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Assimilation of SMAP and ASCAT Soil Moisture Retrievals into the JULES Land Surface Model Using the Local Ensemble Transform Kalman FilterA land data assimilation system is developed to merge satellite soil moisture retrievals into the Joint U.K. Land Environment Simulator (JULES) land surface model (LSM) using the Local Ensemble Transform Kalman Filter (LETKF). The system assimilates microwave soil moisture retrievals from the Soil Moisture Active Passive (SMAP) radiometer and the Advanced Scatterometer (ASCAT) after bias correction based on cumulative distribution function fitting. The soil moisture assimilation estimates are evaluated with ground-based soil moisture measurements over the continental U.S. for five consecutive warm seasons (May–September of 2015–2019). The result shows that both SMAP and ASCAT retrievals improve the accuracy of soil moisture estimates. Especially, the SMAP single-sensor assimilation experiment shows the best performance with the increase of temporal anomaly correlation by ΔR ~ 0.05 for surface soil moisture and ΔR ~ 0.03 for root-zone soil moisture compared with the LSM simulation without satellite data assimilation. SMAP assimilation is more skillful than ASCAT assimilation primarily because of the greater skill of the assimilated SMAP retrievals compared to the ASCAT retrievals. The skill improvement also depends significantly on the region; the higher skill improvement in the western U.S. compared to the eastern U.S. is explained by the Kalman gain in the two experiments. Additionally, the regional skill differences in the single-sensor assimilation experiments are attributed to the number of assimilated observations. Finally, the soil moisture assimilation estimates provide more realistic land surface information than model-only simulations for the 2015 and the 2016 western U.S. droughts, suggesting the advantage of using satellite soil moisture retrievals in the current drought monitoring system.
Document ID
20205003830
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Eunkyo Seo
(Ulsan National Institute of Science and Technology Ulsan, South Korea)
Myong-In Lee
(Ulsan National Institute of Science and Technology Ulsan, South Korea)
Rolf H. Reichle
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Date Acquired
June 24, 2020
Publication Date
December 9, 2020
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier
Volume: 253
Issue Publication Date: February 1, 2021
ISSN: 0034-4257
Subject Category
Geosciences (General)
Funding Number(s)
WBS: 437949.02.03.01.79
CONTRACT_GRANT: KMI2018-03110
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
External Peer Committee
Keywords
SMAP
ASCAT
Soil Moisture
JULES
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