Synergistic impact of simultaneously assimilating radar- and radiometer-based soil moisture retrievals on the performance of numerical weather prediction systems
Yonghwan Kwon,Sanghee Jun,Hyunglok Kim,Kyung-Hee Seol,In-Hyuk Kwon,Eunkyu Kim,and Sujeong Cho
Department of Environment and Energy Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, South Korea
Kyung-Hee Seol
Korea Institute of Atmospheric Prediction Systems, Seoul 07071, South Korea
In-Hyuk Kwon
Korea Institute of Atmospheric Prediction Systems, Seoul 07071, South Korea
Eunkyu Kim
Korea Institute of Atmospheric Prediction Systems, Seoul 07071, South Korea
Sujeong Cho
Korea Institute of Atmospheric Prediction Systems, Seoul 07071, South Korea
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This study investigates how combining satellite soil moisture data from radar and radiometer measurements influences weather forecasts in the Korean Integrated Model. Using a weakly coupled data assimilation approach—where atmospheric and land observations are separately assimilated for their respective variables—we found that assimilating both types of soil moisture data together improves forecasts of humidity, temperature, and rainfall compared to using data from a single sensor.
This study investigates how combining satellite soil moisture data from radar and radiometer...