2013 Oceans | Ocean Temperature | Sea Surface Temperature WCS GeoTIFF ALTTSE_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 8aa7ef0738ec6111243cc5a7c029e306a16b7f74 2020-09-23T13:24:20 Sea Surface Temperature Long Term Trend - 1993-2013 Oceans | Ocean Temperature | Sea Surface Temperature WCS GeoTIFF ALTT_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 48e0cdba146a901bc7ab63fd88807413e1deed03 2020-09-23T13:24:20 Banks Strait Model Grid features banks66_model Tidal Energy | Context Layers "Full Geometry of regional Banks Strait Tidal Model grid " "Full Geometry of regional Banks Strait Tidal Model grid " 149.502321 -41.738328 146.380037 -37.771658 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%3ABankStraitModelGrid e47ab24a1833ffdb3a86c44121b2f2e2bee7e92b 2020-09-23T13:24:20 Clarence Strait Model Grid features clarence68-face Tidal Energy | Context Layers "Full Geometry of regional Clarence Strait Tidal Model grid " "Full Geometry of regional Clarence Strait Tidal Model grid " 132.962415 -12.802737 129.5 -10.5 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%3AClarenceStraitModelGrid 81639246bd4827b3b3a3923909729cc4b093cbab 2020-09-23T13:24:20 Sea Surface Temperature Annual RMSE - 1993-2013 Oceans | Ocean Temperature | Sea Surface Temperature WCS GeoTIFF annualRMSE_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 a4b7037e1ce52c2060e3cf896bbe986fa76fb48e 2020-09-23T13:24:20 Full National Tidal Model Geometry out38 features Tidal Energy | Context Layers "Full Geometry of Tidal Model grid (Very large)" "Full Geometry of Tidal Model grid (Very large)" 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%3AausTidalModelGeom 5c0b03c6a829fe98acc9a9ded66441a78852592e 2020-09-23T13:24:21 0th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Banks Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_drangepc-ti0 b693312794d1a6d58b6e43b1242a60495e4b40e0 2020-09-23T13:24:21 10th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Banks Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_drangepc-ti1 c5d40535230539966d48b37abb6a779c5a55b454 2020-09-23T13:24:21 20th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Banks Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_drangepc-ti2 16724455f8171f04a0a1aa6fbf2e9cdb99c07531 2020-09-23T13:24:21 50th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Banks Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_drangepc-ti5 7ec1f1d6e69908f63c1602cee7aa44c61b604b35 2020-09-23T13:24:21 80th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Banks Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_drangepc-ti8 cdcc8bce85cfcd062b5f17d38ca772c437bd2046 2020-09-23T13:24:21 90th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Banks Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_drangepc-ti9 7aa482be93f59f7353c3ddc72dc81ebebe77b5e1 2020-09-23T13:24:21 Mean Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefmean-ti0 1cca7924cfefb329716e027b5d0d33cf5e0284f0 2020-09-23T13:24:21 0th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefpc-ti0 cfa3dc7a98586dad30bb69ed3b534878503c371b 2020-09-23T13:24:21 10th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefpc-ti1 158e5890011d470eeed03024d1eff87b6f7f4a7a 2020-09-23T13:24:21 100th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefpc-ti10 ae2180c925b3dcb293c3b10ee5661f2aceb1cfd8 2020-09-23T13:24:21 20th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefpc-ti2 f0c8a6bf7f41404760830e02678f6fee2e9f8ac6 2020-09-23T13:24:21 50th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefpc-ti5 dbaae09680d9b764da0deab678568a7163d957ca 2020-09-23T13:24:22 80th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefpc-ti8 4d4b4de369abdd53dbe7c6d7c8d6ae9347d77b32 2020-09-23T13:24:22 90th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Banks Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_kefpc-ti9 0b170128910a00e90d51f652381e74842a9a6a6c 2020-09-23T13:24:22 Mean Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_spmean d261e31051f32b59f542517ba66130fe40f14e30 2020-09-23T13:24:22 0th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_sppc-ti0 475697174f63976548bdd5acea52b66b591073fa 2020-09-23T13:24:22 10th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_sppc-ti1 5a1f7f1f88acde3ec7996a825693a46a6cfeca0d 2020-09-23T13:24:22 100th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_sppc-ti10 a317471417cb89bea0e8efb936323d890355626d 2020-09-23T13:24:22 20th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_sppc-ti2 d216e4e442c96012da46a7b9d6fdc13a27f925f5 2020-09-23T13:24:22 50th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_sppc-ti5 1067cf01a96aaa1f89295157209af86ebb036216 2020-09-23T13:24:22 80th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_sppc-ti8 5b4aa84ef80d4ec6d30bd58c6b78234fdd5e7025 2020-09-23T13:24:22 90th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Banks Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 149.500037 -41.738328 146.380037 -37.768328000000004 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%3Abanks_sppc-ti9 5237b239139fdbbec1a2649a2953f1315b31702c 2020-09-23T13:24:22 0th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Clarence Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_drangepc-ti0 e5630828aa55786f9b4d739a1859a808e5694892 2020-09-23T13:24:22 10th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Clarence Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_drangepc-ti1 0e54c0036af81199969654e6479110e716463308 2020-09-23T13:24:23 20th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Clarence Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_drangepc-ti2 1cb5f00cf3df500fc1177c3da0d506af5cc2a1f5 2020-09-23T13:24:23 50th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Clarence Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_drangepc-ti5 d66ea4708c2725af515ae400a4c606bbd5a70863 2020-09-23T13:24:23 80th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Clarence Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_drangepc-ti8 ee9e0882db66fccdb36df62de2470d00eb9e1046 2020-09-23T13:24:23 90th percentile of Tidal Range Tidal Energy | Tidal Range | Percentile Tidal Range | Clarence Strait Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_drangepc-ti9 8cd358c152dcc2a10f05f08b1ba3796c7507bd7c 2020-09-23T13:24:23 Mean Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefmean-ti0 0511dc104c94d796829c28991ba8d634395419c8 2020-09-23T13:24:23 0th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefpc-ti0 e726b88fb43599640c1659ca34c19e7bc9185a8e 2020-09-23T13:24:23 10th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefpc-ti1 85be16a145565fbb6ff1ee4e0021c28b53015894 2020-09-23T13:24:23 100th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefpc-ti10 580ce0e456b76df61a44743cb009059ad59ce52f 2020-09-23T13:24:23 20th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefpc-ti2 c525ed057f3a4a0da590e65f02d594ea7a4e7fc7 2020-09-23T13:24:23 50th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefpc-ti5 12f7599a43e17a171826916bd14acb64e0079ec1 2020-09-23T13:24:23 80th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefpc-ti8 cbbfd5345e1d8129b0c7c13ed714a302bd953407 2020-09-23T13:24:23 90th percentile of Tidal Stream Kinetic Energy Flux Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | Clarence Strait Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_kefpc-ti9 c9c0ef4ac8a63837c7c196b08375437035407290 2020-09-23T13:24:24 0th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Clarence Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_sppc-ti0 b793fe73171deeb1606db3f759077f4eb97a6e9a 2020-09-23T13:24:24 10th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Clarence Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_sppc-ti1 a426449b97d6d3964a669a5f6db4159140c08901 2020-09-23T13:24:24 100th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Clarence Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_sppc-ti10 760458a652149910f2bc39475fc51c504cc94aa8 2020-09-23T13:24:24 20th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Clarence Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_sppc-ti2 cd04f8af028b5485b57d561f538e80e246bde2d7 2020-09-23T13:24:24 50th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Clarence Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_sppc-ti5 c281d2935f2797c69c8f4d38792d5b8f784bd612 2020-09-23T13:24:24 80th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Clarence Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_sppc-ti8 2bfe8cff7ca5b6abcefa7f8b2ae4385056eb7aa8 2020-09-23T13:24:24 90th percentile of Tidal Current Speed Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | Clarence Strait Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 132.96 -12.802737 129.5 -10.502737 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%3Aclarence_sppc-ti9 c532af2a50f8e5985f62012dbe4b66aba34528d5 2020-09-23T13:24:24 Sea Surface Temperature Efold - 1993-2013 Oceans | Ocean Temperature | Sea Surface Temperature WCS GeoTIFF efold_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 3ca6960867480edb24d4a64358cfd29531095cfa 2020-09-23T13:24:19 Derived Observations on Model Tidal Energy | Context Layers "Grid cells of Derived Observations on model grid" "Grid cells of Derived Observations on model grid" 154.977544 -44.602387 110.465775 -6.848585 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& 921c102e3b3bbc811936446572b928330206359f 2020-09-23T13:24:20 AFMA Fisheries Effort 2011-2014 Agriculture | Agricultural Aquatic Sciences | Fisheries Oceans | Marine Biology | Fish Multiple Use | Fisheries Effort This data set contains summaries of AFMA log book data on effort distribution for Commonwealth fisheries in the Australian Exclusive Economic Zone (excluding Cocos and Christmas Islands, Norfolk Island and the Sub-Antarctic Fisheries). The logbook data has been recorded and submitted to AFMA by commercial fishers. The data has been aggregated to produce summaries of total effort by gear type (summarised across fishery), over 5 year periods and at a 0.1 degree resolution where 5 boats or more operate. All effort information has been removed for areas where less than 5 boats operate and these areas are mapped to a 1 degree resolution. The 5 years periods (1996-2000, 2001-2005 and 2006-2010) correspond to State of Environment (SoE) Reporting, required under the EPBC Act 1999. The most recent reporting period (2011-14) is a four year period. Each is labelled by the years aggregated (ie 2001-2005) and the gear type (ie LLP = long line pelagic). The gear codes and aggregated fisheries and the shape file field descriptions are listed below. Notes: 1. Care needs to be taken when interpreting the fishing effort maps because in areas where there are less than 5 boats operating only the fishing footprint is displayed, consistent with the AFMA Information Disclosure Policy. The fishing footprint indicates that fishing occurred but does not provide information about the intensity of effort (number of operations etc). 2. Legal fishing by foreign flagged vessels occurred in the 1980s and early 1990s in the Australian Fishing Zone. These are shown as areas of higher effort in (i) trawl maps prior to 1990 north of Arnhem Land and (ii) pelagic longline maps up until 1997 south of Tasmania. 3. Minor line was historically recorded as a method in some of AFMA’s daily fishing logbooks, but is not in AFMAs current fishery logbooks. Minor line means trolling, or fishing using a rod or reel, handline or pole. 4. Trawl effort maps are missing Torres Strait Prawn Fishery data prior to 2004. 5. Gillnet effort maps prior to 1996 are not included due to data incompleteness. 6. Jigging data is currently incomplete and is not included. 7. Three records of Danish Seine were misreported (between 1996 and 2010) in the area of the Great Barrier Reef and have been removed. 8. Minor line was historically recorded as a method in some of AFMA’s daily fishing logbooks, but is not in AFMAs current fishery logbooks. Minor line means trolling, or fishing using a rod or reel, handline or pole. 9. Disclaimer: The data provided by AFMA may contain errors or be incomplete. AFMA makes no warranty or representation that the data is accurate or complete. Those who choose to use this data should make their own enquiries as to its accuracy and completeness and AFMA assumes no liability for any errors or omissions in the data provided, or for any decision by a person who chooses to rely on the data. ################################################# Field descriptions for shapefiles: CSQ_CODE: C-Squares code. 1 degree and 0.1 degree grids used CSQ_RESLN: C-Squares resolution of current polygon VESSELS: Number of vessels OPERATIONS: Number of operations HOURS: Effort in hours from start and end time HOOKSSET: Total hooks set NUMLINES: Number of lines deployed NETLENGTH: Gillnet Net Length Fishery Aggregations GEAR_CODE_CSIRO GEAR_CODE_CSIRO_DESCN FISHERY NAME AL Auto Longline CSF Coral Sea Fishery AL Auto Longline GHT Gillnet, Hook and Trap Fishery AL Auto Longline SEN South East Non-Trawl Fishery AL Auto Longline TUN Tuna Fishery BL Demersal Longline CSF Coral Sea Fishery BL Demersal Longline ECT Eastern Tuna & Billfish Fishery BL Demersal Longline GHT Gillnet, Hook and Trap Fishery BL Demersal Longline SEN South East Non-Trawl Fishery BL Demersal Longline SSF Southern Shark Fishery BL Demersal Longline SSG Southern Shark Gillnet Fishery BL Demersal Longline SSH Southern Shark Hook Fishery DS Danish Seine GAB Great Australian Bight Fishery DS Danish Seine SET South East Trawl Fishery DS Danish Seine VIT Victorian Inshore Trawl Fishery DS Danish Seine WDW Western Deep Water Trawl Fishery GN Gillnet ECT Eastern Tuna & Billfish Fishery GN Gillnet GHT Gillnet, Hook and Trap Fishery GN Gillnet SEN South East Non-Trawl Fishery GN Gillnet SSF Southern Shark Fishery GN Gillnet SSG Southern Shark Gillnet Fishery GN Gillnet SSH Southern Shark Hook Fishery HL Handline CSF Coral Sea Fishery HL Handline ECT Eastern Tuna & Billfish Fishery HL Handline GHT Gillnet, Hook and Trap Fishery HL Handline SEN South East Non-Trawl Fishery HL Handline SSF Southern Shark Fishery HL Handline SSG Southern Shark Gillnet Fishery HL Handline SSH Southern Shark Hook Fishery HL Handline TUN Tuna Fishery HL Handline WTB Western Tuna and Billfish HL Handline WTF Southern & Western Tuna & Billfish Fishery J Jigging SPF Small Pelagic Fishery J Jigging SQJ Southern Squid Fishery J Jigging SQD Squid Fishery J Jigging SSF Southern Shark Fishery J Jigging SEN South East Non-Trawl Fishery LLP Pelagic Longline ECT Eastern Tuna & Billfish Fishery LLP Pelagic Longline TUN Tuna Fishery LLP Pelagic Longline WTB Western Tuna and Billfish LLP Pelagic Longline WTF Southern & Western Tuna & Billfish Fishery ML Minor Line ECT Eastern Tuna & Billfish Fishery ML Minor Line WTB Western Tuna and Billfish ML Minor Line WTF Southern & Western Tuna & Billfish Fishery PB Pole & Bait TUN Tuna Fishery PB Pole & Bait ECT Eastern Tuna & Billfish Fishery PB Pole & Bait GHT Gillnet, Hook and Trap Fishery PB Pole & Bait JMF Jack Mackerel Fishery PB Pole & Bait SBT Southern Bluefin Tuna Fishery PB Pole & Bait SEN South East Non-Trawl Fishery PB Pole & Bait WTB Western Tuna and Billfish PB Pole & Bait WTF Southern & Western Tuna & Billfish Fishery PS Purse Seine ECT Eastern Tuna & Billfish Fishery PS Purse Seine EST Eastern Skipjack Fishery PS Purse Seine JMF Jack Mackerel Fishery PS Purse Seine SBT Southern Bluefin Tuna Fishery PS Purse Seine SPF Small Pelagic Fishery PS Purse Seine TUN Tuna Fishery PS Purse Seine WST Western Skipjack Fishery PS Purse Seine WTF Southern & Western Tuna & Billfish Fishery TL Trotline CSF Coral Sea Fishery TL Trotline ECT Eastern Tuna & Billfish Fishery TL Trotline GHT Gillnet, Hook and Trap Fishery TL Trotline SEN South East Non-Trawl Fishery TL Trotline TUN Tuna Fishery TR Trolling CSF Coral Sea Fishery TR Trolling ECT Eastern Tuna & Billfish Fishery TR Trolling SSF Southern Shark Fishery TR Trolling TSF Torres Strait Fishery TR Trolling WTF Southern & Western Tuna & Billfish Fishery TW Trawling CSF Coral Sea Fishery TW Trawling ECD East Coast Deepwater Trawl Fishery TW Trawling GAB Great Australian Bight Fishery TW Trawling JMF Jack Mackerel Fishery TW Trawling NPF Northern Prawn Fishery TW Trawling NWS North West Slope Trawl Fishery TW Trawling SET South East Trawl Fishery TW Trawling SPF Small Pelagic Fishery TW Trawling STR South Tasman Rise Fishery TW Trawling TSP Torres Strait Prawn Fishery TW Trawling TUN Tuna Fishery TW Trawling VIT Victorian Inshore Trawl Fishery TW Trawling WDW Western Deep Water Trawl Fishery This data set contains summaries of AFMA log book data on effort distribution for Commonwealth fisheries in the Australian Exclusive Economic Zone (excluding Cocos and Christmas Islands, Norfolk Island and the Sub-Antarctic Fisheries). The logbook data has been recorded and submitted to AFMA by commercial fishers. The data has been aggregated to produce summaries of total effort by gear type (summarised across fishery), over 5 year periods and at a 0.1 degree resolution where 5 boats or more operate. All effort information has been removed for areas where less than 5 boats operate and these areas are mapped to a 1 degree resolution. The 5 years periods (1996-2000, 2001-2005 and 2006-2010) correspond to State of Environment (SoE) Reporting, required under the EPBC Act 1999. The most recent reporting period (2011-14) is a four year period. Each is labelled by the years aggregated (ie 2001-2005) and the gear type (ie LLP = long line pelagic). The gear codes and aggregated fisheries and the shape file field descriptions are listed below. Notes: 1. Care needs to be taken when interpreting the fishing effort maps because in areas where there are less than 5 boats operating only the fishing footprint is displayed, consistent with the AFMA Information Disclosure Policy. The fishing footprint indicates that fishing occurred but does not provide information about the intensity of effort (number of operations etc). 2. Legal fishing by foreign flagged vessels occurred in the 1980s and early 1990s in the Australian Fishing Zone. These are shown as areas of higher effort in (i) trawl maps prior to 1990 north of Arnhem Land and (ii) pelagic longline maps up until 1997 south of Tasmania. 3. Minor line was historically recorded as a method in some of AFMA’s daily fishing logbooks, but is not in AFMAs current fishery logbooks. Minor line means trolling, or fishing using a rod or reel, handline or pole. 4. Trawl effort maps are missing Torres Strait Prawn Fishery data prior to 2004. 5. Gillnet effort maps prior to 1996 are not included due to data incompleteness. 6. Jigging data is currently incomplete and is not included. 7. Three records of Danish Seine were misreported (between 1996 and 2010) in the area of the Great Barrier Reef and have been removed. 8. Minor line was historically recorded as a method in some of AFMA’s daily fishing logbooks, but is not in AFMAs current fishery logbooks. Minor line means trolling, or fishing using a rod or reel, handline or pole. 9. Disclaimer: The data provided by AFMA may contain errors or be incomplete. AFMA makes no warranty or representation that the data is accurate or complete. Those who choose to use this data should make their own enquiries as to its accuracy and completeness and AFMA assumes no liability for any errors or omissions in the data provided, or for any decision by a person who chooses to rely on the data. ################################################# Field descriptions for shapefiles: CSQ_CODE: C-Squares code. 1 degree and 0.1 degree grids used CSQ_RESLN: C-Squares resolution of current polygon VESSELS: Number of vessels OPERATIONS: Number of operations HOURS: Effort in hours from start and end time HOOKSSET: Total hooks set NUMLINES: Number of lines deployed NETLENGTH: Gillnet Net Length Fishery Aggregations GEAR_CODE_CSIRO GEAR_CODE_CSIRO_DESCN FISHERY NAME AL Auto Longline CSF Coral Sea Fishery AL Auto Longline GHT Gillnet, Hook and Trap Fishery AL Auto Longline SEN South East Non-Trawl Fishery AL Auto Longline TUN Tuna Fishery BL Demersal Longline CSF Coral Sea Fishery BL Demersal Longline ECT Eastern Tuna & Billfish Fishery BL Demersal Longline GHT Gillnet, Hook and Trap Fishery BL Demersal Longline SEN South East Non-Trawl Fishery BL Demersal Longline SSF Southern Shark Fishery BL Demersal Longline SSG Southern Shark Gillnet Fishery BL Demersal Longline SSH Southern Shark Hook Fishery DS Danish Seine GAB Great Australian Bight Fishery DS Danish Seine SET South East Trawl Fishery DS Danish Seine VIT Victorian Inshore Trawl Fishery DS Danish Seine WDW Western Deep Water Trawl Fishery GN Gillnet ECT Eastern Tuna & Billfish Fishery GN Gillnet GHT Gillnet, Hook and Trap Fishery GN Gillnet SEN South East Non-Trawl Fishery GN Gillnet SSF Southern Shark Fishery GN Gillnet SSG Southern Shark Gillnet Fishery GN Gillnet SSH Southern Shark Hook Fishery HL Handline CSF Coral Sea Fishery HL Handline ECT Eastern Tuna & Billfish Fishery HL Handline GHT Gillnet, Hook and Trap Fishery HL Handline SEN South East Non-Trawl Fishery HL Handline SSF Southern Shark Fishery HL Handline SSG Southern Shark Gillnet Fishery HL Handline SSH Southern Shark Hook Fishery HL Handline TUN Tuna Fishery HL Handline WTB Western Tuna and Billfish HL Handline WTF Southern & Western Tuna & Billfish Fishery J Jigging SPF Small Pelagic Fishery J Jigging SQJ Southern Squid Fishery J Jigging SQD Squid Fishery J Jigging SSF Southern Shark Fishery J Jigging SEN South East Non-Trawl Fishery LLP Pelagic Longline ECT Eastern Tuna & Billfish Fishery LLP Pelagic Longline TUN Tuna Fishery LLP Pelagic Longline WTB Western Tuna and Billfish LLP Pelagic Longline WTF Southern & Western Tuna & Billfish Fishery ML Minor Line ECT Eastern Tuna & Billfish Fishery ML Minor Line WTB Western Tuna and Billfish ML Minor Line WTF Southern & Western Tuna & Billfish Fishery PB Pole & Bait TUN Tuna Fishery PB Pole & Bait ECT Eastern Tuna & Billfish Fishery PB Pole & Bait GHT Gillnet, Hook and Trap Fishery PB Pole & Bait JMF Jack Mackerel Fishery PB Pole & Bait SBT Southern Bluefin Tuna Fishery PB Pole & Bait SEN South East Non-Trawl Fishery PB Pole & Bait WTB Western Tuna and Billfish PB Pole & Bait WTF Southern & Western Tuna & Billfish Fishery PS Purse Seine ECT Eastern Tuna & Billfish Fishery PS Purse Seine EST Eastern Skipjack Fishery PS Purse Seine JMF Jack Mackerel Fishery PS Purse Seine SBT Southern Bluefin Tuna Fishery PS Purse Seine SPF Small Pelagic Fishery PS Purse Seine TUN Tuna Fishery PS Purse Seine WST Western Skipjack Fishery PS Purse Seine WTF Southern & Western Tuna & Billfish Fishery TL Trotline CSF Coral Sea Fishery TL Trotline ECT Eastern Tuna & Billfish Fishery TL Trotline GHT Gillnet, Hook and Trap Fishery TL Trotline SEN South East Non-Trawl Fishery TL Trotline TUN Tuna Fishery TR Trolling CSF Coral Sea Fishery TR Trolling ECT Eastern Tuna & Billfish Fishery TR Trolling SSF Southern Shark Fishery TR Trolling TSF Torres Strait Fishery TR Trolling WTF Southern & Western Tuna & Billfish Fishery TW Trawling CSF Coral Sea Fishery TW Trawling ECD East Coast Deepwater Trawl Fishery TW Trawling GAB Great Australian Bight Fishery TW Trawling JMF Jack Mackerel Fishery TW Trawling NPF Northern Prawn Fishery TW Trawling NWS North West Slope Trawl Fishery TW Trawling SET South East Trawl Fishery TW Trawling SPF Small Pelagic Fishery TW Trawling STR South Tasman Rise Fishery TW Trawling TSP Torres Strait Prawn Fishery TW Trawling TUN Tuna Fishery TW Trawling VIT Victorian Inshore Trawl Fishery TW Trawling WDW Western Deep Water Trawl Fishery 163.240005493164 -47.2722854614258 113.0 -9.18199253082275 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://www.marlin.csiro.au/geonetwork/srv/eng/search#!aa53a4df-7fe6-46d1-93b7-2d3732f4883e b67acd48003437e1b2dbaa0f8eb134f55d30c645 2020-09-23T13:24:27 10th percentile of Tidal Current Speed raster_sppc-ti1 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | National Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 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%3Araster_sppc_ti1 e21857179ac082cfceefe4d64942a6421760f982 2020-09-23T13:24:27 100th percentile of Tidal Current Speed raster_sppc-ti10 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | National Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 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%3Araster_sppc_ti10 ef4a487bb6e8b5d0e4d2551d85956e43650d57a4 2020-09-23T13:24:27 20th percentile of Tidal Current Speed raster_sppc-ti2 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | National Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 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%3Araster_sppc_ti2 0c4fb905f228e26b462474a7ddb3ad9c2dd313e3 2020-09-23T13:24:27 50th percentile of Tidal Current Speed raster_sppc-ti5 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | National Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 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%3Araster_sppc_ti5 61a118933e78fe59a674ffb4bbced7963e8d1137 2020-09-23T13:24:27 80th percentile of Tidal Current Speed raster_sppc-ti8 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | National Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 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%3Araster_sppc_ti8 575559e71b2dd986e805b88d39e98520a713e00d 2020-09-23T13:24:27 90th percentile of Tidal Current Speed raster_sppc-ti9 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | National Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 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%3Araster_sppc_ti9 420ea67c0240e235a418b280ee2e744c140b1f97 2020-09-23T13:24:27 Sea Surface Temperature Residual SD - 1993-2013 Oceans | Ocean Temperature | Sea Surface Temperature WCS GeoTIFF residSD_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 5a82d01756830fdb8ece72ad5f98837291a0777f 2020-09-23T13:24:24 Mean Lagoon Ebb/Flood Power Density lagoon_ebbflood_pden_mean-ti0 WCS GeoTIFF Tidal Energy | Tidal Range | Tidal Range Power Density | National Lagoon_ebbflood_pden: 25h-averaged power density (W/m^2) potentially exploitable by a bi-directional tidal lagoon system. The amount of electrical power generated by the system will be some fraction of this quantity times the area of the lagoon, or empoundment region. Each time a body of water with area A rises or falls a height H an amount Ep= 1/2ρgAH^2 J of gravitational potential energy is potentially convertable to electricity. For purely semidiurnal tides the maximum theoretically extractable energy from 2 rises and 2 falls is 2ρgAH^2, while for diurnal tides it is just ρgAH^2. One way to generalise this equation for mixed tides is to measure the number of tidal cycles per day as the daily integrated fall F divided by the range H. The daily-average theoretical maximum power per unit area of impoundment is therefore ρgHF/86400 W/m^2. Lagoon_ebbflood_pden: 25h-averaged power density (W/m^2) potentially exploitable by a bi-directional tidal lagoon system. The amount of electrical power generated by the system will be some fraction of this quantity times the area of the lagoon, or empoundment region. Each time a body of water with area A rises or falls a height H an amount Ep= 1/2ρgAH^2 J of gravitational potential energy is potentially convertable to electricity. For purely semidiurnal tides the maximum theoretically extractable energy from 2 rises and 2 falls is 2ρgAH^2, while for diurnal tides it is just ρgAH^2. One way to generalise this equation for mixed tides is to measure the number of tidal cycles per day as the daily integrated fall F divided by the range H. The daily-average theoretical maximum power per unit area of impoundment is therefore ρgHF/86400 W/m^2. 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%3Alagoon_ebbflood_pden_mean-ti0 1be65d2c14182719391352c1ee25674649409145 2020-09-23T13:24:24 AMSA Oil Spill Events 1970-2015 Oceans Solid Earth | Natural Resources | Petroleum features oil_spills_sum Multiple Use | Pollution This data contains summaries at 0.1 deg of all suspected and confirmed oil pollution events reported to, or suspected by AMSA. Data on the date, geographic location, source type and ship type was provided by AMSA. This data was summarised over the entire time period (1970-2016) at 0.1 degree resolution and the count of the number of incidents produced. http://www.amsa.gov.au/environment/major-historical-incidents/index.asp This data contains summaries at 0.1 deg of all suspected and confirmed oil pollution events reported to, or suspected by AMSA. Data on the date, geographic location, source type and ship type was provided by AMSA. This data was summarised over the entire time period (1970-2016) at 0.1 degree resolution and the count of the number of incidents produced. http://www.amsa.gov.au/environment/major-historical-incidents/index.asp Australian Maritime Safety Authority (AMSA), Australian Government. copyright 168.359497070312 -54.7594985961914 95.7405014038086 -2.34049987792969 dataset http://oa-gis.csiro.au/geoserver/wms?SERVICE=WMS& http://www.marlin.csiro.au/geonetwork/srv/eng/search#!2ff40822-a773-4788-aedd-232639142cde 9490880e13cab82b80628abe1567b74f8389cf19 2020-09-23T13:24:25 0th percentile of Daily average Tidal Stream Kinetic Energy Flux raster_dkefpc-ti0 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Daily average Tidal Stream | National Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC 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%3Araster_dkefpc_ti0 http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Araster_dkefpc_ti0&style=kefc_log2 3fa92ecffef893cd9a86cdc5a30c4d038e38b686 2020-09-23T13:24:25 10th percentile of Daily average Tidal Stream Kinetic Energy Flux raster_dkefpc-ti1 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Daily average Tidal Stream | National Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC 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%3Araster_dkefpc_ti1 http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Araster_dkefpc_ti1&style=kefc_log2 97fa2e9f5edc4ed91b5d2b6ed42f47dcb1f7f796 2020-09-23T13:24:25 100th percentile of Daily average Tidal Stream Kinetic Energy Flux raster_dkefpc-ti10 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Daily average Tidal Stream | National Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC 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%3Araster_dkefpc_ti10 http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Araster_dkefpc_ti10&style=kefc_log2 d1ae76f1afef41fd9e7a36a03a97ad1627c4fe83 2020-09-23T13:24:25 20th percentile of Daily average Tidal Stream Kinetic Energy Flux raster_dkefpc-ti2 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Daily average Tidal Stream | National Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC 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%3Araster_dkefpc_ti2 http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Araster_dkefpc_ti2&style=kefc_log2 d055d1671f1d230e607f34d7b9422cf0ded5b63c 2020-09-23T13:24:25 50th percentile of Daily average Tidal Stream Kinetic Energy Flux raster_dkefpc-ti5 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Daily average Tidal Stream | National Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC 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%3Araster_dkefpc_ti5 http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Araster_dkefpc_ti5&style=kefc_log2 f34fd4325bc84446a7fed261f1dc3900a3620126 2020-09-23T13:24:25 80th percentile of Daily average Tidal Stream Kinetic Energy Flux raster_dkefpc-ti8 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Daily average Tidal Stream | National Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC 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%3Araster_dkefpc_ti8 http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Araster_dkefpc_ti8&style=kefc_log2 8777f91220862ba34a4563f1119023750d320a8c 2020-09-23T13:24:26 20th percentile of Daily Average Tidal Current Speed raster_dsppc-ti2 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Daily Average Current Speed | National Percentiles of the daily average speed v (m/s) Percentiles of the daily average speed v (m/s) 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%3Araster_dsppc_ti2 8943976e9b73f6013a803c7983ef74543ab78cd5 2020-09-23T13:24:26 50th percentile of Daily Average Tidal Current Speed raster_dsppc-ti5 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Daily Average Current Speed | National Percentiles of the daily average speed v (m/s) Percentiles of the daily average speed v (m/s) 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%3Araster_dsppc_ti5 d64e0610f52752165a8a65fd3af541003a349d81 2020-09-23T13:24:26 80th percentile of Daily Average Tidal Current Speed raster_dsppc-ti8 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Daily Average Current Speed | National Percentiles of the daily average speed v (m/s) Percentiles of the daily average speed v (m/s) 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%3Araster_dsppc_ti8 88c088be23d5368de5e484a491416702a4fad7ef 2020-09-23T13:24:26 90th percentile of Daily Average Tidal Current Speed WCS GeoTIFF raster_dsppc_ti9 Tidal Energy | Tidal Current Speed | Daily Average Current Speed | National Percentiles of the daily average speed v (m/s) Percentiles of the daily average speed v (m/s) 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%3Araster_dsppc_ti9 c3e0eaab2bba40444c2e8033144e2a400eb10799 2020-09-23T13:24:26 0th percentile of Tidal Stream Kinetic Energy Flux raster_kefpc-ti0 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | National Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 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%3Araster_kefpc_ti0 d5b98413b9a775a4a3b1c39c52b749cd2595231d 2020-09-23T13:24:26 10th percentile of Tidal Stream Kinetic Energy Flux raster_kefpc-ti1 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | National Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 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%3Araster_kefpc_ti1 f58d6e76e9a6a63b8cadc63c712ab20dd9df0a44 2020-09-23T13:24:27 100th percentile of Tidal Stream Kinetic Energy Flux raster_kefpc-ti10 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | National Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 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%3Araster_kefpc_ti10 5c3ef4c25497d0fd06eca9e6cbf1fee4b72d60d4 2020-09-23T13:24:27 20th percentile of Tidal Stream Kinetic Energy Flux raster_kefpc-ti2 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | National Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 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%3Araster_kefpc_ti2 100e19235c57cf0b323fefcd3e1b82a0ab4ce13d 2020-09-23T13:24:27 50th percentile of Tidal Stream Kinetic Energy Flux raster_kefpc-ti5 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | National Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 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%3Araster_kefpc_ti5 44d53731b036ddc57709039a1c734983a96b6556 2020-09-23T13:24:27 80th percentile of Tidal Stream Kinetic Energy Flux raster_kefpc-ti8 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | National Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 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%3Araster_kefpc_ti8 b0cd17f0176a2b12ee2deddfac5d117dc02b48fa 2020-09-23T13:24:27 90th percentile of Tidal Stream Kinetic Energy Flux raster_kefpc-ti9 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Tidal Stream Kinetic Energy Flux | National Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. Kinetic Energy Flux (W/m^2) = 1/2 ρ v^3 where ρ=1023kg/m^3 is the density of seawater and v is the depth-average current speed (m/s) output hourly from our barotropic implementation of COMPAS. This is the rate at which kinetic energy passes through a vertical plane in the undisturbed ocean. The amount of electrical power generated by a turbine will be some fraction of this quantity (about half) times the swept area of the blades. Percentiles (PC=0:10:100) of KEF. These percentiles are estimated from the full length (59 days) of our model run, and describe the range of values that occur. The minimum, median and maximum values of KEF are the 0th, 50th and 100th percentiles. These are useful statistics for structure design, but are not very informative about energy production because of the way the spring-neap cycle modulates the daily variability. 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%3Araster_kefpc_ti9 397d56dc944c946ebf31b222c74189a15e4f2d21 2020-09-23T13:24:27 0th percentile of Tidal Current Speed raster_sppc-ti0 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Percentile Tidal Current Speed | National Percentiles of the speed v (m/s) Percentiles of the speed v (m/s) 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%3Araster_sppc_ti0 1df2aa383ece2e0e22a457eb20fa236d1ac22e4d 2020-09-23T13:24:25 50th percentile of Tidal Range raster_drangepc-ti5 WCS GeoTIFF Tidal Energy | Tidal Range | Percentile Tidal Range | National Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 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%3Araster_drangepc_ti5 951d5d4a0e9eed38f3b657e1c7c6eedfbac01c8b 2020-09-23T13:24:26 80th percentile of Tidal Range raster_drangepc-ti8 WCS GeoTIFF Tidal Energy | Tidal Range | Percentile Tidal Range | National Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 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%3Araster_drangepc_ti8 6470bbc48244f37b90e340e38695921768bfe36a 2020-09-23T13:24:26 90th percentile of Tidal Range raster_drangepc-ti9 WCS GeoTIFF Tidal Energy | Tidal Range | Percentile Tidal Range | National Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 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%3Araster_drangepc_ti9 27e3d9320a58e06517155d536b25920e63946d33 2020-09-23T13:24:26 0th percentile of Daily Average Tidal Current Speed raster_dsppc-ti0 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Daily Average Current Speed | National Percentiles of the daily average speed v (m/s) Percentiles of the daily average speed v (m/s) 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%3Araster_dsppc_ti0 5a6e017a0e7c7d131651bcef0eddf4a7b018eaa8 2020-09-23T13:24:26 10th percentile of Daily Average Tidal Current Speed raster_dsppc-ti1 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Daily Average Current Speed | National Percentiles of the daily average speed v (m/s) Percentiles of the daily average speed v (m/s) 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%3Araster_dsppc_ti1 cf61cdc4327d47975807eaa2d2e5dd0d9798f934 2020-09-23T13:24:26 100th percentile of Daily Average Tidal Current Speed raster_dsppc-ti10 WCS GeoTIFF Tidal Energy | Tidal Current Speed | Daily Average Current Speed | National Percentiles of the daily average speed v (m/s) Percentiles of the daily average speed v (m/s) 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%3Araster_dsppc_ti10 65b700c24e5e8147a303afbce252ad5b3300edcc 2020-09-23T13:24:25 90th percentile of Daily average Tidal Stream Kinetic Energy Flux raster_dkefpc-ti9 WCS GeoTIFF Tidal Energy | Tidal Stream Kinetic Energy | Daily average Tidal Stream | National Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC Daily average Kinetic Energy Flux (W/m^2) = where DKEF denotes a moving 25hour-average, evaluated every 24h. See KEFPC 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%3Araster_dkefpc_ti9 http://oa-gis.csiro.au/geoserver/wms?request=GetLegendGraphic&format=image%2Fpng&width=20&height=20&layer=tidal%3Araster_dkefpc_ti9&style=kefc_log2 f06d77c1cde8b3d2e88dea2068a5f3c46dcf9eec 2020-09-23T13:24:25 0th percentile of Tidal Range raster_drangepc-ti0 WCS GeoTIFF Tidal Energy | Tidal Range | Percentile Tidal Range | National Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 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%3Araster_drangepc_ti0 47b2b4117de85d9a95bdd5de8e0d76b78694c0f1 2020-09-23T13:24:25 10th percentile of Tidal Range raster_drangepc-ti1 WCS GeoTIFF Tidal Energy | Tidal Range | Percentile Tidal Range | National Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 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%3Araster_drangepc_ti1 51c24f9a538d93a135cbba77421f0a0fcd5e9c1b 2020-09-23T13:24:25 100th percentile of Tidal Range raster_drangepc-ti10 WCS GeoTIFF Tidal Energy | Tidal Range | Percentile Tidal Range | National Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 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%3Araster_drangepc_ti10 b1b2d7385727cd65cba7005354dd5402263ef9c5 2020-09-23T13:24:25 20th percentile of Tidal Range raster_drangepc-ti2 WCS GeoTIFF Tidal Energy | Tidal Range | Percentile Tidal Range | National Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. Difference (m) between the highest and lowest value of the tidal elevation in a 25h period, evaluated daily - DRANGE, DRANGEPC - percentiles (m) of DRANGE. 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%3Araster_drangepc_ti2 f73b1d480edef982565941818ca98a4551ab6648 2020-09-23T13:24:38 (Month 09) September Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The September 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 September data from September 1980 to September 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 September 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 September data from September 1980 to September 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.09 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.09.nc 294c92674921707d210ec28c1bcb9d55a3be478c 2020-09-23T13:24:38 (Month 10) October Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The October 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 October data from October 1980 to October 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 October 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 October data from October 1980 to October 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.10 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.10.nc ecd931afc948459bd6ceede4d5e36fb2809287ed 2020-09-23T13:24:38 (Month 11) November Mean Direction of the Maximum Directionally Resolved Wave Power Wave Energy Resource | Direction of Maximum Directionally Resolved Wave Power | Monthly Means The November 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 November data from November 1980 to November 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 November 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 November data from November 1980 to November 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.11 http://oa-gis.csiro.au/data/jthm/ww3.aus_4m.jthm_avg.11.nc