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Improving Greenland Surface Mass Balance Estimates Through the Assimilation of MODIS Albedo: A Case Study Along the K‐Transect
Author(s) -
Navari Mahdi,
Margulis Steven A.,
Tedesco Marco,
Fettweis Xavier,
Alexander Patrick M.
Publication year - 2018
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2018gl078448
Subject(s) - greenland ice sheet , environmental science , glacier mass balance , albedo (alchemy) , climatology , transect , data assimilation , snow , snowpack , atmospheric sciences , geology , ice sheet , physical geography , meteorology , oceanography , glacier , geography , art , geomorphology , performance art , art history
Estimating the Greenland ice sheet 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 underutilized 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 Greenland ice sheet 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 of the posterior estimates of SMB from 1,240 millimeter water equivalent per year (mmWE/yr) to 230 mmWE/yr and reduces the bias from 1,140 mmWE/yr to −20 mmWE/yr.