Earth System Science Data (Feb 2022)

A new Greenland digital elevation model derived from ICESat-2 during 2018–2019

  • Y. Fan,
  • Y. Fan,
  • Y. Fan,
  • C.-Q. Ke,
  • C.-Q. Ke,
  • C.-Q. Ke,
  • X. Shen,
  • X. Shen,
  • X. Shen

DOI
https://doi.org/10.5194/essd-14-781-2022
Journal volume & issue
Vol. 14
pp. 781 – 794

Abstract

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Greenland digital elevation models (DEMs) are indispensable to fieldwork, ice velocity calculations, and mass change estimations. Previous DEMs have provided reasonable estimations for all of Greenland, but the time span of applied source data may lead to mass change estimation bias. To provide a DEM with a specific time stamp, we applied approximately 5.8×108 ICESat-2 observations from November 2018 to November 2019 to generate a new DEM, including the ice sheet and glaciers in peripheral Greenland. A spatiotemporal model fit process was performed at 500 m, 1 km, 2 km, and 5 km grid cells separately, and the final DEM was posted at the modal resolution of 500 m. A total of 98 % of the grids were obtained by the model fit, and the remaining DEM gaps were estimated via the ordinary Kriging interpolation method. Compared with IceBridge mission data acquired by the Airborne Topographic Mapper (ATM) lidar system, the ICESat-2 DEM was estimated to have a maximum median difference of −0.48 m. The performance of the grids obtained by model fit and interpolation was similar, both of which agreed well with the IceBridge data. DEM uncertainty rises in regions of low latitude and high slope or roughness. Furthermore, the ICESat-2 DEM showed significant accuracy improvements compared with other altimeter-derived DEMs, and the accuracy was comparable to those derived from stereophotogrammetry and interferometry. Overall, the ICESat-2 DEM showed excellent accuracy stability under various topographic conditions, which can provide a specific time-stamped DEM with high accuracy that will be useful to study Greenland elevation and mass balance changes. The Greenland DEM and its uncertainty are available at https://doi.org/10.11888/Geogra.tpdc.271336 (Fan et al., 2021).