A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China
Data sets
Integrated Multi-satellitE Retrievals for GPM (IMERG) Technical Documentation https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/GPM_3IMERGDF.06/
GSMaP (Global Satellite Mapping of Precipitation) http://sharaku.eorc.jaxa.jp/GSMaP/index.htm
A quasi-global precipitation time series for drought monitoring https://data.chc.ucsb.edu/products/CHIRPS-2.0/
NOAA Climate Data Record (CDR) of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR), Version 1, Revision 1 https://www.ncei.noaa.gov/data/precipitation-persiann/access/
NOAA CPC Morphing Technique (CMORPH) Global Precipitation Analyses https://ftp.cpc.ncep.noaa.gov/precip/CMORPH_V1.0/CRT/
ERA5-Land monthly averaged data from 1950 to present https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.68d2bb30
NASA/GSFC/HSL, GLDAS Noah Land Surface Model L4 3 hourly 0.25x0.25 degree V2.1 https://doi.org/10.5067/E7TYRXPJKWOQ