A Thermodynamically Informed Precipitation Retrieval Method Based on FY‐4A/AGRI Multi‐Channel Infrared Observations Over Complex Terrain

Abstract Accurate precipitation monitoring is critical for hazard risk mitigation in regions characterized by complex terrain. To address these challenges, this study proposes a two‐stage framework that integrates thermodynamic controls, including cloud top brightness temperature (BT) from FengYun‐4A geostationary Multi‐Infrared observations And Orographic effects, for Precipitation retrieval (MIAO2Precip) over China's Sichuan Basin and its surrounding plateau regions at high spatio‐temporal resolutions (0.04°, 15 min). The main findings of this study are: (a) orographic effects (∼16%) contribute comparably to cloud top BT (∼19%) in precipitation retrieval, (b) accuracy of infrared‐based precipitation estimation is jointly influenced by cloud top BT and underlying topographic conditions, and (c) incorporating topography improves heavy precipitation detection (>10 mm/hr) with reduced root mean squared error, bias, and improved correlation coefficient, compared to benchmark products. The results highlight the proposed framework's enhanced capability in identifying heavy precipitation and its potential to support early warning systems in regions with complex topography.