Impact of Aerosols on Weather Forecasts in China During Winter 2016–2017

Abstract The China Meteorological Administration's mesoscale operational Global/Regional Assimilation and PrEdiction System (GRAPES_Meso5.1), coupled with the Chinese Unified Atmospheric Chemistry Environment (CUACE) model, has been enhanced to incorporate aerosol‐cloud‐radiation interactions, creating the CMA's first version of the chemistry‐weather integrated model, GRAPES_Meso5.1/CUACE CW V1.0. We applied this model to examine the impacts of aerosols on weather forecasts during the 2016–2017 winter season across China. Results indicate that incorporating aerosol feedbacks improves forecasts of temperature and precipitation, particularly in several regions. The most pronounced improvement in 72‐hr temperature forecasts occurred over the Beijing‐Tianjin‐Hebei (JJJ) region, where forecast errors were reduced by up to 30%. High cloud cover increased in the JJJ and Pearl River Delta regions. On a broader scale, the model reduced cumulative precipitation forecast errors by an average of 7.9–8.7 mm across China. While some of these improvements may fall within the range of internal atmospheric variability, the results suggest that aerosols can meaningfully influence convective and radiative processes relevant to short‐term weather prediction. These findings underscore the potential benefits of integrating prognostic aerosol processes into numerical weather prediction systems, particularly for improving forecast accuracy under high‐pollution conditions.