基于动态最优PP法的乡镇温度预报技术

Forecasting Technology of township Temperature Based on Dynamic Optimal PP Method

利用2016年宁夏气象台县站温度预报数据和宁夏县级气象观测站、乡镇级自动观测站实况数据,采用训练择优、回归PP技术,建立动态最优PP法乡镇温度预报统计方法,检验该方法的温度预报效果,分析择优过程中的内部规律。研究表明:动态择优PP法对宁夏固原乡镇温度预报的质量评分明显高于旧指标法的乡镇预报质量评分,其中最低气温提高4.74%,最高气温提高8.20%;经过逐日动态最优方法选择的最佳样本长度,各县站、各月的出现频次并不完全相同,说明采用动态择优技术选择最佳样本长度是合适的;一年中最佳样本长度累计频次随着样本数的增加而呈对数下降,但依然有3、5、7、11、19、22等样本长度容易被选中为最佳;最佳样本长度间接反映了县与乡镇温度之间的关系存在周期性。

Based on temperature forecast values of county stations in Ningxia in 2016, the dynamic optimal PP method of township temperature forecast was established using dynamic, training optimal and PP method. The tests show that the quality score of PP method was significantly better than that of Ningxia township business forecast. The mimimum and maximum temperatures increased by 4.74% and 8.20%, respectively. The appearance frequency of optimal sample length selected by the dynamic optimal method was not exactly the same in different counties and in different months.Therefore, it was appropriate that the dynamic optimization techniques were used to select the optimal sample length.In one year, the accumulated frequency of optimal sample length decreased logarithmically with increasing number of samples, among them, 3, 5, 7, 11, 19, 22, etc. were easily selected as the optimal sample length. The optimal sample length reflected indirectly that the relationship between county temperature and township temperature was periodic.