Articles | Volume 17, issue 23
https://doi.org/10.5194/gmd-17-8799-2024
https://doi.org/10.5194/gmd-17-8799-2024
Methods for assessment of models
 | 
11 Dec 2024
Methods for assessment of models |  | 11 Dec 2024

Assimilation of snow water equivalent from AMSR2 and IMS satellite data utilizing the local ensemble transform Kalman filter

Joonlee Lee, Myong-In Lee, Sunlae Tak, Eunkyo Seo, and Yong-Keun Lee

Data sets

IMS Snow Cover Data B. Ramsay https://noaadata.apps.nsidc.org/NOAA/G02156/

Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data R. D. Brown and B. Brasnett https://doi.org/10.5067/W9FOYWH0EQZ3

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Short summary
We developed an advanced snow water equivalent (SWE) data assimilation framework using satellite data based on a land surface model. The results of this study highlight the beneficial impact of data assimilation by effectively combining land surface model and satellite-derived data according to their relative uncertainty, thereby controlling not only transitional regions but also the regions with heavy snow accumulation that are difficult to detect by satellite.