基于CMA_GFS模式的海南州气温客观预报订正方法研究

Study on Correction Method of Objective Temperature Forecast in Hainan Prefecture Based on CMA_GFS

基于CMA_GFS模式逐3小时温度预报产品和海南州共和、贵德、兴海、贵南、同德五个国家观测站地面观测数据,利用动态滑动双权重订正方法,选取10天、15天、20天3个不同滑动周期,分别对海南地区范围24 h时效内逐3 h气温进行订正,形成三种不同动态滑动周期下的气温客观预报订正产品。以2020年7月~2021年12月的预报为训练样本,选取2021年1月~2021年12月的数据对客观订正产品进行检验,结果如下:(1)三种周期的订正产品全年平均准确率均高于CMA_GFS,相对而言08时起报的10天滑动平均产品对海南地区五个站点的预报准确率最高。(2)空间误差结果看出订正产品对贵德站的预报订正效果最佳;三种订正方法中10天滑动平均产品的平均误差最小。(3)08时起报的10天滑动平均产品最优,本地产品对模式逐3 h温度预报有正技巧,其中对贵德站预报订正效果最佳。研究结果可以在气温预报业务中应用,能够进一步提高本地气温预报准确率。

Based on the 3-hour temperature forecast products of CMA_GFS model and the ground observation data of Gonghe,Guide,Xinghai,Guinan and Tongde observatories in Hainan,using dynamic sliding double weight correction method,three different sliding periods of 10 days,15 days and 20 days were selected to correct the temperature in Hainan area within 24 hours one by one,and the revised products of objective temperature forecast under three different dynamic sliding periods were formed.Taking the forecast from July 2020 to December 2021 as training samples,the data from January 2021 to December 2021 are selected to test the objective revised products.The results are as follows:(1)The annual average accuracy of the revised products in three periods is higher than that of CMA_GFS,and the 10-day moving average products reported from 08:00 have the highest forecast accuracy for five stations in Hainan.(2)Spatial error results show that the revised product has the best forecast correction effect on Guide Station.Among the three correction methods,the average error of 10-day moving average products is the smallest.(3)The 10-day moving average from 08:00 is the best,and the local products have positive skills for the model temperature forecast every 3 hours,among which the forecast correction effect for Guide Station is the best.The research results can be applied in the temperature forecast business and can further improve the accuracy of local temperature forecast.