Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 30, issue 4
Articles | Volume 30, issue 4
https://doi.org/10.5194/hess-30-1261-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-1261-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 4
Research article
 | 
03 Mar 2026
Research article |  | 03 Mar 2026

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

Viewed

Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.

Total article views: 2,918 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,654 223 41 2,918 61 32 38
  • HTML: 2,654
  • PDF: 223
  • XML: 41
  • Total: 2,918
  • Supplement: 61
  • BibTeX: 32
  • EndNote: 38
Views and downloads (calculated since 30 Apr 2025)
Cumulative views and downloads (calculated since 30 Apr 2025)

Viewed (geographical distribution)

Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.

Total article views: 2,918 (including HTML, PDF, and XML) Thereof 2,857 with geography defined and 61 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 18 Aug 2026
Download
Short summary
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.
Read more
Share