Complete map of ice motion in Antarctica combining phase data in the interior and speckle tracking in the fast-moving sectors.

We present a new map of Antarctic ice velocity that is ten times more precise than prior maps and reveals ice motion at a high precision over 80% of the continent versus 20% in the past. The ice motion vector map provides novel constrains on interior ice motion and its connection with the glaciers and ice stream that control the stability and mass balance of the Antarctic Ice Sheet.

This mosaic is a merge between phase-derived velocity and the earlier mosaic of ice velocity derived from speckle and feature tracking (Mouginot et al., 2017). Where available, the phase data takes priority. At the transition boundary, we apply a feathering technique to minimize the discontinuity in velocity and in spatial derivative in both horizontal directions, but preserving the phase data.

For the phase, we rely on the entire SAR archive since 1992 with six sensors from multiple space agencies. The data are the Canadian Space Agency (CSA) with RADARSAT-1 and RADARSAT-2, the European Space Agency (ESA) with the Earth Remote Sensing Satellites 1-2 (ERS-1/2) and the Envisat ASAR; the Japan Aerospace Exploration Agency (JAXA) with ALOS PALSAR-1 and a few scenes from ALOS2 PALSAR. We do not include data from the European Copernicus Sentinel-1a/b SARs because the TopSAR acquisition mode of the Sentinel-1a/b data produces residual phase jumps at burst boundaries that make it impractical for precision phase-mapping, even with data stacking and additional corrections (Scheuchl et al., 2016). Each sensor has its own advantage and inconvenience: Envisat ASAR and RADARSAT-2 are the only sensors providing descending passes over East Antarctica. ALOS PALSAR-1 provides ascending passes with a high temporal coherence along the periphery. RADARSAT-2 provides the most complete dataset with coverage of the southernmost regions including ascending and descending passes in left looking mode and right looking coverage with ascending and descending passes similar to Envisat ASAR. ERS-1/2 provides high coherence images (1-day repeat) over rapidly changing sectors of West Antarctica. Phase-derived velocity are mostly for years between 2007 and 2018 while regions covered by speckle- tracking-derived velocity (along the coasts) are mostly representative of years 2013-2017. SAR and interferogram processing, unwrapping and geocoding were done using GAMMA remote sensing processor.

The data are formatted in Network Common Data Form, Version 4 (NetCDF-4) (.nc) following version 1.6 of the Climate and Forecast (CF) metadata conventions. For more information about working with NetCDF formatted data, visit the UCAR Unidata Network Common Data Form Web site.

This data set includes one file named v_mix.v21May2019.nc (450 m grid spacing).

Spatial Coverage:

The data set spans the continent of Antarctica.

Southernmost Latitude: 90° S 
Northernmost Latitude: 60° S 
Westernmost Longitude: 180° W 
Easternmost Longitude: 180° E

Polar stereographic with true scale at 71° S. Refer to Polar Stereographic Projection and Grid page for more information and polar stereographic grid definitions.

This data set provides a comprehensive ice velocity map of the Antarctic Ice Sheet posted at 450 m grid spacing. The velocity components for the x and y direction, as defined by the polar stereographic grid, are stored in the NetCDF variables named VX and VY and are recorded in m/yr. Error estimates for the velocity components are provided as variables ERRX and ERRY; however, these values should be used more as an indication of relative quality rather than absolute error. The data also include the standard deviations for the velocity estimates (STDX,STDY), as well as a count of scenes (CNT) used to estimate the values for each pixel. Finally, the data include the source for the velocity estimates (SOURCE) from tracking-based techniques (=1), phase-based techniques (=2), or interpolation between tracking- and phase-based techniques (=3).

Data sources:

References and Related Publications:

Michel, R., and E. Rignot. 1999. Flow of Glacier Moreno, Argentina, from Repeat-Pass Shuttle Imaging Radar Images: Comparison of the Phase Correlation Method with Radar Interferometry. Journal of Glaciology 45(149): 93-100.

Mouginot, J., et al. 2017. Comprehensive Annual Ice Sheet Velocity Mapping Using Landsat-8, Sentinel-1, and RADARSAT-2 Data. Remote Sensing 9(4): Art. #364. doi: 10.3390/rs9040364.

Mouginot, J., E. Rignot, and B. Scheuchl. 2015. Sustained increase in ice discharge from the Amundsen Sea Embayment, West Antarctica, from 1973 to 2013. Geophysical Research Letters 41: 1576–1584. doi: 10.1002/2013GL059069.

Mouginot, J., B. Scheuchl, and E. Rignot. 2012. Mapping of Ice Motion in Antarctica Using Synthetic-Aperture Radar Data. Remote Sensing 4(9): 2753-2767. doi: 10.3390/rs4092753.

Rignot, E., J. Mouginot, and B. Scheuchl. 2011. Ice Flow of the Antarctic Ice Sheet. Science 333(6048): 1427-1430. doi: 10.1126/science.1208336.

Rignot, E., J. Mouginot, and B. Scheuchl. 2011. Antarctic grounding line mapping from differential satellite radar interferometry. Geophysical Research Letters 38(10): Art. #L10504. doi: 10.1029/2011GL047109.

Scheuchl, B., J. Mouginot, and E. Rignot. 2012. Ice velocity changes in the Ross and Ronne sectors observed using satellite radar data from 1997 and 2009. The Cryosphere 6: 1019-1030. doi: 10.5194/tc-6-1019-2012.