GHCNdgp: an observation-based daily gridded precipitation dataset for forecast verification

The GHCNdgp is a daily gridded precipitation dataset for the period from 2020 to 2025 based on the station-based Global Historical Climatology Network (GHCN). Two daily datasets, i.e., the GHCN daily (GHCNd) and Global Surface Summary of the Day (GSOD), and three subdaily datasets, i.e., GHCN hourly (GHCNh), Integrated Surface Database (ISD) and Integrated Global Land surface Dataset (IGLD), are used to provide precipitation observations. Through multi-stage quality control checks including the reporting time match, observations of 58,796 stations are integrated to form the GHCNdgp dataset. To align with current AI weather forecasts, the precipitation observations are aggregated into gridded format with the spatial resolution of 0.25°×0.25°. The gridded precipitation values are derived from the daily observations of stations within each grid cell separately using arithmetic mean, simple inverse distance weighting (IDW) and ordinary point kriging. Accordingly, the GHCNdgp dataset provide separate daily gridded precipitation generated by these three methods. For easy extraction and utilization, the dataset is provided in the Network Common Data Form (NetCDF) format by years. The data variables include the daily precipitation by arithmetic mean (PRCP_mean), IDM (PRCP_IDM), ordinary point kriging (PRCP_Kriging), the standard deviation (PRCP_std) and the number of stations (Station_num) per grid cell. After decompression, it will occupy approximately 51GB of storage.