Evaluation and Verification of Precipitation Forecast by Cloud Models CPEFS and CMA-GD in Guangdong Region
Abstract：To enhance the understanding of numerical model forecast performance among artificial weather modification staff, based on the precipitation field forecast products of two cloud models, CMA-GD and CPEFS, combined with ground precipitation observation data, a quantitative comparison and verification were conducted for the 24-hour precipitation forecasts at 86 national stations in Guangdong Province and 15 major precipitation processes from 2022 to 2023. The results showed that: (1) The average absolute errors of 24-hour precipitation forecasts for the entire province by CPEFS and CMA-GD were 2.3 mm and 2.2 mm, respectively, with root mean square errors of approximately 4.1 mm and determination coefficient scores of about 0.78. Overall, the forecast errors and accuracy of the two cloud models were similar, with good forecasting performance, especially CMA-GD showing better results. (2) The rain-sun accuracy rate and general precipitation TS score of CMA-GD were generally better than those of CPEFS, with a lower false negative rate. Both cloud models performed better in August. (3) The forecasting performance of both cloud models for general precipitation in western Guangdong was slightly worse, while the differences in other regions were not significant. Among them, the general precipitation TS score of CMA-GD was higher than that of CPEFS in various cities. (4) Both cloud models had strong forecasting capabilities for precipitation under typhoon weather types, but their TS scores for precipitation under upper-level troughs, shear lines, and monsoon weather types were relatively low.
Keywords：Weather ForecastingCloud ModelCPEFS ModelCMA-GD ModelPrecipitation ForecastingGuangdong
Publication Date：2025-06-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 49-52 )