Polar Environmental Data Layers

These layers are polar climatological and other summary environmental layers that may be useful for purposes such as general modelling, regionalisation, and exploratory analyses. All of the layers in this collection are provided on a consistent 0.1-degree grid, which covers -180 to 180E, 80S to 30S (Antarctic) and 45N to 90N (Arctic). As far as practicable, each layer is provided for both the Arctic and Antarctic regions. Where possible, these have been derived from the same source data; otherwise, source data have been chosen to be as compatible as possible between the two regions. Some layers are provided for only one of the two regions.Each data layer is provided in netCDF and ArcInfo ASCII grid format. A png preview map of each is also provided.Processing details for each layer:BathymetryFile: bathymetryMeasured and estimated seafloor topography from satellite altimetry and ship depth soundings.Antarctic:Source data: Smith and Sandwell V13.1 (Sep 4, 2010)Processing steps: Depth data subsampled from original 1-minute resolution to 0.05-degree resolution and interpolated to 0.1-degree grid using bilinear interpolation.Reference: Smith, W. H. F., and D. T. Sandwell (1997) Global seafloor topography from satellite altimetry and ship depth soundings. Science 277:1957-1962. http://topex.ucsd.edu/WWW_html/mar_topo.htmlArctic:Source data: ETOPO1Processing steps: Depth data subsampled to 0.05-degree resolution and interpolated to 0.1-degree grid using bilinear interpolation on polar stereographic projection.Reference: Amante, C. and B. W. Eakins, ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis. NOAA Technical Memorandum NESDIS NGDC-24, 19 pp, March 2009. http://www.ngdc.noaa.gov/mgg/global/global.html----Bathymetry slopeFile: bathymetry_slopeSlope of sea floor, derived from Smith and Sandwell V13.1 and ETOPO1 bathymetry data (above).Processing steps: Slope calculated on 0.1-degree gridded depth data (above). Calculated using the equation given by Burrough, P. A. and McDonell, R.A. (1998) Principles of Geographical Information Systems (Oxford University Press, New York), p. 190 (see http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=How%20Slope%20works)----CAISOM model-derived variablesVariables derived from the CAISOM ocean model. This model has been developed by Ben Galton-Fenzi (AAD and ACE-CRC), and is based on the Regional Ocean Modelling System (ROMS). It has circum-Antarctic coverage out to 50S, with a spatial resolution of approximately 5km. The values here are averaged over 12 snapshots from the model, each separated by 2 months. These parameters should be treated as experimental.Reference: Galton-Fenzi BK, Hunter JR, Coleman R, Marsland SJ, Warner RC (2012) Modeling the basal melting and marine ice accretion of the Amery Ice Shelf. Journal of Geophysical Research: Oceans, 117, C09031. http://dx.doi.org/10.1029/2012jc008214Floor current speedFile: caisom_floor_current_speedCurrent speed near the sea floor.Floor temperatureFile: caisom_floor_temperaturePotential temperature near the sea floor.Floor vertical velocityFile: caisom_floor_vertical_velocityVertical water velocity near the sea floor.Surface current speedFile: caisom_surface_current_speedNear-surface current speed (at approximately 2.5m depth)----Chlorophyll summerFile: chl_summer_climatologySource data: Near-surface chl-a summer climatology from MODIS AquaAntarctic:Climatology spans the 2002/03 to 2009/10 austral summer seasons. Data interpolated from original 9km resolution to 0.1-degree grid using bilinear interpolation.Arctic:Climatology spans the 2002 to 2009 boreal summer seasons. Data interpolated from original 9km resolution to 0.1-degree grid using bilinear interpolation.Reference: Feldman GC, McClain CR (2010) Ocean Color Web, MODIS Aqua Reprocessing, NASA Goddard Space Flight Center. Eds. Kuring, N., Bailey, S.W. https://oceancolor.gsfc.nasa.gov/----Distance to AntarcticaFile: distance_antarcticaDistance to nearest part of Antarctic continent (Antarctic only)Source data: A modified version of ESRI's world map shapefileProcessing steps: Distances calculated in km using the Haversine formula on a spherical earth of radius 6378.137km.----Distance to nearest seabird breeding colony (Antarctic only)File: distance_colonyAntarctic source data: Inventory of Antarctic seabird breeding sites, collated by Eric Woehler. http://data.aad.gov.au/aadc/biodiversity/display_collection.cfm?collection_id=61.Processing steps: The closest distance of each grid point to the colonies was calculated in km using the Haversine formula on a spherical earth of radius 6378.137km.----Distance to maximum winter sea ice extent File: distance_max_ice_edgeSource data: SMMR-SSM/I passive microwave estimates of daily sea ice concentration from the National Snow and Ice Data Center (NSIDC).Processing steps:Antarctic:Mean maximum winter sea ice extent was derived from daily estimates of sea ice concentration as described at https://data.aad.gov.au/metadata/records/sea_ice_extent_winter. The closest distance of each grid point to this extent line was calculated in km using the Haversine formula on a spherical earth of radius 6378.137km.Arctic:The median March winter sea ice extent was obtained from the NSIDC at http://nsidc.org/data/g02135.html. The closest distance of each grid point to this extent line was calculated in km using the Haversine formula on a spherical earth of radius 6378.137km.Reference: Cavalieri, D., C. Parkinson, P. Gloersen, and H. J. Zwally. 1996, updated 2008. Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I passive microwave data. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. tp://nsidc.org/data/nsidc-0051.html----Distance to shelf breakFile: distance_shelfDistance to nearest area of sea floor of depth 500m or less.Derived from Smith and Sandwell V13.1 and ETOPO1 bathymetry data (above).Processing steps: Distances calculated in km using the Haversine formula on a spherical earth of radius 6378.137km. Points in less than 500m of water (i.e. over the shelf) were assigned negative distances.See also distance to upper slope----Distance to subantarctic islands (Antarctic only)File: distance_subantarctic_islandsDistance to nearest land mass north of 65S (includes land masses of e.g. South America, Africa, Australia, and New Zealand).Processing steps: Distances calculated in km using the Haversine formula on a spherical earth of radius 6378.137km. ----Distance to canyonFile: distance_to_canyonDistance to the axis of the nearest canyon (Antarctic only)Source data: O'Brien and Post (2010) seafloor geomorphic feature dataset, expanded from O'Brien et al. (2009). Mapping based on GEBCO contours, ETOPO2, seismic lines.Processing steps: Distances to nearest canyon axis calculated in km using the Haversine formula on a spherical earth of radius 6378.137km.NOTE: source data extend only as far north as 45S. Do not rely on this layer near or north of 45S.Reference: O'Brien, P.E., Post, A.L., and Romeyn, R. (2009) Antarctic-wide geomorphology as an aid to habitat mapping and locating vulnerable marine ecosystems. CCAMLR VME Workshop 2009. Document WS-VME-09/10----Distance to polynyaFile: distance_to_polynyaDistance to the nearest polynya area (Antarctic only)Source data: AMSR-E satellite estimates of daily sea ice concentration at 6.25km resolutionProcessing steps: The seaice_gt_85 layer (see below) was used. Pixels which were (on average) covered by sea ice for less than 35% of the year were identified. The distance from each grid point on the 0.1-degree grid to the nearest such polynya pixel was calculated in km using the Haversine formula on a spherical earth of radius 6378.137km. (NB the threshold of 35% was chosen to give a good empirical match to the polynya locations identified by Arrigo and van Dijken (2003), although the results were not particularly sensitive to the choice of threshold.Reference: Arrigo KR, van Dijken GL (2003) Phytoplankton dynamics within 37 Antarctic coastal polynya systems. Journal of Geophysical Research, 108, 3271. http://dx.doi.org/10.1029/2002JC001739----Distance to upper slope (Antarctic only)File: distance_upper_slopeDistance to the "upper slope" geomorphic feature from the Geoscience Australia geomorphology data set. This is probably a better indication of the distance to the Antarctic continental shelf break than the "distance to shelf break" data (above).Source data: O'Brien and Post (2010) seafloor geomorphic feature dataset, expanded from O'Brien et al. (2009). Mapping based on GEBCO contours, ETOPO2, seismic lines.Processing steps: Distances calculated in km using the Haversine formula on a spherical earth of radius 6378.137km. Points inside of an "upper slope" polygon were assigned negative distances.Reference: O'Brien, P.E., Post, A.L., and Romeyn, R. (2009) Antarctic-wide geomorphology as an aid to habitat mapping and locating vulnerable marine ecosystems. CCAMLR VME Workshop 2009. Document WS-VME-09/10----Fast iceFile: fast_iceThe average proportion of the year for which landfast sea ice is present in a locationSource data: 20-day composite records of East Antarctic landfast sea-ice, derived from MODIS imagery (Fraser at al. 2012)Processing steps: The average proportion of the year for which each pixel was covered by landfast sea ice was calculated as an average across 2001--2008. Data were regridded to the 0.1-degree grid using bilinear interpolation.Distance to fast iceFile: distance_to_fast_iceDistance to the nearest location where fast ice is typically present.Source data: 20-day composite records of East Antarctic landfast sea ice, derived from MODIS imagery (Fraser at al. 2012)Processing steps: Pixels in the landfast sea ice data that were associated with fast ice presence for more than half of the year (on average) were identified. The distance from each pixel in the 0.1-degree grid to the nearest of these fast ice pixels was calculated in km using the Haversine formula on a spherical earth of radius 6378.137km.Reference: Fraser AD, Massom RA, Michael KJ, Galton-Fenzi BK and Lieser JL (2012) East Antarctic landfast sea ice distribution and variability, 2000-08. Journal of Climate 25:1137-1156.See also: http://data.aad.gov.au/aadc/metadata/metadata_redirect.cfm?md=AMD/AU/modis_20day_fast_ice----Seafloor temperatureFile: floor_temperatureSource data: Original data derived from World Ocean Atlas 2005 data and provided on a 1-degree grid.Processing steps: Isolated missing pixels (i.e. single pixels of missing data with no surrounding missing pixels) were filled using bilinear interpolation. Data provided in two versions: one regridded from 1-degree grid using nearest neighbour interpolation (floor_temperature) and the other using bilinear interpolation (floor_temperature_interpolated).Reference: Clarke, A. et al. (2009) Spatial variation in seabed temperatures in the Southern Ocean: Implications for benthic ecology and biogeography. Journal of Geophysical Research 114:G03003. doi:10.1029/2008JG000886----GeomorphologyFile: geomorphologyGeomorphic feature classificationSource data: O'Brien and Post (2010) seafloor geomorphic feature dataset, expanded from O'Brien et al. (2009). Mapping based on GEBCO contours, ETOPO2, seismic lines.Reference: O'Brien, P.E., Post, A.L., and Romeyn, R. (2009) Antarctic-wide geomorphology as an aid to habitat mapping and locating vulnerable marine ecosystems. CCAMLR VME Workshop 2009. Document WS-VME-09/10Geomorphic feature class names and their corresponding values in the gridded files:1: Abyssal_Plain2: Bank_Wave_Affected3: Coastal_Terrane4: Contourite_Feature5: Cross_Shelf_Valley6: Fracture_Zone7: Iceshelf_Cavity8: Island_Arc9: Island_Coastal_Terrane10: Lower_Slope11: Margin_Ridges12: Marginal_Plateau13: Mid_Ocean_Ridge_Valley14: Plateau15: Plateau_Slope16: Ridge17: Rough_Seafloor18: Seamount19: Seamount_Ridges20: Shelf_Bank21: Shelf_Deep22: Structural_Slope23: Trench24: Trough25: Trough_Mouth_Fan26: Upper_Slope27: Volcano----Light budgetFile: light_budgetAnnual light budget (cumulative solar radiation) reaching the water surface.Processing steps: As per Clark et al. (in press). Daily incident solar radiation was modelled assuming a cloud-free sky (Suri and Hofierka 2004). Sea ice data (AMSR-E sea ice concentration) were used as a mask: if sea ice was present on a given day then the solar radiation reaching the ocean surface was assumed to be zero. The annual light budget for a given pixel was therefore calculated as the sum of daily solar radiation values on all days when sea ice was not present. The values here are the mean annual light budget over the 2002/03 to 2010/11 austral summer seasons (1-Jul to 30-Jun). Calculations were made on the AMSR-E 6.25km polar stereographic grid, and then interpolated to the 0.1-degree rectangular grid using triangle-based linear interpolation.References: Clark GF, Stark JS, Johnston EL, Runcie JW, Goldsworthy PM, Raymond B, Riddle MJ (in press) Light-driven tipping points in polar ecosystems. Global Change Biology. http://dx.doi.org/10.1111/gcb.12337Suri M, J Hofierka (2004) A new GIS-based solar radiation model and its application to photovoltaic assessments. Transactions in GIS, 8, 175-190----Mixed layer depthFile: mixed_layer_depth_summer_climatology and mixed_layer_depth_summer_climatology_interpolatedSummer mixed layer depth climatology from ARGOS dataProcessing steps: Data provided in two versions: one regridded from 2-degree grid using nearest neighbour interpolation (mixed_layer_depth_summer_climatology) and the other using bilinear interpolation (mixed_layer_depth_summer_climatology_interpolated).Reference: de Boyer Montegut, C., G. Madec, A. S. Fischer, A. Lazar, and D. Iudicone (2004), Mixed layer depth over the global ocean: an examination of profile data and a profile-based climatology, J. Geophys. Res., 109, C12003, doi:10.1029/2004JC002378. http://www.ifremer.fr/cerweb/deboyer/mld/home.php----Sea ice coverFile: seaice_gt85Proportion of time the ocean is covered by sea ice of concentration 85% or higher.Source data: AMSR-E satellite estimates of daily sea ice concentration at 6.25km resolutionProcessing steps: Concentration data from 1-Jan-2003 to 31-Dec-2010 used. The fraction of time each pixel was covered by sea ice of at least 85% concentration was calculated for each pixel in the original (polar stereographic) grid. Data then regridded to 0.1-degree grid using triangle-based linear interpolation.Reference: Spreen, G., L. Kaleschke, and G. Heygster (2008), Sea ice remote sensing using AMSR-E 89 GHz channels, J. Geophys. Res., doi:10.1029/2005JC003384 https://seaice.uni-bremen.de/sea-ice-concentration/----Sea ice summer variabilityFile: seaice_summer_variabilityVariability of sea ice cover during summer monthsSource data: AMSR-E satellite estimates of daily sea ice concentration at 6.25km resolutionProcessing steps: Daily estimates of sea ice concentration across December, January, and February of a given austral summer season were collated. For each pixel, the standard deviation of these values was calculated. The values given here are averaged over the 2002/03 to 2009/10 austral summer seasons.Reference: Spreen, G., L. Kaleschke, and G. Heygster (2008), Sea ice remote sensing using AMSR-E 89 GHz channels, J. Geophys. Res., doi:10.1029/2005JC003384 https://seaice.uni-bremen.de/sea-ice-concentration/----Sea surface height variablesNOTE: The sea surface height-related data are derivative works of level-4 gridded altimetry data (data courtesy of Ssalto/Duacs, Aviso, and CNES; http://www.aviso.oceanobs.com/duacs/). These derivative works are available for scientific purposes ONLY.Sea surface heightFile: sshSource data: CNES-CLS09 Mean Dynamic Topography v1.1 (Rio et al., 2009)Processing steps: Regridded to 0.1-degree grid using bilinear interpolation.SSH spatial gradientFile: ssh_spatial_gradientThe spatial gradient (in mm/km) of the mean dynamic topography.Source data: CNES-CLS09 Mean Dynamic Topography v1.1 (Rio et al., 2009)Processing steps: Gradient calculated on the native 0.25-degree grid and interpolated to 0.1-degree grid using bilinear interpolation.SSH variabilityFile: ssha_variabilityThe variability of sea surface height over timeSource data: SSHA data from http://www.aviso.oceanobs.com/en/data/products/sea-surface-height-products/global/index.htmlProcessing steps: Weekly SSHA data covering the period 14-Oct-1992 to 14-Oct-2007 were used. For each pixel in the native 1/3-degree Mercator grid, the standard deviation of SSHA values over that period was calculated. Data were then interpolated to 0.1-degree grid using bilinear interpolation.Reference: Rio, M-H, P. Schaeffer, G. Moreaux, J-M Lemoine, E. Bronner (2009) : A new Mean Dynamic Topography computed over the global ocean from GRACE data, altimetry and in-situ measurements . Poster communication at OceanObs09 symposium, 21-25 September 2009, Venice----SST summerFile: sst_summer_climatologySource data: Sea surface temperature summer climatology from MODIS Aqua.Antarctic:Climatology spans the 2002/03 to 2009/10 austral summer seasons. Data interpolated from original 9km resolution to 0.1-degree grid using bilinear interpolation.Arctic:Climatology spans the 2002 to 2009 boreal summer seasons. Data interpolated from original 9km resolution to 0.1-degree grid using bilinear interpolation on polar stereographic grid.Reference: Feldman GC, McClain CR (2010) Ocean Color Web, MODIS Aqua Reprocessing, NASA Goddard Space Flight Center. Eds. Kuring, N., Bailey, S.W. https://oceancolor.gsfc.nasa.gov/----SST spatial gradientFile: sst_spatial_gradientSource data: Sea surface temperature summer climatology from MODIS Aqua.Antarctic:Climatology spans the 2002/03 to 2009/10 austral summer seasons. Spatial gradient of the SST (degrees C per km) calculated on the original 9km resolution data, following the equation given in http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=How%20Slope%20works. Gradient values were then interpolated from original 9km resolution to 0.1-degree grid using bilinear interpolation.Reference: Feldman GC, McClain CR (2010) Ocean Color Web, MODIS Aqua Reprocessing, NASA Goddard Space Flight Center. Eds. Kuring, N., Bailey, S.W. https://oceancolor.gsfc.nasa.gov/----Surface windFile: surface_wind_annualSource data: Average 10m wind (2000-2010) from Monthly NCEP/DOE Reanalysis 2Processing steps: Monthly mean 10m wind speed (from u- and v-wind components) from Jan-2000 to Dec-2010 was averaged. Data interpolated from original 2.5-degree grid to 0.1-degree grid using bilinear interpolation.Reference: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis2.html----Salinity 0m winterFile: salinity_0_winter_climatology and salinity_0_interpolated_winter_climatologySalinity winter climatology at 0m depth.Source data: World Ocean Atlas 2009 (National Oceanographic Data Center, Silver Springs, MD, U.S.A.) http://www.nodc.noaa.gov/OC5/WOA09/pr_woa09.htmlProcessing steps: Data regridded to 0.1-degree grid using nearest-neighbour interpolation (salinity_0_winter_climatology) and bilinear interpolation (salinity_0_interpolated_winter_climatology).Reference: Antonov, J. I., D. Seidov, T. P. Boyer, R. A. Locarnini, A. V. Mishonov, and H. E. Garcia, 2010. World Ocean Atlas 2009, Volume 2: Salinity. S. Levitus, Ed. NOAA Atlas NESDIS 69, U.S. Government Printing Office, Washington, D.C., 184 pp.----Salinity 0m summerSee above (WOA)----Salinity 50m winterSee above (WOA)----Salinity 50m summerSee above (WOA)----Salinity 200m winterSee above (WOA)----Salinity 200m summerSee above (WOA)----Salinity 500m winterSee above (WOA)----Salinity 500m summerSee above (WOA)----NOX and Silicate 0m winterSee above (WOA)File: nox_0_winter_climatology, nox_0_interpolated_winter_climatology; and si_0_winter_climatology, si_0_interpolated_winter_climatologyReference: Garcia, H. E., R. A. Locarnini, T. P. Boyer, and J. I. Antonov, 2010. World Ocean Atlas 2009, Volume 4: Nutrients (phosphate, nitrate, silicate). S. Levitus, Ed. NOAA Atlas NESDIS 71, U.S. Government Printing Office, Washington, D.C., 398 pp.----NOX and Silicate 0m summer See above (WOA)----NOX and Silicate 50m summerSee above (WOA)----NOX and Silicate 50m winterSee above (WOA)----NOX and Silicate 200m summerSee above (WOA)----NOX and Silicate 200m winterSee above (WOA)----Oxygen 0m winterSee above (WOA)File: oxygen_0_winter_climatology and oxygen_0_interpolated_winter_climatologyReference: Garcia, H. E., R. A. Locarnini, T. P. Boyer, and J. I. Antonov, 2010. World Ocean Atlas 2009, Volume 3: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation. S. Levitus, Ed. NOAA Atlas NESDIS 70, U.S. Government Printing Office, Washington, D.C., 344 pp.----Oxygen 0m summerSee above (WOA)----Oxygen 50m winterSee above (WOA)----Oxygen 50m summerSee above (WOA)----Oxygen 200m winterSee above (WOA)----Oxygen 200m summerSee above (WOA)----Temperature 0m winterSee above (WOA)File: t_0_winter_climatology and t_0_interpolated_winter_climatologyReference: Locarnini, R. A., A. V. Mishonov, J. I. Antonov, T. P. Boyer, and H. E. Garcia, 2010. World Ocean Atlas 2009, Volume 1: Temperature. S. Levitus, Ed. NOAA Atlas NESDIS 68, U.S. Government Printing Office, Washington, D.C., 184 pp.----Temperature 0m summerSee above (WOA)----Temperature 50m winterSee above (WOA)----Temperature 50m summerSee above (WOA)----Temperature 200m winterSee above (WOA)----Temperature 200m summerSee above (WOA)----Temperature 500m summerSee above (WOA)----Temperature 500m winterSee above (WOA)----Vertical velocityFile: vertical_velocity_250 and vertical_velocity_500Upward sea water velocity at 250m and 500m depth (Antarctic only)Source data: CSIRO Mk3.5d climate modelProcessing steps: Mean values calculated from the 20C3M model run 1, averaged over 1980--2000. Values then interpolated from original grid (approximate resolution 0.9 degrees latitude by 1.9 degrees longitude) to 0.1-degree grid using bilinear interpolation.Reference: Gordon et al. (2010) The CSIRO Mk3.5 Climate Model. CAWCR Technical Report 21. http://www.cawcr.gov.au/technical-reports/CTR_021.pdf