Development of a Stratospheric Module Based on the CUACE and Preliminary Application to the Global Numerical Weather Prediction Model System GRAEPES_GFS3.0

Abstract Human‐induced changes in atmospheric composition, particularly from aerosols and ozone pollution, significantly impact weather forecasting. Establishing a chemical weather model is essential to more accurately and effectively account for these effects. The stratosphere serves as primary ozone reservoir, but the Chinese Unified Atmospheric Chemistry Environment (CUACE) model lacks a dedicated stratospheric module, limiting accurate simulation of stratospheric ozone variability. Therefore, a stratospheric module is developed within CUACE and coupled online to the global weather prediction model, forming a novel global chemical weather (GCW) model. Critical technical advancements in parallel computation acceleration, optimized array conversion, precision interpolation, stratospheric boundary definition, and standardized unit conversion collectively enhance forecasting timeliness and stability. Benchmarked against reanalysis data, the GCW model successfully captures stratospheric ozone spatial distribution ( R 2 = 0.64–0.90), with radiative feedback implementation reducing stratospheric temperature prediction biases by 1.8–5.4 K. The newly established GCW model enhances environmental forecasts and climate resilience strategies.