[en] Estimating the Greenland Ice Sheet (GrIS) surface mass balance (SMB) is an important component of current and future projections of sea level rise. Given the lack of in situ information, imperfect models, and under‐utilized remote sensing data, it is critical to combine the available observations with a physically based model to better characterize the spatial and temporal variation of the GrIS SMB. This work proposes a data assimilation framework that yields SMB estimates that benefit from a state‐of‐the‐art snowpack model (Crocus) and a 16‐day albedo product. Comparison of our results against in‐situ SMB measurements from the Kangerlussuaq transect shows that assimilation of 16‐day albedo product reduces the root mean square error (RMSE) of the posterior estimates of SMB from 1240 millimeter water equivalent (mmWE/yr) to 230 mmWE/yr and reduces the bias from 1140 mmWE/yr to ‐20 mmWE/yr
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
Alexander, P.
Language :
English
Title :
Improving Greenland surface mass balance estimates through the assimilation of MODIS albedo: a case study along the K‐transect
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