Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 24
Articles | Volume 28, issue 24
https://doi.org/10.5194/hess-28-5401-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-5401-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 24
Research article
 | 
17 Dec 2024
Research article |  | 17 Dec 2024

Estimating global precipitation fields by interpolating rain gauge observations using the local ensemble transform Kalman filter and reanalysis precipitation

Yuka Muto and Shunji Kotsuki

Viewed

Total article views: 1,268 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,017 193 58 1,268 38 36
  • HTML: 1,017
  • PDF: 193
  • XML: 58
  • Total: 1,268
  • BibTeX: 38
  • EndNote: 36
Views and downloads (calculated since 23 Apr 2024)
Cumulative views and downloads (calculated since 23 Apr 2024)

Viewed (geographical distribution)

Total article views: 1,268 (including HTML, PDF, and XML) Thereof 1,228 with geography defined and 40 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 01 Apr 2025
Download
Short summary
It is crucial to improve global precipitation estimates to understand water-related disasters and water resources. This study proposes a new methodology to interpolate global precipitation fields from ground rain gauge observations using ensemble data assimilation and the precipitation of a numerical weather prediction model. Our estimates agree better with independent rain gauge observations than existing precipitation estimates, especially in mountainous or rain-gauge-sparse regions.
Read more
Share