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

Articles | Volume 25, issue 11

https://doi.org/10.5194/hess-25-5667-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

https://doi.org/10.5194/hess-25-5667-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 11

Research article

|

03 Nov 2021

Research article |

| 03 Nov 2021

Chuanfa Chen, Baojian Hu, and Yanyan Li

Data sets

Gauge data China Meteorological Data Service Center http://data.cma.cn/data/detail/dataCode/SURF_CLI_CHN_MUL_DAY_CES_V3.0.html

MOD13A3 data NASA Earth Data https://doi.org/10.5067/MODIS/mod13a3.006

MOD11A2 data NASA Earth Data https://doi.org/10.5067/MODIS/MOD11A2.006

SRTM Data CGIAR https://doi.org/10.5066/F7PR7TFT

Short summary

This study proposes an easy-to-use downscaling-calibration method based on a spatial random...