Abstract：Using the daily highest and lowest temperature data from 15 representative stations in Xiushui County from January 1, 2018 to May 22, 2022, as well as the high and low temperature forecast data from Jiangxi Province, s intelligent grid forecasting system, CMA-GFS, CMA-SH9, ECMWF, JMA and other models, and analyzing the forecast errors of each model, a multi-mode integrated correction method based on the average absolute error weight was used to correct the 24-hour and 48-hour high and low temperature forecasts.The results indicate that the error weight based correction method is applicable to the vast majority of stations and has a good correction effect on the minimum temperature.The correction effect of the 24-hour minimum temperature at 13 station is better than other models, among which the accuracy of the forecast at Xikou station is 5.9％ better than that of the CMA-SH9 model.The correction effect of the lowest temperature at 10 tations within 48 hours is better than other models, among which the accuracy of Xikou station, s forecast is better than that of CMA-SH9 model by 10.19％.The correction effect of the highest temperature is better than that of the lowest temperature, and the correction effect of the 24-hour higest temperature at 14 stations is better than other models.Among them, the accuracy of Huanggang Station, s forecast is better than that of Jiangxi Province, s intelligent grid forecasting system, accounting for 21.45％;The correction effect of the highest temperature at all station within 48 hours is better than other models, among which the accuracy of the forecast at Yuduan Station is 23.05% higher than that of the Jiangxi Province Intelligent Grid Forecast System.
周山华. 基于误差权重的乡镇温度订正预报研究[J]. 气象水文海洋仪器, 2024, 41(4): 37-40.
Zhou Shanhua. Study on revised forecast method of station temperature based on error weight. Meteorological Hydrological and Marine Instrument, 2024, 41(4): 37-40.
2024, Vol. 41 
