This data were collected as part of the Ocean Drilling Program. All data were collected on Leg 119. The cruise for Leg 119 began at Port Louis Harbor, Mauritius, and finished at the Port of Fremantle, Australia. The objective was to complete a transect, along with Leg 120, to study the Late Cretaceous to Holocene palaeoclimatic history of East Antarctic, tectonic history of the Kerguelen Plateau, and the late Mesozoic rifting history of the Indian plate from East Antarctica. Samples are sediments. Good calibration standards for sediments not available. More information can be obtained from the Ocean Drilling Program website. The data obtained from the drilling is available on the Ocean Drilling Program website (see Download Paleontology Data). From the abstract of one of the papers: During Leg 119 of the Ocean Drilling Program, between December 1987 and February 1988, six holes were drilled in the Kerguelen Plateau, southern Indian Ocean, and five in Prydz Bay at the mouth of the Amery Ice Shelf, on the East Antarctic continental shelf. The Prydz Bay holes, reported here, form a transect from the inner shelf to the continental slope, recording a prograding sequence of possible Late Palaeozoic to Eocene to Quaternary glacially dominated sediments. This extends the known onset of large-scale glaciation of Antarctica back to about 36-40 million years ago, the sedimentary record suggesting that a fully developed East Antarctic Ice Sheet reached the coast at Prydz Bay at this time, and was more extensive than the present sheet. Subsequent glacial history is complex, with the bulk of sedimentation in the outer shelf taking place close to the grounding line of an extended Amery Ice Shelf. However, breaks in the record and intervals of no recovery may hide evidence of periods of glacial retreat.

A bibliography of papers on microrganisms from polar areas. Publication dates of papers in the collection range from 1847 to 2002. The bibliography was compiled by Dr David Wynn Williams of the British Antarctic Survey (BAS). Dr Williams is now deceased.

Metadata record for data from ASAC Project 2584 See the link below for public details on this project. The Southern Ocean plays a significant role in the biogeochemical cycling of sulphur due to high spring-summer fluxes of dimethylsulfide (DMS), particularly south of 60 degrees S. Recent DMS flux perturbation simulations have recently highlighted the key role of the SO between 50-70 degrees S in the DMS-climate feedback hypothesis [Gabric et al., 2003; Gabric et al., 2004]. This project examines the interactions and feedback between marine polar plankton and global climate through the use of biogeochemical and global climate models, and explores the sensitivity of climate to the current and future biogenic production of dimethylsulphide at polar latitudes. This was a modelling project, and as such did not collect any data of its own. Taken from the abstracts of the referenced papers: The global climate is intimately connected to changes in the polar oceans. The variability of sea ice coverage affects deep-water formations and large-scale thermohaline circulation patterns. The polar radiative budget is sensitive to sea-ice loss and consequent surface albedo changes. Aerosols and polar cloud microphysics are crucial players in the radioactive energy balance of the Arctic Ocean. The main biogenic source of sulfate aerosols to the atmosphere above remote seas is dimethylsulfide (DMS). Recent research suggests the flux of DMS to the Arctic atmosphere may change markedly under global warming. This paper describes climate data and DMS production (based on the five years from 1998 to 2002) in the region of the Barents Sea (30-35 degrees E and 70-80 degrees N). A DMS model is introduced together with an updated calibration method. A genetic algorithm is used to calibrate the chlorophyll-a (CHL) measurements (based on satellite SeaWiFS data) and DMS content (determined from cruise data collected in the Arctic). Significant interannual variation of the CHL amount leads to significant interannual variability in the observed and modelled production of DMS in the study region. Strong DMS production in 1998 could have been caused by a large amount of ice algae being released in the southern region. Forcings from a general circulation model (CSIRO Mk3) were applied to the calibrated DMS model to predict the zonal mean sea-to-air flux of DMS for contemporary and enhanced greenhouse conditions at 70-80 degrees N. It was found that significantly decreasing ice coverage, increasing sea surface temperature and decreasing mixed-layer depth could lead to annual DMS flux increases of more than 100% by the time of equivalent CO2 tripling (the year 2080). This significant perturbation in the aerosol climate could have a large impact on the regional Arctic heat budget and consequences for global warming. ############### The response of oceanic phytoplankton to climate forcing in the Arctic Ocean has attracted increasing attention due to its special geographical position and potential susceptibility to global warming. Here, we examine the relationship between satellite derived (sea-viewing wide field-of-view sensor, SeaWiFS) surface chlorophyll-a (CHL) distribution and climatic conditions in the Barents Sea (30-35 degrees E, 70-80 degrees N) for the period 1998-2002. We separately examined the regions north and south of the Polar Front (~76 degrees N). Although field data are rather limited, the satellite CHL distribution was generally consistent with cruise observations. The temporal and spatial distribution of CHL was strongly influenced by the light regime, mixed layer depth, wind speed and ice cover. Maximum CHL values were found in the marginal sea-ice zone (72-73 degrees N) and not in the ice-free region further south (70-71 degrees N). This indicates that melt-water is an important contributor to higher CHL production. The vernal phytoplankton bloom generally started in late March, reaching its peak in late April. A second, smaller CHL peak occurred regularly in late summer (September). Of the 5 years, 2002 had the highest CHL production in the southern region, likely due to earlier ice melting and stronger solar irradiance in spring and summer. ############### Arctic ecosystems and global climate are closely related. This paper studies the distributions and the coupling relationship between Chlorophyll a (Chl a) and aerosol optical thickness (AOD) in Greenland Sea (10 degrees W - 10 degrees E, 70 degrees N - 85 degrees N) during 2003-2009 using satellite ocean colour data from MODIS Aqua. The regression analysis of EViews shows that Chl a and AOD are correlated with a time lag. Based on the lag of Chl a and AOD, co-integration inquiry finds that there is co-integration between them, which means that they will have a long-term equilibrium relationship. In general, Chl a starts from March, and gradually increases to a peak in July. The peak of AOD is usually in May, 11 weeks before Chl a. After shifting the time lag, the correlation between Chl a and AOD is 0.98 in the spring in 80 degrees N - 85 degrees N. Apart from the year of 2005, when Chl a and AOD had no time lag, the other years' intervals increased about 6 weeks within the 7 years. The peaks of AOD shifted one and a half months ahead, while Chl a also shifted about two months ahead. In northern part (75 degrees N - 85 degrees N), Chl a and AOD were much higher in the summer and autumn of 2009 than those in other years. The reason could be the much larger ice melting and higher AOD. The results indicate that the global warming has significant impact on the ecosystem in the Arctic Ocean.

The International Programme for Antarctic Buoys (IPAB) is run by the World Climate Research Programme (WCRP). IPAB is a self-sustaining project of the WCRP, and provides a link between institutions with Antarctic and Southern Ocean interests. IPAB was formally established, following a one year pilot phase, at a meeting in Helsinki, Finland in June 1994. IPAB aims to establish and maintain a network of drifting buoys in the Antarctic sea-ice zone, which monitor ice motion, pressure and temperature. In 1997, 16 organisations, representing 11 countries, were involved in the IPAB programme, including: Alfred Wegener Institute, Antarctic CRC, Australian Antarctic Division, British Antarctic Survey, Commonwealth Bureau of Meteorology, INPE -National Institute for Space Research, Institute for Marine Research and University of Helsinki, Hydrographic Department, Maritime Safety Agency, National Ice Center, National Institute of Polar Research, Programma Nazionale di Ricerche in Antardtide, Scott Polar Research Institute, Service Argos, South African Weather Bureau, United Kingdom Meteorological Office, and World Data Center A Glaciology. Tables of data availability, information, experiment details, literature, and data sets are available from the IPAB home page. Links are also available to databases held by other organisations, and links to Arctic and Indian Ocean buoy databases. The data are available via several provided URLs. Further information and the data can be obtained from the IPAB home page URL. The data and documentation are also available directly from the NSIDC website. Finally, an older copy of the data are also held locally on the Australian Antarctic Data Centre's servers. The documentation held at the NSIDC website provides important information on interpreting the dataset. A static copy of this document is included with the local copy of the dataset held on the Australian Antarctic Data Centre's servers. Data from January 1995 to July 1998 only has been made available on the NSIDC website (and correspondingly on the AADC's servers). The Australian subset contains data from drifting buoys that are along the ice edge or frozen into the ice. The data were observed around the Australian sector of Antarctica and recordings began in February 1985. Observations exist for around 20 buoys over this area and are not continuous over this area for this time period. Data from the period 1995-1998 only have been archived. This work was also completed as part of ASAC projects 732, 742 and 2678. The fields in this dataset are: Buoy Number Year Time Longitude Latitude ARGOS Positional Accuracy Sea Ice Flag Air Pressure Air Temperature Water Temperature Velocity

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: Bathymetry File: bathymetry Measured 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.html Arctic: Source data: ETOPO1 Processing 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 slope File: bathymetry_slope Slope 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 variables Variables 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/10.1029/2012jc008214 Floor current speed File: caisom_floor_current_speed Current speed near the sea floor. Floor temperature File: caisom_floor_temperature Potential temperature near the sea floor. Floor vertical velocity File: caisom_floor_vertical_velocity Vertical water velocity near the sea floor. Surface current speed File: caisom_surface_current_speed Near-surface current speed (at approximately 2.5m depth) ---- Chlorophyll summer File: chl_summer_climatology Source data: Near-surface chl-a 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. 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 Antarctica File: distance_antarctica Distance to nearest part of Antarctic continent (Antarctic only) Source data: A modified version of ESRI's world map shapefile Processing 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_colony Antarctic 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_edge Source 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 break File: distance_shelf Distance 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_islands Distance 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 canyon File: distance_to_canyon Distance 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 polynya File: distance_to_polynya Distance to the nearest polynya area (Antarctic only) Source data: AMSR-E satellite estimates of daily sea ice concentration at 6.25km resolution Processing 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_slope Distance 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 ice File: fast_ice The average proportion of the year for which landfast sea ice is present in a location Source 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 ice File: distance_to_fast_ice Distance 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 temperature File: floor_temperature Source 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 ---- Geomorphology File: geomorphology Geomorphic feature classification 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. 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 Geomorphic feature class names and their corresponding values in the gridded files: 1: Abyssal_Plain 2: Bank_Wave_Affected 3: Coastal_Terrane 4: Contourite_Feature 5: Cross_Shelf_Valley 6: Fracture_Zone 7: Iceshelf_Cavity 8: Island_Arc 9: Island_Coastal_Terrane 10: Lower_Slope 11: Margin_Ridges 12: Marginal_Plateau 13: Mid_Ocean_Ridge_Valley 14: Plateau 15: Plateau_Slope 16: Ridge 17: Rough_Seafloor 18: Seamount 19: Seamount_Ridges 20: Shelf_Bank 21: Shelf_Deep 22: Structural_Slope 23: Trench 24: Trough 25: Trough_Mouth_Fan 26: Upper_Slope 27: Volcano ---- Light budget File: light_budget Annual 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.12337 Suri 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 depth File: mixed_layer_depth_summer_climatology and mixed_layer_depth_summer_climatology_interpolated Summer mixed layer depth climatology from ARGOS data Processing 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 cover File: seaice_gt85 Proportion 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 resolution Processing 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 variability File: seaice_summer_variability Variability of sea ice cover during summer months Source data: AMSR-E satellite estimates of daily sea ice concentration at 6.25km resolution Processing 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 variables NOTE: 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 height File: ssh Source 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 gradient File: ssh_spatial_gradient The 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 variability File: ssha_variability The variability of sea surface height over time Source data: SSHA data from http://www.aviso.oceanobs.com/en/data/products/sea-surface-height-products/global/index.html Processing 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 summer File: sst_summer_climatology Source 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 gradient File: sst_spatial_gradient Source 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 wind File: surface_wind_annual Source data: Average 10m wind (2000-2010) from Monthly NCEP/DOE Reanalysis 2 Processing 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 winter File: salinity_0_winter_climatology and salinity_0_interpolated_winter_climatology Salinity 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.html Processing 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 summer See above (WOA) ---- Salinity 50m winter See above (WOA) ---- Salinity 50m summer See above (WOA) ---- Salinity 200m winter See above (WOA) ---- Salinity 200m summer See above (WOA) ---- Salinity 500m winter See above (WOA) ---- Salinity 500m summer See above (WOA) ---- NOX and Silicate 0m winter See above (WOA) File: nox_0_winter_climatology, nox_0_interpolated_winter_climatology; and si_0_winter_climatology, si_0_interpolated_winter_climatology Reference: 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 summer See above (WOA) ---- NOX and Silicate 50m winter See above (WOA) ---- NOX and Silicate 200m summer See above (WOA) ---- NOX and Silicate 200m winter See above (WOA) ---- Oxygen 0m winter See above (WOA) File: oxygen_0_winter_climatology and oxygen_0_interpolated_winter_climatology Reference: 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 summer See above (WOA) ---- Oxygen 50m winter See above (WOA) ---- Oxygen 50m summer See above (WOA) ---- Oxygen 200m winter See above (WOA) ---- Oxygen 200m summer See above (WOA) ---- Temperature 0m winter See above (WOA) File: t_0_winter_climatology and t_0_interpolated_winter_climatology Reference: 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 summer See above (WOA) ---- Temperature 50m winter See above (WOA) ---- Temperature 50m summer See above (WOA) ---- Temperature 200m winter See above (WOA) ---- Temperature 200m summer See above (WOA) ---- Temperature 500m summer See above (WOA) ---- Temperature 500m winter See above (WOA) ---- Vertical velocity File: vertical_velocity_250 and vertical_velocity_500 Upward sea water velocity at 250m and 500m depth (Antarctic only) Source data: CSIRO Mk3.5d climate model Processing 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

Ice Station POLarstern [ISPOL] was a multi-national, interdisciplinary study coordinated by the Alfred Wegener Institute for Polar and Marine Research, Germany, involving scientists from different institutes and nations across a range of scientific disciplines. ISPOL had been planned as a 50-day drift station in the Western Weddell Sea. Due to particularly heavy sea-ice conditions, the start of the drifting ice station was delayed, so that the drift interval, originating at -68 degrees 10'N, -54 degrees 46'W, lasted only a total of 35 days (28.11.2004 - 01.01.2005). Data and auxiliary information presented here are on the sea-ice drift and deformation experiment, which was a collaborative research program involving the International Arctic Research Center [IARC] at the University of Alaska Fairbanks, the Australian Antarctic Division [AAD], the Finnish Institute of Marine Research [FIMR] and the Alfred Wegener Institute [AWI]. Buoy contributions came from all four institutions listed above. - This metadata record covers only AAD buoy data from the ISPOL 2004 experiment. To estimate the characteristics of the sea-ice drift and dynamics in the Western Weddell Sea a meso-scale array of 26 drifting ice buoys was deployed for about 30 days during late November and December 2004. Sea-ice drift was obtained from the horizontal GPS-derived location measurements, which were made at all buoys but collected at various temporal resolutions and different spatial accuracies. Auxiliary instruments were attached to some of the sea-ice drifters, including temperature probes for air and sea-ice temperatures, and air pressure sensors. Four of the buoys were left in the ice pack after the end of the ISPOL field phase to record the large-scale drift in the region around the ice station from late summer into winter. See the metadata record 'Ice Station Polarstern. Aerial photographs over sea ice taken during the ISLOP project' for more information on the ISPOL project. Also, see the URL given below for the ISPOL home page.

These data are in the ASPeCt format. National program: Russia Vessel: Akademic Fedorov Dates in ice: 06 Jan 1993 - 03 Feb 1993 Observers: Unknown Translation to ASPeCt data format: Vladimir Smirnov Summary of voyage track: 6/1 Ice edge at approx. 63S, 80E 6-8/1 From ice edge to Mirny (93E) 12-18/1 From Mirny to Dumont d'Urville (140E) 18-20/1 From DD to Leningradskaya (159E) 21-23/1 From Leningradskaya to McMurdo (168E) 29/1-1/2 From McMurdo to Russkaya (136W) 1-3/2 From Russkaya to Bellingshausen (59W) No observations after Bellingshausen The fields in this dataset are: SEA ICE CONCENTRATION SEA ICE FLOE SIZE SEA ICE SNOW COVER SEA ICE THICKNESS SEA ICE TOPOGRAPHY SEA ICE TYPE RECORD DATE TIME LATITUDE LONGITUDE OPEN WATER TRACK SNOW THICKNESS SNOW TYPE SEA TEMPERATURE AIR TEMPERATURE WIND VELOCITY WIND DIRECTION FILM COUNTER FRAME COUNTER FOR FILM VIDEO RECORDER COUNTER VISIBILITY CODE CLOUD WEATHER CODE COMMENTS

These data describe pack ice characteristics in the Antarctic sea ice zone. These data are in the ASPeCt format. National program: Russia Vessel: Akademic Fedorov Dates in ice: 21 Feb 1988 - 01 Mar 1988 Observers: Unknown Translation to ASPeCt data format: Vladimir Smirnov Summary of voyage track: 21/2 Ice edge at approx. 75S, 163W heading east from Leningradskaya 21-23/2 Track along fast ice edge to Russkaya (136W) 27/2-1/3 Russkaya to ice edge at approx. 72S, 124W The fields in this dataset are: SEA ICE CONCENTRATION SEA ICE FLOE SIZE SEA ICE SNOW COVER SEA ICE THICKNESS SEA ICE TOPOGRAPHY SEA ICE TYPE RECORD DATE TIME LATITUDE LONGITUDE OPEN WATER TRACK SNOW THICKNESS SNOW TYPE SEA TEMPERATURE AIR TEMPERATURE WIND VELOCITY WIND DIRECTION FILM COUNTER FRAME COUNTER FOR FILM VIDEO RECORDER COUNTER VISIBILITY CODE CLOUD WEATHER CODE COMMENTS

These data describe pack ice characteristics in the Antarctic sea ice zone. These data are in the ASPeCt format. National program: Russia Vessel: Akademic Fedorov Dates in ice: 30 Mar 1994 - 21 Apr 1994 Observers: Unknown Translation to ASPeCt data format: Vladimir Smirnov Summary of voyage track: 30/3 Ice edge at approx. 65S, 81E 30/3-3/4 Ice edge to Oasiz (100E) 3-9/4 Oazis to Druzhnaya (74E) 9-11/4 Druzhnaya to Progress (76E) 12-16/4 Progress to Mirny (93E) 19-21/4 Mirny to ice edge at approx. 64S, 86E The fields in this dataset are: SEA ICE CONCENTRATION SEA ICE FLOE SIZE SEA ICE SNOW COVER SEA ICE THICKNESS SEA ICE TOPOGRAPHY SEA ICE TYPE RECORD DATE TIME LATITUDE LONGITUDE OPEN WATER TRACK SNOW THICKNESS SNOW TYPE SEA TEMPERATURE AIR TEMPERATURE WIND VELOCITY WIND DIRECTION FILM COUNTER FRAME COUNTER FOR FILM VIDEO RECORDER COUNTER VISIBILITY CODE CLOUD WEATHER CODE COMMENTS

These data describe pack ice characteristics in the Antarctic sea ice zone. These data are in the ASPeCt format. National program: Russia Vessel: Mikhail Somov Dates in ice: 09 Mar 1994 - 09 May 1994 Observers: Unknown Translation to ASPeCt data format: Vladimir Smirnov Summary of voyage track: 9/3 Ice edge at approx. 67S, 13E 9-15/3 Ice edge to Novolazarevskaya (12E) 20-24/3 Novolazarevskaya to Molodezhnaya (46E) 2-9/4 Molodezhnaya to Druzhnaya (74E) 11-12/4 Druzhnaya to Progress (76E) 12-17/4 Progress to Molodezhnaya 25-30/4 Molodezhnaya to Novolazarevskaya 1-9/5 Novolazarevskaya to Bellingshausen St (59W) The fields for this dataset are: SEA ICE CONCENTRATION SEA ICE FLOE SIZE SEA ICE SNOW COVER SEA ICE THICKNESS SEA ICE TOPOGRAPHY SEA ICE TYPE RECORD DATE TIME LATITUDE LONGITUDE OPEN WATER TRACK SNOW THICKNESS SNOW TYPE SEA TEMPERATURE AIR TEMPERATURE WIND VELOCITY WIND DIRECTION FILM COUNTER FRAME COUNTER FOR FILM VIDEO RECORDER COUNTER VISIBILITY CODE CLOUD WEATHER CODE COMMENTS