Articles | Volume 28, issue 24
https://doi.org/10.5194/hess-28-5401-2024
https://doi.org/10.5194/hess-28-5401-2024
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

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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.
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