摘要：CHIRPS-GEFS is an operational data set that provides daily bias-corrected forecasts for next 1-day to ~15-day precipitation totals and anomalies at a quasi-global 50-deg N to 50-deg S extent and 0 .05-degree resolution . These are based on National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System version 12 (GEFS v12) precipitation forecasts . CHIRPS-GEFS forecasts are compatible with Climate Hazards center InfraRed Precipitation with Stations (CHIRPS) data, which is actively used for drought monitoring, early warning, and near real-time impact assessments . A rank- based quantile matching procedure is used to transform GEFS v12 “reforecast” and “real-time” forecast ensemble means to CHIRPS spatial-temporal characteristics . Matching distributions to CHIRPS makes forecasts better refect local climatology at fner spatial resolution and reduces moderate-to-large forecast errors . As shown in this study, having a CHIRPS-compatible version of the latest generation of NCEP GEFS forecasts enables rapid assessment of current forecasts and local historical context . CHIRPS-GEFS efectively bridges the gap between observations and weather predictions, increasing the value of both by connecting monitoring resources (CHIRPS) with interoperable forecasts .
