Monthly 0.01° IMERG-Final dataset over Chinese mainland

Based on the relationship between precipitation and multi-geospatial factors, we proposed a new spatial downscaling approach named as gradient boosting decision tree (GBDT) to downscale the annual satellite precipitation estimates of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) from 0.1◦ to 0.01◦ gridded resolution over Mainland China (18°N-55°N, 72°E-136°E) from 2015 to 2018. Then, the 0.01°/yr IMERG dataset is disaggregated from annual precipitation into monthly values by using the disaggregation procedure proposed by Duan and Bastiaanssen. (2013). However, considering the huge amount of data, we substitute a weighting moving window for the spline tension interpolator in the disaggregation procedure.

Details on the dataset development and its assessment with ground observations are provided as:

Shen, Z., Yong, B., 2021. Downscaling the GPM-based satellite precipitation retrievals using gradient boosting decision tree approach over Mainland China. Journal of Hydrology, 602: 126803. DOI: 10.1016/j.jhydrol.2021.126803.