基于准对称混合滑动训练期方法,对近两年来中国气象局陆面同化分析系统(CMA Land Data Assimilation System,CLDAS)输出的日最高气温、日最低气温网格实况分析产品进行订正,以期提高该产品在重庆地区的适用性.结果表明:订正前,2021年CLDAS日最高气温产品的平均误差为0.63℃,平均绝对误差为1.14℃,订正后平均误差减小至-0.03℃,平均绝对误差减小至0.64℃,误差小于或等于1℃的准确率由约64%提高到约90%,明显改善了该产品在重庆西部和东南部地区的适用性;订正前,2021年CLDAS日最低气温的平均误差为-0.22℃,平均绝对误差为0.75℃,订正后平均误差减小至-0.03℃,平均绝对误差减小至0.55℃,误差小于或等于1℃的准确率由约91%提高到约93%,改善了该产品在重庆中部地区的适用性.
Correction and evaluation of CLDAS air temperature products based on quasi-symmetric hybrid sliding training method
Based on the quasi-symmetric mixed sliding training period method,the grid analysis products of daily maximum tempera-ture and daily minimum temperature from Land Data Assimilation System of China Meteorological Administration(CLDAS)in recent two years are revised,in order to improve the applicability of the products in Chongqing.The results show that before revision,the aver-age error of daily maximum temperature products in 2021 was 0.63℃,and the average absolute error was 1.14℃.After revision,the average error decreased to-0.03℃,the average absolute error decreased to 0.64℃,the accuracy of error less than or equal to 1℃was improved from about 64%to 90%,which obviously improved the applicability of products in western and northeastern Chongqing.Be-fore revision,the average error of daily minimum temperature products in 2021 was-0.22℃,and the average absolute error was 0.75℃.After revision,the average error was reduced to-0.03℃,the average absolute error was reduced to 0.55℃,and the accuracy of error less than or equal to 1℃was improved from about 91%to 93%,which improved the applicability of products in central Chongqing.
NETL
NSTL
万方数据
