[en] Accurate estimates of surface mass balance over the Greenland ice sheet (GrIS) would contribute to understanding the cause of recent changes and would help to better estimate the future contribution of the GrIS to sea-level rise. Given the limitations of in-situ measurement, modeling, and remote sensing, it is critical to explore the opportunity to merge the available data to better characterize the spatial and temporal variation of the GrIS surface mass balance (SMB).
This work utilizes a particle batch smoother data assimilation technique that yields SMB estimates that benefit from the snow model Crocus and a 16-day albedo product derived from satellite remote sensing data. Comparison of the results against in-situ SMB measurements shows that the assimilation of the albedo product reduces the root mean square error (RMSE) of the posterior estimates of SMB by 51% and reduces bias by 95%.
Research center :
Sphères - SPHERES
Disciplines :
Earth sciences & physical geography
Author, co-author :
Navari, M.
Margulis, S.
Tedesco, M.
Fettweis, Xavier ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie
van de wal, R.
Language :
English
Title :
Reanalysis Surface Mass Balance of the Greenland Ice Sheet along K-transect (2000-2014)
Publication date :
August 2021
Journal title :
Geophysical Research Letters
ISSN :
0094-8276
eISSN :
1944-8007
Publisher :
Wiley, Washington, United States - District of Columbia
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