Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5667-2021
https://doi.org/10.5194/hess-25-5667-2021
Research article
 | 
03 Nov 2021
Research article |  | 03 Nov 2021

Easy-to-use spatial random-forest-based downscaling-calibration method for producing precipitation data with high resolution and high accuracy

Chuanfa Chen, Baojian Hu, and Yanyan Li

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Latest update: 18 Jul 2024
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Short summary
This study proposes an easy-to-use downscaling-calibration method based on a spatial random forest with the incorporation of high-resolution variables. The proposed method is general, robust, accurate and easy to use as it shows more accurate results than the classical methods in the study area with heterogeneous terrain morphology and precipitation. It can be easily applied to other regions where precipitation data with high resolution and high accuracy are urgently required.