Data Catalog

Quantarctica includes a complete, user-configurable basemap for Antarctica and the subantarctic from the south pole to 40°S, as well as high-quality, peer-reviewed, free and open Antarctic scientific data in ten different themes chosen by our Editorial Board. Take a look at what Quantarctica offers:

 

The Quantarctica basemap is the foundation for any new map project. Whether you're planning a traverse or starting the all-important Figure 1 for your next paper, the Basemap looks great and runs smoothly thanks to the team of cartographers at the Norwegian Polar Institute.

Antarctic Digital Database (ADD) SCAR, 2017

SCAR

Coastlines, streams, lakes, elevation contours, moraines, rock outcrops, sea masks provided by the ADD at high, medium, and low scales. See individual layer metadata or visit the ADD website for more information.

SCAR. Antarctic Digital Database. British Antarctic Survey, Cambridge, 2017.

COMNAP listed facilities COMNAP, 2017

COMNAP

The Council of Managers of National Antarctic Programs (COMNAP) maintains a curated list of Antarctic facilities (stations, camps, etc.). The COMNAP Antarctic Facilities is a comprehensive list of the 115 Antarctic facilities with a status of 'Open' or 'Temporarily Closed'. See 'Information' tab of Excel spreadsheet (`.xls`) in the `dist` directory of the GitHub page for a reference of fields / attributes included in the dataset. The information included in the datasets was provided by each National Antarctic Program to COMNAP and is updated frequently. COMNAP will release scheduled updates of this dataset. If you would like to be notified of changes, you can watch the GitHub repository.

Reference for the use of the material is 'COMNAP 2017.'

SCAR Composite Gazetteer of Antarctica (CGA) SCAR, 1992/2017

SCAR

The Scientific Committee on Antarctic Research (SCAR) initiates, promotes and co-ordinates a wide range of scientific research programmes in Antarctica, many of which involve significant international collaboration. The SCAR Standing Committee on Antarctic Geographic Information (SC-AGI) co-ordinates the provision of a geographic reference for scientific activities in Antarctica and the dissemination of Antarctic geographic information. The SCAR Composite Gazetteer of Antarctica is an activity conducted in this framework. In 1992 the SCAR Working Group on Geodesy and Geographic Information (WG-GGI), during the XXII SCAR meeting in Bariloche, recognized the need for a composite gazetteer of Antarctica to bring some order to the complex toponymy of Antarctica. The goal of the work programme which evolved from that discussion was to provide the scientific community with two products: 1. compilation of all existing geographic names of Antarctica and 2. a set of guidelines to be followed when proposing new names and when selecting one name from a list of synonyms for a given feature. Because Antarctica does not fall under the sovereignty of any one nation this particular continent is similar, in many respects, to the oceans. In general every country has a recognized body which approves the names of geographic features in the country and also has the power to enforce their use. For Antarctica, however, there is no such single naming authority. Individual countries are responsible for their national policy on, and authorisation and use of, Antarctic names.

SCAR Secretariat (1992, updated 2014 and 2017). Composite Gazetteer of Antarctica, Scientific Committee on Antarctic Research.

IHO-IOC GEBCO Undersea feature names GEBCO, 2017

GEBCO

Point, line, and polygon undersea features for the southern ocean to 40°S. Features are frequently corrected and updated by GEBCO.

Please include the following citation when data from the gazetteer are used or reproduced in reports, presentations and other products: IHO-IOC GEBCO Gazetteer of Undersea Feature Names, www.gebco.net

Additional/Miscellaneous layers NPI, 2018

NPI/Quantarctica

The Quantarctica Project Team has developed and included numerous additional basemap layers, including: Overview place names, Subantarctic stations, Map frame, UTM zones, South Pole, Antarctic Circle, Latitude and Longitude lines, and DEM mosaics (see Terrain Rasters).

http://quantarctica.npolar.no/

Quantarctica is a unique visualization and analysis environment for atmospheric data, allowing users to show observation and model data with fully customizable color ramps, vector arrows, and more features provided by QGIS. The QGIS Plugin Repository contains user-created tools for managing NetCDF files, contouring point data, and even creating animations from time-stamped layers.

Wind scour zones Nature Geoscience, 2013

Das et al.

Identification of wind-scour zones based on a combination of airborne radar observations, lidar-derived surface roughness and an empirical model.

Das, I., R. E. Bell, T. A. Scambos, M. Wolovick, T. T. Creyts, M. Studinger, N. Frearson, J. P. Nicolas, J. T. M. Lenaerts and M . R. van den Broeke, 2013: Influence of persistent wind scour on the surface mass balance of Antarctica, Nature Geoscience 6, 367-371, doi:10.1038/ngeo1766.

RACMO Average 2m temperature (35km) The Cryosphere, 2014

Van Wessem et al.

RACMO2.3p1 modelled 2 m (near-surface) temperature. Original resolution: ~27 km. Lateral forcing: ERA-Interim. Averaging period: 1979-2011. Unit: C.

Van Wessem, J. M., C. H. Reijmer, J. T. M. Lenaerts, W. J. van de Berg, M. R. van den Broeke and E. van Meijgaard, 2014: Updated cloud physics in a regional atmospheric climate model improves the modelled surface energy balance of Antarctica, The Cryosphere 8, 125-135, doi:10.5194/tc-8-125-2014.

RACMO Total sublimation (35km) Journal of Glaciology, 2014

Van Wessem et al.

RACMO2.3p1 modelled total (surface and drifting snow) sublimation. Original resolution: ~27 km. Lateral forcing: ERA-Interim. Averaging period: 1979-2011. Unit: kg m-2 yr-1.

Van Wessem, J. M., C. H. Reijmer, M. Morlighem, J. Mouginot, E. Rignot, B. Medley, I. Joughin, B. Wouters, M. A. DePoorter, J. L. Bamber, J. T. M. Lenaerts, W. J. van de Berg, M. R. van den Broeke and E. van Meijgaard, 2014: Improved representation of East Antarctic surface mass balance in a regional atmospheric climate model, Journal of Glaciology 60, 761-770, doi:10.3189/JoG14J051

RACMO Surface mass balance (35km) Journal of Glaciology, 2014

Van Wessem et al.

RACMO2.3p1 modelled surface mass balance. Original resolution: ~27 km. Lateral forcing: ERA-Interim. Averaging period: 1979-2011. Unit: kg m-2 yr-1.

Van Wessem, J. M., C. H. Reijmer, M. Morlighem, J. Mouginot, E. Rignot, B. Medley, I. Joughin, B. Wouters, M. A. DePoorter, J. L. Bamber, J. T. M. Lenaerts, W. J. van de Berg, M. R. van den Broeke and E. van Meijgaard, 2014: Improved representation of East Antarctic surface mass balance in a regional atmospheric climate model, Journal of Glaciology 60, 761-770, doi:10.3189/JoG14J051

RACMO Total precipitation rate (35km) Journal of Glaciology, 2014

Van Wessem et al.

RACMO2.3p1 modelled total (rain and snow) annual precipitation. Original resolution: ~27 km. Lateral forcing: ERA-Interim. Averaging period: 1979-2011. Unit: kg m-2 yr-1.

Van Wessem, J. M., C. H. Reijmer, M. Morlighem, J. Mouginot, E. Rignot, B. Medley, I. Joughin, B. Wouters, M. A. DePoorter, J. L. Bamber, J. T. M. Lenaerts, W. J. van de Berg, M. R. van den Broeke and E. van Meijgaard, 2014: Improved representation of East Antarctic surface mass balance in a regional atmospheric climate model, Journal of Glaciology 60, 761-770, doi:10.3189/JoG14J051

RACMO Average absolute 10m wind speed (35km) The Cryosphere, 2014

Van Wessem et al.

RACMO2.3p1 modelled absolute 10 m (near-surface) wind speed. Original resolution: ~27 km. Lateral forcing: ERA-Interim. Averaging period: 1979-2011. Unit: m s-1.

Van Wessem, J. M., C. H. Reijmer, J. T. M. Lenaerts, W. J. van de Berg, M. R. van den Broeke and E. van Meijgaard, 2014: Updated cloud physics in a regional atmospheric climate model improves the modelled surface energy balance of Antarctica, The Cryosphere 8, 125-135, doi:10.5194/tc-8-125-2014.

Quantarctica contains satellite and ship-board measurements of biology throughout Antarctica's coast and the entire Southern Ocean. Antarctic biologists can quickly and easily import their own field measurements and sample locations and examine their relation to sea ice, ocean nutrients, and more.

MEOP CTD-equipped seal tracks GRL, 2013

Roquet et al.

Traces of available temperature/salinity data collected by sensors attached to marine mammals. Almost all in situ oceanic data in the Southern Ocean were collected in austral summer. Few exceptions are these data collected by marine mammals carrying CTD (conductivity-temperature-depth profiler). We only show the geographic location of data. Data can be downloaded from the MEOP website.

Roquet F., Wunsch C., Forget G., Heimbach P., Guinet C., Reverdin G., Charrassin J.-B., Bailleul F., Costa D. P., Huckstadt L. A., Goetz K. T., Kovacs K. M., Lydersen C., Biuw M., Nøst O. A., Bornemann H., Ploetz, J., Bester M. N., Mcintyre T., Muelbert M. C., Hindell M. A., McMahon C. R., Williams G., Harcourt R., Field I. C., Chafik L., Nicholls K. W., Boehme L., and Fedak M. A., 2013. Estimates of the Southern Ocean General Circulation Improved by Animal-Borne Instruments. Geoph. Res. Letts., 40:1-5. doi: 10.1002/2013GL058304.

Emperor penguin colonies PLoS ONE, 2012

Fretwell et al.

Emperor Penguin colonies and population estimates using very high resolution satellite imagery acquired in the 2009 breeding season.

Fretwell PT, LaRue MA, Morin P, Kooyman GL, Wienecke B, Ratcliffe N, et al. (2012) An Emperor Penguin Population Estimate: The First Global, Synoptic Survey of a Species from Space. PLoS ONE 7(4): e33751. https://doi.org/10.1371/journal.pone.0033751

KRILLBASE Earth Syst. Sci. Data, 2017

Atkinson et al.

KRILLBASE is a data rescue and compilation project to improve the availability of information on two key Southern Ocean zooplankton: Antarctic krill and salps. We provide a circumpolar database that combines 15?194 scientific net hauls (1926 to 2016) from 10 countries. These data provide a resource for analysing the distribution and abundance of krill and salps throughout the Southern Ocean to support ecological and biogeochemical research as well as fisheries management and conservation.

Atkinson, A., Hill, S. L., Pakhomov, E. A., Siegel, V., Anadon, R., Chiba, S., Daly, K. L., Downie, R., Fielding, S., Fretwell, P., Gerrish, L., Hosie, G. W., Jessopp, M. J., Kawaguchi, S., Krafft, B. A., Loeb, V., Nishikawa, J., Peat, H. J., Reiss, C. S., Ross, R. M., Quetin, L. B., Schmidt, K., Steinberg, D. K., Subramaniam, R. C., Tarling, G. A., and Ward, P.: KRILLBASE: a circumpolar database of Antarctic krill and salp numerical densities, 1926–2016, Earth Syst. Sci. Data, 9, 193-210, https://doi.org/10.5194/essd-9-193-2017, 2017.

Important Bird Areas (IBAs) BirdLife International, 2016

Harris et al.

There is a large amount of information on birds in Antarctica but this has never previously been assembled and analysed to determine exactly where the most significant breeding sites for the avifauna as a whole are. Such information is essential in order to inform the conservation actions needed to protect them against the range of threats identified in Antarctica. These include direct disturbance by visitors, disturbance by aircraft or vehicles, exposure to pollutants, ingestion of or fouling by marine debris, competition for prey from fisheries, accidental by-catch on fishing lines or in nets, introduction of disease from other parts of the world and climate change. Recent analyses have identified 204 Important Bird Areas (IBAs) in Antarctica, for all of which detailed site accounts have been compiled. Sites were identified using internationally agreed criteria that have been applied in 200 countries over the past 35 years. The compiled list of IBAs provides a baseline against which change can be measured and conservation actions considered.

Colin Harris, Lincoln Fishpool, Ben Lascelles, Katherina Lorenz, 2016. Important Bird Areas in Antarctica. Antarctic Environments Portal. https://www.environments.aq/information-summaries/important-bird-areas-in-antarctica/

chl-a summer climatology (Johnson, 9km) AAD, 2017

Raymond, B.

This dataset is a climatological summer chlorophyll-a layer for the Southern Ocean south of 40S, following the OC3M algorithm of Johnson et al. (2013). The climatology was calculated from level-3 binned MODISA RRS products spanning the 2002/03 to 2015/16 austral summer seasons (summer taken as day 355 to day 80).

Johnson, R., Sumner, M., Raymond, B. (2017, updated 2017) Southern Ocean summer chlorophyll-a climatology Australian Antarctic Data Centre - doi:10.4225/15/5906b48f70bf9. Feldman GC, McClain CR (2010) Ocean Color Web, MODIS Aqua Reprocessing, NASA Goddard Space Flight Center. Eds. Kuring, N., Bailey, S.W. http://oceancolor.gsfc.nasa.gov/ http://onlinelibrary.wiley.com/doi/10.1002/jgrc.20270/abstract https://data.aad.gov.au/metadata/records/AAS_4343_so_chlorophyll

chl-a summer climatology (NASA, 9km) AAD, 2017

Raymond, B.

This dataset is a climatological summer chlorophyll-a layer for the Southern Ocean south of 40S, following the standard NASA OC3M algorithm. The climatology was calculated from level-3 binned MODISA RRS products spanning the 2002/03 to 2015/16 austral summer seasons (summer taken as day 355 to day 80). The climatology calculated is also included.

Feldman GC, McClain CR (2010) Ocean Color Web, MODIS Aqua Reprocessing, NASA Goddard Space Flight Center. Eds. Kuring, N., Bailey, S.W. http://oceancolor.gsfc.nasa.gov/ http://onlinelibrary.wiley.com/doi/10.1002/jgrc.20270/abstract . Raymond, B. (2012, updated 2014) Polar Environmental Data Layers Australian Antarctic Data Centre - CAASM Metadata (https://data.aad.gov.au/metadata/records/Polar_Environmental_Data)

Pelagic regionalisation AAD, 2014

Raymond, B.

This layer is a circumpolar, pelagic regionalisation of the Southern Ocean south of 40°S, based on sea surface temperature, depth, and sea ice information. The results show a series of latitudinal bands in open ocean areas, consistent with the oceanic fronts. Around islands and continents, the spatial scale of the patterns is finer, and is driven by variations in depth and sea ice.

Raymond B (2014) Pelagic Regionalisation. In: de Broyer C, Koubbi P, Griffiths H, Raymond B et al. (eds) The Biogeographic Atlas of the Southern Ocean. Scientific Committee on Antarctic Research, Cambridge UK, pp. 418-421

Benthic regionalisation PLoS ONE, ADD, 2017

Douglass et al.

This layer is a circumpolar, hierarchical classification of benthic ecoregions, bathomes and environmental types. Ecoregions are defined according to available data on biogeographic patterns and environmental drivers on dispersal. Bathomes are identified according to depth strata defined by species distributions. Environmental types are uniquely classified according to the geomorphic features found within the bathomes in each ecoregion.

Douglass LL, Turner J, Grantham HS, Kaiser S, Constable A, Nicoll R, Raymond B, Post A, Brandt A, Beaver D (2014) A hierarchical classification of benthic biodiversity and assessment of protected areas in the Southern Ocean. PLoS ONE. doi:10.1371/journal.pone.0100551

Quantarctica includes the latest versions of the CCAMLR and ASPA/ASMA databases, letting Antarctic managers get a birds-eye view and helping on-the-ground researchers apply for permits and ensure their field work complies with regulations.

Antarctic Specially Protected Areas (ASPAs) AAD, 2016

Terauds, A.

An Antarctic Specially Protected Area (ASPA) is an area of Antarctica designated by the Committee for Environmental Protection adopted at the Antarctic Treaty Consultative Meeting, which protects outstanding environmental, scientific, historic, aesthetic or wilderness values, and any combination of those values, or ongoing or planned scientific research. Two shapefiles are contained in this update on the location and extent of Antarctic Specially Protected Areas (ASPAs). The first is a point file (centroids of ASPA locations) and the second is a polygon file showing the spatial extent and boundary of each ASPA. This update builds on the point and polygon files originally provided by Environmental Research and Assessment (2011). The update includes the removal of ASPAs that have been de-designated and new ASPAs that have been designated since 2011. New ASPA boundaries were created from coordinates provided in the management plans.

Terauds, A. (2016, updated 2016) An update to the Antarctic Specially Protected Areas (ASPAs), March 2016, Australian Antarctic Data Centre. http://dx.doi.org/10.4225/15/572995579cd36

Antarctic Specially Managed Areas (ASMAs) ATS, 2016

ATS/ERA

An Antarctic Specially Managed Area (ASMA) is an area of Antarctica designated by the Committee for Environmental Protection adopted at the Antarctic Treaty Consultative Meeting. An ASMA is an area where activities are being conducted or may be conducted in the future, to assist in the planning and co-ordination of activities, avoid possible conflicts, improve co-operation between Parties or minimize environmental impacts.

See 'ERA APAD License Terms and Conditions.pdf' in the data folder for additional terms and conditions.

Antarctic Conservation Biogeographic Regions (ACBRs) AAD, 2016

Terauds, A. and Lee, J.R.

The Antarctic Conservation Biogeographic Regions (ACBRs), originally proposed in 2012, are now established as an important tool in Antarctic science, conservation, management and policy. Here, we provide a revised version of the ACBRs, reflecting updates in underlying spatial layers, together with the results of new analyses justifying the inclusion of a 16th bioregion. This updated version now covers all ice-free areas of Antarctica and is publicly available through the Australian Antarctic Data Centre. In light of the interest in the ACBRs across a variety of research fields, we also provide a new set of summary statistics for the updated spatial layer, including landscape metrics, climate data, protected area coverage and an overview of human activity. The updated ACBRs represent a contemporary, practical and evidence-based foundation for understanding, conserving and managing Antarctic biodiversity at a continental scale.

Terauds, A. and Lee, J. R. (2016), Antarctic biogeography revisited: updating the Antarctic Conservation Biogeographic Regions. Diversity Distrib., 22: 836–840. doi:10.1111/ddi.12453

CCAMLR CCAMLR, 2017

 

Included layers: Research Blocks, Marine Protected Areas (MPAs), SSMUs, SSRUs, and Statistical Areas. CCAMLR layers are used globally for the purpose of reporting fishery statistics. CCAMLR's Convention Area in the Southern Ocean is divided, for statistical purposes, into Area 48 (Atlantic Antarctic) between 70oW and 30oE, Area 58 (Indian Ocean Antarctic) between 30o and 150oE, and Area 88 (Pacific Antarctic) between 150oE and 70oW. These areas, which are further subdivided into subareas and divisions, are managed by CCAMLR. A global register of statistical areas, subareas and divisions is maintained by FAO http://www.fao.org/fishery/area/search/en.

CCAMLR Secretariat (2013)

Quantarctica provides a diverse package of datasets for exploring Antarctica's geology, from large scale maps of terrestrial and marine geology to individual rock sample locations.

ADD Rock outcrop (Landsat8) The Cryosphere, 2016

Burton-Johnson et al.

An automated methodology for differentiating rock from snow, clouds and sea in Antarctica from "Landsat 8 imagery: a new rock outcrop map and area estimation for the entire Antarctic continent"

Burton-Johnson, A., Black, M., Fretwell, P. T., and Kaluza-Gilbert, J.: An automated methodology for differentiating rock from snow, clouds and sea in Antarctica from Landsat 8 imagery: a new rock outcrop map and area estimation for the entire Antarctic continent, The Cryosphere, 10, 1665-1677, https://doi.org/10.5194/tc-10-1665-2016, 2016.

OSU BPCRC Polar Rock Repository BPCRC, 2017

Grunow, A.

Geographic footprint of all available samples at the Polar Rock Repository. The PRR houses rock samples from Antarctica, the Arctic, southern South America and South Africa. The polar rock collection and database includes field notes, photos, maps, cores, powder and mineral residues, thin sections, as well as microfossil mounts, microslides and residues. Rock samples may be borrowed for research by university scientists from anywhere in the world. Samples may also be borrowed for educational or museum use in the United States. Visitors are welcome at the PRR by appointment.

Curator: Anne Grunow,

IBCSO Multibeam footprint (2016) IBCSO, 2016

ATS/ERA

The IBCSO group also tries to improve multibeam data acquisition in the future by providing information about the current multibeam coverage in the Southern Ocean. The IBCSO SID can be used to determine where multibeam data has already been surveyed. For an easier access to this information we also provide a GIS ready shapefile showing the outline of multibeam surveys as of IBCSO V1.0

Arndt, J.E., H. W. Schenke, M. Jakobsson, F. Nitsche, G. Buys, B. Goleby, M. Rebesco, F. Bohoyo, J.K. Hong, J. Black, R. Greku, G. Udintsev, F. Barrios, W. Reynoso-Peralta, T. Morishita, R. Wigley, "The International Bathymetric Chart of the Southern Ocean (IBCSO) Version 1.0 - A new bathymetric compilation covering circum-Antarctic waters", 2013, Geophysical Research Letters, Vol. 40, p. 3111-3117, doi: 10.1002/grl.50413

GEOMAP Source maps (2016) SCAR, 2016

Cox, S.

There are numerous, hard-copy, regional-scale geological maps that were developed last century. Many have been scanned, some have been georeferenced, but few are more than raster digital information. For the most part, they are geologically reliable for defining bedrock geology (‘deep time’). Unfortunately they contain little representation of glacial geology, the maps have poor spatial reliability in the context of modern science (located by GPS), and the maps have not kept pace with the present focus on Antarctica’s role in climate change. The Geological Mapping Update Action Group will facilitate an integrated programme from 2015-2018 to promote the capture of existing geological map data, update its spatial reliability, improve representation of glacial sequences and geomorphology, and enable data delivery via web-feature services. International representation is still being sought and interested parties should contact the group co-chairs.

Footprint provided by the data author. Citations for individual maps provided in the data table. See https://www.scar.org/science/geomap/about/

USGS Earthquakes (M>2.5, 1900-2017) USGS, 2017

United States Geological Survey

All earthquakes >M2.5 extracted from the USGS Earthquake Catalog south of 40S

USGS (2017). See https://earthquake.usgs.gov/earthquakes/search/ and https://earthquake.usgs.gov/earthquakes/feed/v1.0/csv.php for more information.

Tectonic plates and plate boundaries GGG/Github, 2017

Bird, P.

Global tectonic plates compiled from numerous sources

Originally published as Bird, P. (2003), An updated digital model of plate boundaries, Geochem. Geophys. Geosyst., 4, 1027, doi:10.1029/2001GC000252, 3. http://onlinelibrary.wiley.com/doi/10.1029/2001GC000252/abstract . Download updated files at https://github.com/fraxen/tectonicplates

Schematic Geological Map of Antarctica BMR, 1991

Australia Bureau of Mineral Resources

Compiled 1985-86 by R. J. Tingey, BMR Cartography by R. Swoboda. J. Gallagher, BMR Printed by Mercury-Walch, Hobart, Australia. Base map compiled by the Bureau of Mineral Resources from 1:10 000 000 scale publication supplied by the Australian Surveying and Land Information Group, Department of Administrative Services and amendments received from the British Antarctic Survey. Published by the Bureau of Mineral Resources, A Geology and Geophysics, Department of Primary Industries and Energy. Issued under the authority of the Minister for Primary Industries and Energy. © Commonwealth of Australia 1991

1:10 million scale Continent-wide surface schematic geological units and ages, compiled in 1985-1986. Australian Bureau of Mineral Resources. Schematic Geological Map of Antarctica. First Edition. 1:10 000 000. Hobart, Australia: Mercury-Walch, 1991.

Geomorphic Features AAD, 2017

Post et al.

Geomorphic features delineate distinct sedimentary and oceanographic environments that can be related to major habitat characteristics. Such characteristics include sea floor type (hard versus soft substrate), ice keel scouring, sediment deposition or erosion and current regimes.

Post AL, Meijers AJS, Fraser AD, Meiners KM, Ayers J, Bindoff NL, Griffiths HJ, Van de Putte AP, O'Brien PE, Swadling KM, Raymond B (2014) Environmental Setting. In: de Broyer C, Koubbi P, Griffiths H, Raymond B et al. (eds) The Biogeographic Atlas of the Southern Ocean. Scientific Committee on Antarctic Research, Cambridge UK, pp. 46-64. https://demo.ands.org.au/geomorphic-features-antarctic-ocean-2012/1161923

If you want to know what’s happening under the ice, Quantarctica is a great way to start building your geophysical toolbox. Quantarctica v3 includes a new geothermal heat flux layer, updates to ADMAP, and further expansion of the available satellite and aerial geophysics data.

AntGG Gravity Anomaly grid (10km) GRL, 2016

Scheinert et al.

Antarctic-wide gravity data compilation derived from 13 million data points covering an area of 10 million km^2, which corresponds to 73% coverage of the continent. Resulting free-air anomaly and Bouguer anomaly grids are given at 10 km resolution. Compilation originates from collaboration within International Association of Geodesy (IAG) Subcommission 2.3f “Gravity and Geoid in Antarctica” (AntGG).

Scheinert, M., et al. (2016), New Antarctic gravity anomaly grid for enhanced geodetic and geophysical studies in Antarctica, Geophys. Res. Lett., 43, 600–610, doi:10.1002/2015GL067439.

EIGEN-6C4 Gravity Model (5km) ICGEM, 2014

Förste et al.

Synthesis of gravity disturbances and height anomalies from EIGEN-6C4, one of the latest global, high-resolution, combined earth gravity field models. The gravity disturbances are a good approximation of gravity anomalies. The height anomaly is a good approximation of the geoid height (both quantities are the same at the ocean). EIGEN-6C4 provides a maximum resolution of about 10 km (Nmax = 2190), and is calculated from satellite data (GRACE and GOCE satellite gravity missions), satellite altimetry over the ocean, and global terrestrial data. However, over Antarctica terrestrial data could not be included, therefore, you might see considerable differences to the “AntGG Gravity Anomaly Grid”.

Förste, Christoph; Bruinsma, Sean.L.; Abrikosov, Oleg; Lemoine, Jean-Michel; Marty, Jean Charles; Flechtner, Frank; Balmino, G.; Barthelmes, F.; Biancale, R. (2014): EIGEN-6C4 The latest combined global gravity field model including GOCE data up to degree and order 2190 of GFZ Potsdam and GRGS Toulouse. GFZ Data Services.

World Magnetic Model NOAA NGDC, 2016

Chulliat et al.

Magnetic Declination degree lines and magnetic south pole locations

Chulliat, A., S. Macmillan, P. Alken, C. Beggan, M. Nair, B. Hamilton, A. Woods, V. Ridley, S. Maus and A. Thomson, 2014. The US/UK World Magnetic Model for 2015-2020, NOAA National Geophysical Data Center, Boulder, CO, doi: 10.7289/V5TH8JNW [access date]. https://www.ngdc.noaa.gov/geomag/WMM/DoDWMM.shtml

ADMAP Magnetic Anomaly (5km) SCAR, 2001

Golynsky et al.

Antarctic Digital Magnetic Anomaly Map (ADMAP) compiled using Orsted and CHAMP satellite total intensity anomaly data. Data gaps are augmented for the wavelengths larger than 400 km. Map unit is nT.

Golynsky, A., M. Chiappini, D. Damaske, F. Ferraccioli, J. Ferris, C. Finn, M. Ghidella, T. Isihara, A. Johnson, H.R. Kim, L. Kovacs, J. LaBrecque, V. Masolov, Y. Nogi, M. Purucker, P. Taylor, and M. Torta, 2001, ADMAP – Magnetic Anomaly Map of the Antarctic, 1:10 000 000 scale map, in Morris, P., and R. von Frese, eds., BAS (Misc.) 10, Cambridge, British Antarctic Survey.

Geothermal Heat Flux (5km) JGR, 2015

An et al.

Geothermal heat flux (mW/m^2) inferred from seismic velocities

An, M., Wiens, D. A., Zhao, Y., Feng, M., Nyblade, A., Kanao, M., ... & Lévêque, J. J. (2015). Temperature, lithosphere-asthenosphere boundary, and heat flux beneath the Antarctic Plate inferred from seismic velocities. Journal of Geophysical Research: Solid Earth, 120(12), 8720-8742. http://onlinelibrary.wiley.com/doi/10.1002/2015JB011917/full

The very first version of Quantarctica was designed for glaciologists who needed an all-in-one mapping environment that they could use on the ice. Modeled ice flow, thickness, mass balance, and snow accumulation coexist with comprehensive databases of subglacial hydrology and grounding lines to give glaciologists a solid jumping-off point for planning, fieldwork, visualization, and modelling.

Surface snow isotopes The Cryosphere, 2016

Touzeau et al.

Isotopic composition from varied snow samples from East Antarctica. The database provides temperature and water isotopes d18O, d-ex, 17O-ex in samples from surface snow, snow pits and precipitation

Touzeau, A., Landais, A., Stenni, B., Uemura, R., Fukui, K., Fujita, S., Guilbaud, S., Ekaykin, A., Casado, M., Barkan, E., Luz, B., Magand, O., Teste, G., Le Meur, E., Baroni, M., Savarino, J., Bourgeois, I., and Risi, C.: Acquisition of isotopic composition for surface snow in East Antarctica and the links to climatic parameters, The Cryosphere, 10, 837-852, https://doi.org/10.5194/tc-10-837-2016, 2016.

GSFC Drainage systems GSFC, 2012

Zwally et al.

This dataset provides boundaries of Antarctic drainage systems for the ice sheet and ice shelves. Characteristics of each system (Table 3 in the reference) are also included in the attribute table. The original dataset shows polygons of full (grounded + floating portions) drainage systems and their grounded portions only. The dataset provided in Quantarctica is recalculated so that grounded and floating portions of each drainage system are shown.

Zwally, H. Jay, Mario B. Giovinetto, Matthew A. Beckley, and Jack L. Saba, 2012, Antarctic and Greenland Drainage Systems, GSFC Cryospheric Sciences Laboratory, at http://icesat4.gsfc.nasa.gov/cryo_data/ant_grn_drainage_systems.php

ASAID Grounding/hydrostatic lines NSIDC, 2011

Bindschadler, Choi, and ASAID Collaborators

High-resolution image-derived grounding line position for the Antarctic Ice Sheet. The data are derived using customized software to combine data from Landsat-7 imagery and Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry, which were primarily collected between 1999 to 2003. The data were developed as part of the Antarctic Surface Accumulation and Ice Discharge (ASAID) project.

Bindschadler, R., H. Choi, and ASAID Collaborators. 2011. High-resolution Image-derived Grounding and Hydrostatic Lines for the Antarctic Ice Sheet. Boulder, Colorado, USA: National Snow and Ice Data Center. Digital media.

RAISED Paleo ice extents QSR, 2014

Bentley et al.

New synthesis of geological and glaciological datasets related to the Antarctic Ice Sheet deglacial history since the Last Glacial Maximum. Series of timeslice maps are provided for 20 ka, 15 ka, 10 ka and 5 ka, including grounding line position and ice sheet thickness changes, along with a clear assessment of levels of confidence

Bentley, M. J., Cofaigh, C. Ó., Anderson, J. B., Conway, H., Davies, B., Graham, A. G., ... & Mackintosh, A. (2014). A community-based geological reconstruction of Antarctic Ice Sheet deglaciation since the Last Glacial Maximum. Quaternary Science Reviews, 100, 1-9. http://www.sciencedirect.com/science/article/pii/S0277379114002546?via%3Dihub

Blue ice areas Annals of Glaciology, 2014

Hui et al.

This dataset provides blue ice areas detected using Landsat ETM+ and MODIS satellite data. Areas and perimetres of each blue-ice polygon are included in the attribute, which was calculated by the Quantarctica project.

Hui, F.M., T.Y. Ci, X. Cheng, T.A. Scambos, Y. Liu, Y.M. Zhang, Z.H. Chi, H.B. Huang, X.W. Wang, F. Wang, C. Zhao and Z.Y. Jin 2014. Mapping blue ice areas in Antarctica using ETM+ and MODIS data. Annals of Glaciology, 55(66): 129-137.

Ice rises inventory NPI, 2015

Moholdt, G., & Matsuoka, K.

Inventory of Antarctic ice rises and rumples. Outlines and statistics for over 700 ice rises and rumples, derived from visual interpretation of MODIS and Landsat imagery, MEaSUREs ice velocity and BEDMAP2.

Moholdt, G., & Matsuoka, K. (2015). Inventory of Antarctic ice rises and rumples (version 5) [Data set]. Norwegian Polar Institute.

Subglacial lakes, Wright & Siegert Antarctic Science, 2012

Wright, A., and Sigert, M.

This data set is a new inventory of locations, dimensions and data sources for 379 subglacial lakes. A major advance is the rise in the total number of lakes from the 145 known at the time of the last inventory in 2005.

Wright, A., & Siegert, M. (2012). A fourth inventory of Antarctic subglacial lakes. Antarctic Science, 24(6), 659-664. doi:10.1017/S095410201200048X

Subglacial lakes, Blankenship NSIDC, 2009

Blankenship et al.

Subglacial lake classification collection based on radar reflection properties. The Subglacial lakes are separated into four categories specified by radar reflection properties. Additional information includes: latitude, longitude, length (in kilometers), hydro-potential (in meters), bed elevation (in meters above WGS84), and ice thickness (in meters). Source data used to compile this data set were collected between 1998 and 2001.

Blankenship, David D., Sasha P. Carter, John W. Holt, David L. Morse, Matthew E. Peters, and Duncan A. Young. 2009. Antarctic Subglacial Lake Classification Inventory. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media.

Subglacial lakes, Smith Journal of Glaciology, 2009

Smith et al.

Outlines of subglacial lakes identified with ICESat altimetry.

Smith, B. E., H. A. Fricker, I. R. Joughin, and S. Tulaczyk (2009), An inventory of active subglacial lakes in Antarctica detected by ICESat (2003-2008), J. Glaciol., 55(192), 573-595

Recovery Subglacial Lakes Nature, 2007

Bell et al.

Outlines of Recovery Lakes A through D in East Antarctica.

Bell, R., M. Studinger, C.A. Shuman, M.A. Fahnestock and I. Joughin (2007), Large subglacial lakes in East Antarctica at the onset of fast-flowing ice streams, Nature, 445, 904-907.

Vostok Subglacial Lake EPSL, 2003

An et al.

Outlines of subglacial lake Vostok in East Antarctica.

Studinger, M., R.E. Bell, G.D. Karner, A.A. Tikku, J.W. Holt, D.L. Morse, T.G. Richter, S.D. Kempf, M.E. Peters, D.D. Blankenship, R.E. Sweeney, V.L. Rystrom (2003), Ice cover, landscape setting, and geological framework of Lake Vostok, East Antarctica. Earth Planet. Sci. Lett., 205, 195-210.

Subglacial water flux (modelled, 1km) Nature Geoscience, 2013

Le Brocq et al.

Modelled subglacial water flux beneath the grounded ice sheet. Uses BEDMAP2 ice sheet configuration to route subglacial meltwater derived from numerical ice sheet model output (from Frank Pattyn).

Le Brocq, A. M., Ross, N., Griggs, J. A., Bingham, R. G., Corr, H. F., Ferraccioli, F., ... & Siegert, M. J. (2013). Evidence from ice shelves for channelized meltwater flow beneath the Antarctic Ice Sheet. Nature Geoscience, 6(11), 945-948. https://www.nature.com/articles/ngeo1977

ALBMAP Masks (5km) ESSD, 2010

Le Brocq et al.

These grids summarise processing which has been carried out on the various ALBMAP datasets described below.

Le Brocq, A. M., Payne, A. J., and Vieli, A.: An improved Antarctic dataset for high resolution numerical ice sheet models (ALBMAP v1), Earth Syst. Sci. Data, 2, 247-260, doi:10.5194/essd-2-247-2010, 2010.

ALBMAP Snow accumulation, Arthern (5km) ESSD, 2010

Arthern et al.

This accumulation dataset was derived from interpolation of in situ point measurements, i.e. snow pits, ice cores and stake measurements. Passive microwave satellite data (firn emissivity) were used as a “forcing field” to control the interpolation. The original data were supplied at a resolution of 25 km. The data were, here, interpolated onto the 5 km grid using spline interpolation. The unit of the data is meters in ice equivalent per year.

Arthern, R. J., Winebrenner, D. P., and Vaughan, D. G.: Antarctic snow accumulation mapped using polarization of 4.3-cm wavelength microwave emission, J. Geophys. Res.-Atmos., 111, D06107, doi:10.1029/2004JD005667, 2006.

ALBMAP Snow accumulation, Van de Berg (5km) ESSD, 2010

Van de Berg et al.

This accumulation dataset is an output from the RACMO regional model. The data were provided as lat-lon point measurements, these were reprojected onto the polar stereographic grid and interpolated onto the 5 km grid using spline interpolation. The unit of the data is meters in ice equivalent per year.

Van de Berg, W. J., van den Broeke, M. R., and van Meijgaard, E.: Reassessment of the Antarctic surface mass balance using calibrated output of a regional atmospheric climate model, J. Geophys. Res., 111, D11104, doi:10.1029/2005JD006495, 2006.

ALBMAP Surface air temperature (5km) ESSD, 2010

Comiso, J.C.

The surface temperature estimates in °C are derived from AVHRR infrared data. Annual mean temperatures from 1982–2004 were averaged to provide the surface air temperature field.

Comiso, J. C.: Variability and trends in Antarctic surface temperatures from in situ and satellite infrared measurements, J. Climate, 13(10), 1674–1696, 2000.

ALBMAP Firn thickness (clipped, 5km) ESSD, 2010

Van den Broeke et al.

The spatial estimate of the firn correction for Antarctica has been produced using a regional climate model (RACMO), clipped to the current Antarctic ice extent. The firn correction is defined as the difference between the actual depth of the firn layer and the depth that the firn would be if it was all at the density of meteoric ice.

Van den Broeke, M. R., van de Berg, W. J., and van Meijgaard, E.: Firn depth correction along the Antarctic grounding line, Antarct. Sci., 20(5), 513–517, doi:10.1017/S095410200800148X, 2008.

ALBMAP Geothermal flux, Fox Maule (5km) ESSD, 2010

Fox Maule et al.

This geothermal flux dataset was derived from satellite magnetic data and a thermal model. The point data provided were interpolated on to the 5 km grid using spline interpolation. The data unit is mWm-2.

Fox Maule, C., Purucker, M., Olsen, N., and Mosegaard, K.: Heat flux anomalies in Antarctica revealed by satellite magnetic data, Science, 309, 464–467, 2005.

ALBMAP Geothermal flux, Shapiro & Ritzwoller (5km) ESSD, 2010

Shapiro, N. M. and Ritzwoller, M. H.

This dataset uses a global seismic model of the crust and upper mantle to extrapolate existing heat-flux measurements to areas where there are few data, using a “structural similarity function”. The original data are gridded on a geographic (lat-lon) grid, so when they are projected to a polar stereographic projection, this creates problems in gridding straight to 5 km resolution, due to the directionality of the points used in the interpolation procedure. The gridding introduces elongated features which are not present in the original data. The effective resolution of the data (in latitude anyway) is 100 km. Therefore the data were first gridded on to a 100 km grid using spline interpolation. The 100 km grid points were then reinterpolated, again using spline interpolation, onto the 5 km grid. This reduces the elongated features whilst retaining most of the detail in the original dataset. The data unit is mWm-2.

Shapiro, N. M. and Ritzwoller, M. H.: Inferring surface heat flux distributions guided by a global seismic model: particular application to Antarctica, Earth Planet. Sc. Lett., 223, 213–224, 2004.

ALBMAP Upper ice surface elevation (5km) ESSD, 2010

Bamber et al., Liu et al.

This DEM is largely derived from the DEM of Bamber et al. (2009) (JLB/JAG DEM), in combination with the RAMP DEM (Antarctic Peninsula, Liu et al., 1999).

Bamber, J. L., Gomez-Dans, J. L., and Griggs, J. A.: A new 1 km digital elevation model of the Antarctic derived from combined satellite radar and laser data – Part 1: Data and methods, The Cryosphere, 3, 101–111, doi:10.5194/tc-3-101-2009, 2009.

Liu, H., Jezek, K., and Li, B.: Development of an Antarctic digital elevation model by integrating cartographic and remotely sensed data: A geographic information system based approach, J. Geophys. Res., 104(B10), 23199–23213, 1999.

ALBMAP Lower ice surface elevation 2 (5km) ESSD, 2010

Griggs et al., Lythe et al., Vaughan et al., Holt et al., Le Brocq et al.

Lower ice surface elevation in m asl from BEDMAP (Version 1) plus recalculated ice shelf thickness derived from new surface DEM data and new data from the Recovery basin.

Griggs, J. A. and Bamber, J. L.: Ice shelf thickness over Larsen C, Antarctica, derived from satellite altimetry, Geophys. Res. Lett., 36, L19501, doi:10.1029/2009GL039527, 2009b.

Lythe, M. B., Vaughan, D. G.. and the BEDMAP Consortium: BEDMAP: A new ice thickness and subglacial topographic model of Antarctica, J. Geophys. Res.-Sol. Ea., 106(B6), 11335– 11351, 2001.

Vaughan, D. G., Corr, H. F. J., Ferraccioli, F., Frearson, N., O’Hare, A., Mach, D., Holt, J., Blankenship, D., Morse, D., and Young, D. A.: New boundary conditions for theWest Antarctic ice sheet: subglacial topography beneath Pine Island Glacier, Geophys. Res. Lett., 33, L09501, doi:10.1029/2005GL025588, 2006.

Holt, J. W., Blankenship, D. D., Morse, D. L., Young, D. A., Peters, M. E., Kempf, S. D., Richter, T. G., Vaughan, D. G., and Corr, H. F. J.: New boundary conditions for the West Antarctic Ice Sheet: Subglacial topography of the Thwaites and Smith glacier catchments, Geophys. Res. Lett., 33, L09502, doi:10.1029/2005GL025561, 2006

Le Brocq, A. M., Hubbard, A., Bentley, M. J., and Bamber, J. L.: Subglacial topography inferred from ice surface terrain analysis reveals a large un-surveyed basin below sea level in East Antarctica, Geophys. Res. Lett., 34, L16503, doi:10.1029/2008GL034728, 2008.

ALBMAP Lower ice surface elevation (5km) ESSD, 2010

Griggs et al., Lythe et al., Vaughan et al., Holt et al.

Lower ice surface elevation in m asl from BEDMAP (Version 1) plus recalculated ice shelf thickness derived from new surface DEM data.

Griggs, J. A. and Bamber, J. L.: Ice shelf thickness over Larsen C, Antarctica, derived from satellite altimetry, Geophys. Res. Lett., 36, L19501, doi:10.1029/2009GL039527, 2009b.

Lythe, M. B., Vaughan, D. G.. and the BEDMAP Consortium: BEDMAP: A new ice thickness and subglacial topographic model of Antarctica, J. Geophys. Res.-Sol. Ea., 106(B6), 11335– 11351, 2001.

Vaughan, D. G., Corr, H. F. J., Ferraccioli, F., Frearson, N., O’Hare, A., Mach, D., Holt, J., Blankenship, D., Morse, D., and Young, D. A.: New boundary conditions for theWest Antarctic ice sheet: subglacial topography beneath Pine Island Glacier, Geophys. Res. Lett., 33, L09501, doi:10.1029/2005GL025588, 2006.

Holt, J. W., Blankenship, D. D., Morse, D. L., Young, D. A., Peters, M. E., Kempf, S. D., Richter, T. G., Vaughan, D. G., and Corr, H. F. J.: New boundary conditions for the West Antarctic Ice Sheet: Subglacial topography of the Thwaites and Smith glacier catchments, Geophys. Res. Lett., 33, L09502, doi:10.1029/2005GL025561, 2006.

ALBMAP Bed/bathymetry elevation 2 (5km) ESSD, 2010

Lythe et al. and BEDMAP, Nitsche et al., Le Brocq et al.

Bed elevation under grounded ice was derived by subtracting the ice thickness from the combined ice surface dataset. Bathymetry beneath ice shelves were reinterpolated from BEDMAP (version 1), and new data plus Recovery basin modification are included.

Lythe, M. B., Vaughan, D. G.. and the BEDMAP Consortium: BEDMAP: A new ice thickness and subglacial topographic model of Antarctica, J. Geophys. Res.-Sol. Ea., 106(B6), 11335–11351, 2001.

Nitsche, F.O., Jacobs, S., Larter, R. D., and Gohl, K.: Bathymetry of the Amundsen Sea continental shelf: Implications for geology, oceanography, and glaciology, Geochem. Geophy. Geosy., 8, Q10009, doi:10.1029/2007GC001694, 2007.

Le Brocq, A. M., Hubbard, A., Bentley, M. J., and Bamber, J. L.: Subglacial topography inferred from ice surface terrain analysis reveals a large un-surveyed basin below sea level in East Antarctica, Geophys. Res. Lett., 34, L16503, doi:10.1029/2008GL034728, 2008.

ALBMAP Bed/bathymetry elevation (5km) ESSD, 2010

Lythe et al. and BEDMAP, Nitsche et al.

Bed elevation under grounded ice was derived by subtracting the ice thickness from the combined ice surface dataset. Bathymetry beneath ice shelves were reinterpolated from BEDMAP (version 1) and new data is included.

Lythe, M. B., Vaughan, D. G.. and the BEDMAP Consortium: BEDMAP: A new ice thickness and subglacial topographic model of Antarctica, J. Geophys. Res.-Sol. Ea., 106(B6), 11335–11351, 2001.

Nitsche, F.O., Jacobs, S., Larter, R. D., and Gohl, K.: Bathymetry of the Amundsen Sea continental shelf: Implications for geology, oceanography, and glaciology, Geochem. Geophy. Geosy., 8, Q10009, doi:10.1029/2007GC001694, 2007.

MEASURES Ice flow speed (450m) NSIDC, 2017

Rignot et al.

Provides the first comprehensive, high-resolution (450 m), digital mosaics of ice motion in Antarctica. It is assembled from multiple satellite interferometric synthetic-aperture radar systems. Data was largely acquired during the International Polar Year 2007 to 2009, as well as between 2013 and 2016. Additional data acquired between 1996 and 2016 was used as needed to maximize coverage. This dataset is part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program

Rignot, E., J. Mouginot, and B. Scheuchl. 2017. MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/D7GK8F5J8M8R. [Date Accessed].

Firn density (33km) The Cryosphere, 2011

Ligtenberg et al.

Modelled (IMAU Firn Density Model) near-surface (0-1 m depth) firn density and depths for firn densities of 830 and 550 kg/m^3. Forced at top by RACMO2.3p1 mass fluxes and skin temperature. Averaging period:1979-2011.

Ligtenberg, S. R. M., M. M. Helsen and M. R. van den Broeke, 2011: An improved semi-empirical model for the densification of Antarctic firn, The Cryosphere 5, 809-819, doi: doi:10.5194/tc-5-809-2011.

SUMER Ice shelf buttressing (modelled, 1km) Nature Climate Change, 2016

Fürst et al.

This data set consists of high-resolution data about ice-shelf buttressing for the whole of Antarctica. Buttressing is inferred from known ice geometry and ice motion with the Elmer/Ice ice flow model. Input sources are Bedmap2, MEaSUREs surface ice velocities, and the MEaSUREs grounding-line positions. This data set is part of the French National Research Agency’s project on Survey and Modelling of East Antarctica (SUMER)

Fürst, J. J., Durand, G., Gillet-Chaulet, F., Tavard, L., Rankl, M., Braun, M., & Gagliardini, O. (2016). The safety band of Antarctic ice shelves. Nature Climate Change, 6(5), 479-482. http://dx.doi.org/10.5067/FWHORAYVZCE7

Surface melt rate (1999-2009, QuikSCAT, observed, 4.5km) JGR, 2015

Trusel et al.

Surface meltwater production using an empirical relationship between radar backscatter from the QuikSCAT satellite and melt calculated from in situ energy balance observations. Resolution: ~5 km. Averaging period: 1999–2009. Unit: mm weq yr-1 (= kg m-2 yr-1)

Trusel, L. D., K. E. Frey, S. B. Das, P. Kuipers Munneke, and M. R. van den Broeke, 2013: Satellite-based estimates of Antarctic surface meltwater fluxes, Geophysical Research Letters 40, 6148–6153, doi:10.1002/2013GL058138. http://onlinelibrary.wiley.com/doi/10.1002/2013GL058138/abstract

MEaSUREs Antarctic boundaries (v2) NSIDC, 2017

Mouginot et al.

Maps of Antarctic ice shelves, the Antarctic coastline and Antarctic basins. The maps are assembled from 2008-2009 ice-front data from ALOS PALSAR and ENVISAT ASAR data acquired during International Polar Year, 2007-2009 (IPY), the InSAR-based grounding line data (MEaSUREs Antarctic Grounding Line from Differential Satellite Radar Interferometry), augmented with other grounding line sources, the Antarctic ice velocity map (MEaSUREs InSAR-Based Antarctica Ice Velocity Map), and the Bedmap-2 DEM. This data set is part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program.

Mouginot, J., B. Scheuchl, and E. Rignot. 2017. MEaSUREs Antarctic Boundaries for IPY 2007-2009 from Satellite Radar, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/AXE4121732AD. [Date Accessed]. https://nsidc.org/data/nsidc-0709/versions/2

Quantarctica includes a comprehensive ice core database with modern and historical ice core locations, links to core data, and basic information about each ice core's depth, year, and managing program.

Ice cores database ITASE, 2017

ITASE, CCI, and the WAIS Divide Team

Ice Core locations and metadata compiled from multiple sources. See data table for links to data and citation information for individual ice cores.

ITASE IceReader: http://www.icereader.org/icereader/listData.jsp

Climate Change Institute Antarctic Ice Core Data: http://cci.icecoredata.org/Antarctica.html

WAIS Divide Project summary paper: https://www.nature.com/articles/nature12376

By including a complete picture of average temperature, salinity, nutrients, currents, and more, Quantarctica ensures that your view of the Southern Ocean is just as complete as what's happening on land.

Southern Ocean fronts Deep Sea Research, 1995

Orsi et al.

The subsurface Southern Ocean is characterized by relatively uniform zones separated by zonal fronts. Climatological position of four (three?) of the major fronts were estimated from observed temperature and salinity data.

Alejandro H. Orsi, Thomas Whitworth III, and Worth D. Nowlin Jr (1995), On the meridional extent and fronts of the Antarctic Circumpolar Current., Deep-Sea Research, 42, 5, 641-673

SOSE Mean surface current speed (16km) JPO, 2010

Mazloff et al.

Surface current velocity estimated by data-constrained numerical model. Ocean currents are difficult quantity to measure with variability of wide spatial and temporal scales. Here we provide one of the best estimates of current velocity at the surface. This is output from a state estimate numerical model, SOSE, where ocean state satisfying the laws of physics (e.g. conservation of mass and momentum) were estimated by minimizing differences from available observed data (satellite, ship-based, etc.).

M. Mazloff, P. Heimbach, and C. Wunsch, 2010: "An Eddy-Permitting Southern Ocean State Estimate." J. Phys. Oceanogr., 40, 880–899. doi: 10.1175/2009JPO4236.1

World Ocean Atlas (WOA) 2013 Temperature NOAA, 2013

Locarnini et al.

Compilation of observed temperature of sea water. All available ocean observation data were quality controlled, correction applied where necessary, and interpolated in the vertical direction to standard depths. In the horizontal direction, “objective mapping” was used to achieve statistically best interpolation to the grid. No adjustment for pressure effects (i.e. “potential temperature”) is applied. Note that most of data were collected in austral summer and seasonally biased. Layers provided for austral summer and winter climatology at 0, 50, 200, and 500 m depths.

Locarnini, R. A., A. V. Mishonov, J. I. Antonov, T. P. Boyer, H. E. Garcia, O. K. Baranova, M. M. Zweng, C. R. Paver, J. R. Reagan, D. R. Johnson, M. Hamilton, and D. Seidov, 2013. World Ocean Atlas 2013, Volume 1: Temperature. S. Levitus, Ed., A. Mishonov Technical Ed.; NOAA Atlas NESDIS 73, 40 pp.

World Ocean Atlas (WOA) 2013 Salinity NOAA, 2013

Zweng et al.

Compilation of observed salinity of sea water. All available ocean observation data were quality controlled, correction applied where necessary, and interpolated in the vertical direction to standard depths. In the horizontal direction, “objective mapping” was used to achieve statistically best interpolation to the grid. Salinity is converted to Practical Salinity Scale (1978) hence unitless. Note that most of data were collected in austral summer and seasonally biased. Layers provided for austral summer and winter climatology at 0, 50, 200, and 500 m depths.

Zweng, M.M, J.R. Reagan, J.I. Antonov, R.A. Locarnini, A.V. Mishonov, T.P. Boyer, H.E. Garcia, O.K. Baranova, D.R. Johnson, D.Seidov, M.M. Biddle, 2013. World Ocean Atlas 2013, Volume 2: Salinity. S. Levitus, Ed., A. Mishonov Technical Ed.; NOAA Atlas NESDIS 74, 39 pp.

World Ocean Atlas (WOA) 2013 Oxygen NOAA, 2013

Garcia et al.

Compilation of observed oxygen concentration of sea water. All available ocean observation data were quality controlled, correction applied where necessary, and interpolated in the vertical direction to standard depths. In the horizontal direction, “objective mapping” was used to achieve statistically best interpolation to the grid. No adjustment for pressure effects (i.e. “potential temperature”) is applied. Note that most of data were collected in austral summer and seasonally biased. Layers provided for austral summer and winter climatology at 0, 50, 200, and 500 m depths.

Garcia, H. E., R. A. Locarnini, T. P. Boyer, J. I. Antonov, O.K. Baranova, M.M. Zweng, J.R. Reagan, D.R. Johnson, 2014. World Ocean Atlas 2013, Volume 3: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation. S. Levitus, Ed., A. Mishonov Technical Ed.; NOAA Atlas NESDIS 75, 27 pp.

World Ocean Atlas (WOA) 2013 Phosphate, Nitrate, and Silicate NOAA, 2013

Garcia et al.

Compilation of observed silica concentration of sea water. All available ocean observation data were quality controlled, correction applied where necessary, and interpolated in the vertical direction to standard depths. In the horizontal direction, “objective mapping” was used to achieve statistically best interpolation to the grid. No adjustment for pressure effects (i.e. “potential temperature”) is applied. Note that most of data were collected in austral summer and seasonally biased. Layers provided for austral summer and winter climatology at 0, 50, 200, and 500 m depths.

Garcia, H. E., R. A. Locarnini, T. P. Boyer, J. I. Antonov, O.K. Baranova, M.M. Zweng, J.R. Reagan, D.R. Johnson, 2014. World Ocean Atlas 2013, Volume 4: Dissolved Inorganic Nutrients (phosphate, nitrate, silicate). S. Levitus, Ed., A. Mishonov Technical Ed.; NOAA Atlas NESDIS 76, 25 pp.

In addition to including ten years of measured sea ice extents and concentrations, Quantarctica makes it easy to import outside satellite imagery and satellite-derived sea ice data for cruise logistics, sampling, and model visualization.

Median sea ice extent 1981-2010 NSIDC, 2017

Fetterer et al.

Monthly median sea ice extents for the period 1981-2010.

Fetterer, F., K. Knowles, W. Meier, M. Savoie, and A. K. Windnagel. 2016, updated daily. Sea Ice Index, Version 2. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: http://dx.doi.org/10.7265/N5736NV7. [Date Accessed].

NSIDC February and October Sea Ice Concentration (25km) NSIDC, 2017

Fetterer et al.

February (min) and October (max) satellite-observed sea ice concentrations from 2007-2017.

Fetterer, F., K. Knowles, W. Meier, M. Savoie, and A. K. Windnagel. 2016, updated daily. Sea Ice Index, Version 2. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: http://dx.doi.org/10.7265/N5736NV7. [Date Accessed]. http://nsidc.org/data/g02135

Proportion of year ice covered (6.25km) AAD, 2017

Spreen et al.

Proportion of time the ocean is covered by sea ice of concentration 85% or higher. Calculated from AMSR-E satellite estimates of daily sea ice concentration at 6.25km resolution, using concentration data from 1-Jul-2002 to 30-Jun-2011. 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.

Spreen G, Kaleschke L, Heygster G (2008), Sea ice remote sensing using AMSR-E 89 GHz channels, J. Geophys. Res., doi:10.1029/2005JC003384 http://www.ifm.zmaw.de/en/research/remote-sensing-assimilation/sea-ice/amsr-e-sea-ice-concentration/

Quantarctica v3 has expanded data coverage beyond the physical sciences into the social sciences. Explore old stations, monuments, and other historical sites, and see how your own route or site compares with some of the most famous expeditions in history.

Non-native species incursions Biodiversity and Conservation, 2015

Hughes et al.

Non-native species removal and eradication attempts within the Antarctic continent and off-shore islands

Hughes, K. A., Pertierra, L. R., Molina-Montenegro, M. A., & Convey, P. (2015). Biological invasions in terrestrial Antarctica: what is the current status and can we respond?. Biodiversity and Conservation, 24(5), 1031-1055. https://doi.org/10.1007/s10531-015-0896-6

ADD Historic sites and monuments SCAR, 2016

SCAR ADD

Downloaded June 2016 from http://www.add.scar.org/

Originally Downloaded Feb 2015 from Antarctic Treaty Secretariat: http://www.ats.aq/documents/atcm36/ww/atcm36_ww004_e.pdf

Historic stations Polar Record, 2019

Headland, R.K.

The earliest winter scientific station established in the Antarctic was in 1883 as part of the International Polar Year (IPY) of 1883. Subsequently, to the IPY of 2007-2009, scientific stations have been deployed on 139 sites (103 on the Antarctic continent, 36 on peri-Antarctic islands), by 24 countries for a cumulative total of 2666 winters to that of 2008.

Headland, R. K. (2009). Antarctic winter scientific stations to the International Polar Year, 2007–2009. Polar Record, 45(1), 9-24.

Five historic expedition routes (digitized) AGS/PGC, 1975/2017

Dater, H.M.

A selection of routes and tracks from some of the most significant early Antarctic expeditions, from the first circumnavigation of Antarctica by Fabien Gottlieb von Bellingshausen, to the first Trans-Antarctic flight by Lincoln Ellsworth in 1935.

Dater, Henry M. "History of Antarctic Exploration and Scientific Investigation." In Antarctic Map Folio Series, edited by Vivian C. Bushnell: American Geographical Society, 1975.

Quantarctica’s topography data has you covered from the bottom of the ocean to the bottom of the ice, from the deepest submarine canyons to the highest ice domes. When you’re asking how high or how deep, Quantarctica has the answer, thanks to the definitive package of DEMs, contours, bathymetry, and bed topography products with user-customizable contour interval and hillshade settings.

BEDMAP2 (1km) BAS/The Cryosphere, 2013

Fretwell et al.

Bed and surface elevation, ice thickness, uncertainty and data masks

Fretwell, P., Pritchard, H. D., Vaughan, D. G., Bamber, J. L., Barrand, N. E., Bell, R., Bianchi, C., Bingham, R. G., Blankenship, D. D., Casassa, G., Catania, G., Callens, D., Conway, H., Cook, A. J., Corr, H. F. J., Damaske, D., Damm, V., Ferraccioli, F., Forsberg, R., Fujita, S., Gim, Y., Gogineni, P., Griggs, J. A., Hindmarsh, R. C. A., Holmlund, P., Holt, J. W., Jacobel, R. W., Jenkins, A., Jokat, W., Jordan, T., King, E. C., Kohler, J., Krabill, W., Riger-Kusk, M., Langley, K. A., Leitchenkov, G., Leuschen, C., Luyendyk, B. P., Matsuoka, K., Mouginot, J., Nitsche, F. O., Nogi, Y., Nost, O. A., Popov, S. V., Rignot, E., Rippin, D. M., Rivera, A., Roberts, J., Ross, N., Siegert, M. J., Smith, A. M., Steinhage, D., Studinger, M., Sun, B., Tinto, B. K., Welch, B. C., Wilson, D., Young, D. A., Xiangbin, C., and Zirizzotti, A.: Bedmap2: improved ice bed, surface and thickness datasets for Antarctica, The Cryosphere, 7, 375-393, doi:10.5194/tc-7-375-2013, 2013.

RAMP2 (200m) NSIDC, 2012

Liu et al.

Radarsat Antarctic Mapping Project Digital Elevation Model Version 2 provided for both WGS84 and OSU91a elevation datum, contours, and hillshades.

Liu, H., K. C. Jezek, B. Li, and Z. Zhao. 2015. Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/8JKNEW6BFRVD. [Date Accessed].

CryoSat-2 Elevation model (1km) The Cryosphere, 2014

Helm et al.

CryoSat-2-derived elevation model of Antarctica, with 1000m pixel resolution and uncertainty of 3 m ± 15 m. This DEM will tend to have fewer errors in the inland ice areas and more near the coast or other areas with sharp relief.

Helm, V., Humbert, A., and Miller, H.: Elevation and elevation change of Greenland and Antarctica derived from CryoSat-2, The Cryosphere, 8, 1539-1559, https://doi.org/10.5194/tc-8-1539-2014, 2014.

IBCSO (500m) IBCSO/GRL, 2013

Dater, H.M.

International Bathymetric Chart of the Southern Ocean digital elevation model. Coverage: 90-60°S. Includes bed and surface rasters, hillshades, and contours.

Arndt, J. E., et al. (2013), The International Bathymetric Chart of the Southern Ocean (IBCSO) Version 1.0—A new bathymetric compilation covering circum-Antarctic waters, Geophys. Res. Lett., 40, 3111–3117, doi:10.1002/grl.50413.

ETOPO1 (2km / 1 arc-minute) NOAA NGDC, 2009

Amante, C. and B.W. Eakins

Low resolution global elevation model. Coverage: 90-40°S

Amante, C. and B.W. Eakins, 2009. ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis. NOAA Technical Memorandum NESDIS NGDC-24. National Geophysical Data Center, NOAA. doi:10.7289/V5C8276M [access date].

Quantarctica includes low- and medium-resolution satellite mosaics from Landsat, MODIS, and RADARSAT, now with additional coverage of the Subantarctic islands. Need something a little more high-resolution or more recent? Go ahead and import your own satellite or aerial imagery with no extra work required - QGIS is built on the open-source GDAL library, which can read over 150 different image formats.

LIMA Landsat Image Mosaic of Antarctica (15/240m) USGS / Rem. Sens. Environ., 2008

Bindschadler et al.

Low-resolution center-filled Landsat Image Mosaic Of Antarctica (LIMA) and mosaicked 15m CIRREF tiles

R. Bindschadler, P. Vornberger, A. Fleming, A. Fox, J. Mullins, D. Binnie, S.J. Paulsen, B. Granneman, D. Gorodetzky. The Landsat image mosaic of Antarctica, Rem. Sens. Environ., 112 (2008), pp. 4214-4226

Subantarctic Landsat (15m) USGS/NASA, 2017

 

Pansharpened, clipped 15m Landsat-8 image mosaics of various Antarctic and Subantarctic islands not included in LIMA. Images were selected for best illumination and low cloud cover from the Landsat-8 record (2013-2017) Imagery has been color stretched, converted to 8-bit pixel values and converted to lossy .JP2 format, and is not suitable for remote sensing analysis.

Landsat-8 imagery courtesy of the U.S. Geological Survey

MODIS mosaic (125m) NSIDC, 1999/2013

Haran et al., Scambos et al.

MODIS Mosaic of Antarctica (MOA) image map

Haran, T., J. Bohlander, T. Scambos, T. Painter, and M. Fahnestock. 2005, updated 2013. MODIS Mosaic of Antarctica 2003-2004 (MOA2004) Image Map, Version 1. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: http://dx.doi.org/10.7265/N5ZK5DM5. [Date Accessed].

Scambos, T., T. Haran, M. Fahnestock, T. Painter, and J. Bohlander. 2007. MODIS-based Mosaic of Antarctica (MOA) data sets: continent-wide surface morphology and snow grain size, Remote Sensing of Environment. 111. 242-257. http://dx.doi.org/10.1016/j.rse.2006.12.020 Rem. Sens. Environ., 111 (2007), pp. 242-257

RAMP RADARSAT mosaic (100m) NSIDC, 1999/2013

Jezek et al.

RADARSAT-1 Antarctic Mapping Project (RAMP) SAR imagery

Jezek, K. C. 1999. Glaciological properties of the Antarctic ice sheet from RADARSAT-1 synthetic aperture radar imagery. Annals of Glaciology 29:286-290. Jezek, K.C. in press. RADARSAT-1 Antarctic mapping project: change detection and surface velocity campaign. Annals of Glaciology 34. ## Jezek, K. C., J. C. Curlander, F. Carsey, C. Wales, and R. G. Barry. 2013. RAMP AMM-1 SAR Image Mosaic of Antarctica. [Indicate subset used]. Boulder, Colorado USA. http://dx.doi.org/10.5067/8af4zrpuls4h NSIDC: National Snow and Ice Data Center. [Date Accessed].