Performance of high-resolution precipitation products in capturing sub-daily spatial-temporal evolution of the recent record-breaking rainfall events in Chinese cities

This repository contains the datasets and code (R language) used in the study evaluating the spatial-temporal performance of seven high-resolution precipitation products (CMORPH, GPM, PERSIANN, PERSIANN-CCS, ERA5 single-level, ERA5-Land, and MSWEP) in capturing record-breaking extreme rainfall events (REREs). The analysis covers sub-daily (30 minutes to 3 hours) temporal scales and fine spatial resolutions (0.04° to 0.25°), focusing on four cities with varying climatic conditions (e.g., Beijing, Longnan, Zhengzhou, and Hong Kong). Key findings reveal that CMORPH, GPM, and MSWEP generally outperform other datasets, though all show limitations in accurately representing storm center dynamics and rainfall duration. The performance of these precipitation products strongly depends on rainfall intensity, spatial patterns, and regional climate characteristics. This data and code release supports reproducibility and further research on selecting appropriate precipitation datasets for extreme rainfall event analysis.