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Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface modelThis second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domainscale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospherichydrological process within a land surface model for use in HMA.
Document ID
20220009580
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Yuan Xue ORCID
(George Mason University Fairfax, Virginia, United States)
Paul R. Houser
(George Mason University Fairfax, Virginia, United States)
Viviana Maggioni
(George Mason University Fairfax, Virginia, United States)
Yiwen Mei ORCID
(George Mason University Fairfax, Virginia, United States)
Sujay V. Kumar ORCID
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Yeosang Yoon ORCID
(Science Applications International Corporation (United States) McLean, Virginia, United States)
Date Acquired
June 21, 2022
Publication Date
March 26, 2022
Publication Information
Publication: Journal of Geophysical Research: Atmospheres
Publisher: American Geophysical Union/Wiley Open Access
Volume: 127
Issue: 7
Issue Publication Date: April 16, 2022
ISSN: 2169-897X
e-ISSN: 2169-8996
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
WBS: 430728.02.80.01.14 
CONTRACT_GRANT: 80GSFC20C0044
CONTRACT_GRANT: NNX17AB28G
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
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