Detailed simulations of snow properties and accumulation across the Antarctic Ice Sheet
- 1Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, United States of America (jan.lenaerts@colorado.edu)
- 2Department of Atmospheric and Oceanic Sciences, University of Maryland, College Park, MD, United States of America
- 3Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States of America
- 4Institute for Marine and Atmospheric research Utrecht, Utrecht University, Utrecht, The Netherlands
Surface mass balance (SMB) represents a large uncertainty in characterizing Antarctic Ice Sheet (AIS) mass balance. Atmospheric reanalysis products, which are commonly used for AIS SMB studies, do not include small-scale snow redistribution processes even though these can be of the same order of magnitude as snow accumulation in many parts of the AIS. Therefore, a proper representation of these processes is critical to interpret local SMB and firn observations, such as from ICESat-2 repeat altimetry. In this study, we use a detailed, multi-layer snow model (SNOWPACK) forced by a global atmospheric reanalysis (MERRA-2). Firstly, we show that a new accumulation scheme, designed to better represent wind-driven snow compaction in SNOWPACK, substantially reduces simulated biases in near-surface snow density at 131 locations across the AIS. Next, we employ a distributed version of SNOWPACK to two regions on the AIS, and compare the simulation output to airborne radar and in-situ observations of SMB. Our results demonstrate that SNOWPACK can capture the timing of blowing snow events, snow erosion events, as well as observed kilometer-scale spatial SMB variability. This study illustrates the importance of using high-resolution SMB models when converting surface height (volume) observations to mass changes.
How to cite: Lenaerts, J., Keenan, E., Wever, N., Dattler, M., Reijmer, C., and Medley, B.: Detailed simulations of snow properties and accumulation across the Antarctic Ice Sheet , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10368, https://doi.org/10.5194/egusphere-egu2020-10368, 2020
This abstract will not be presented.