Improving FY‐4A/AGRI BT Simulations Over Rugged Areas via Enhanced Solar Radiative Effects in WRF

Abstract Effective assimilation of satellite land surface‐sensitive infrared brightness temperature (BT) depends critically on accurate background land surface temperature (LST), which is closely linked to surface downward solar radiation () simulations. However, current numerical models often neglect topographic effects on , producing significant biases over rugged terrain and consequently degrading modeled LST. This study aims to improve FY‐4A/Advanced Geosynchronous Radiation Imager clear‐sky surface‐sensitive infrared BT simulations by enhancing the representation of and LST over mountainous regions. To this end, a three‐dimensional sub‐grid terrain solar radiative effect scheme (3DSTSRE) is incorporated into the Weather Research and Forecasting model. The analysis focuses on areas spanning the southeastern Tibetan Plateau and Sichuan Basin. Results show that 3DSTSRE substantially mitigates terrain‐dependent overestimation, decreasing regional‐mean bias by 76.86% from 22.08 to 5.11 Wm −2 , with larger improvements over rugged terrain with sky view factor (SVF) less than 0.90. Correspondingly, clear‐sky LST overestimation is effectively alleviated, with the bias reduced by 61.18% (1.70°C–0.66°C) over SVF ≤ 0.90 regions. These improvements occur primarily during daytime hours (08:00–18:00 Beijing Time). Consequently, terrain‐dependent clear‐sky BT overestimations for FY‐4A/AGRI channels 11–13 are markedly reduced. Over rugged terrain, the daytime negative BT observation‐minus‐background biases decrease by 60.53%, 54.96%, and 51.26%, from −1.14, −1.31, and −1.19 K to −0.45, −0.59, and −0.58 K, respectively. The findings highlight the value of incorporating 3DSTSRE into numerical models to improve and LST simulations, thereby reducing terrain‐induced BT biases and benefiting the assimilation of surface‐sensitive infrared observations over rugged terrain.