华北地区极端温度MOS预报的季节划分

Seasonal Partition Problem of MOS Forecast for Extreme Temperature in North China

  • 摘要: 针对极端温度MOS (Model Output Statistics) 预报中的季节划分问题,通过聚类分析方法以华北地区为例进行试验,在此基础上提出一种新的MOS温度预报方程季节分类方式:2月11日—3月20日和11月5日—12月4日定义为早春晚秋类,5月1日—9月30日定义为夏季类,3月21日—4月30日和10月1日—11月4日定义为晚春早秋类,12月5日—2月10日定义为冬季类。由于上述季节分类与传统的季节划分在3—5月和9—11月时间段存在较大差异,因此利用2009年进行试报,就两种时间分类进行对比分析。检验结果表明:利用新分类方法制作的极端温度MOS预报的整体效果好于传统的季节划分得到MOS极端温度预报效果,说明新的分类方式更适合于极端温度MOS预报。

     

    Abstract: Aiming at seasonal partition problem of MOS (Model Output Statistics) forecast for extreme temperature, experiments are carried out in North China with cluster analysis method. A new seasonal partition way of MOS prediction equations for temperature is proposed on the basis of clustering results. The period from 11 February to 20 March and from 5 November to 4 December is defined as early spring and late autumn class; the period from 1 May to 30 September is defined as summer class; the period from 21 March to 30 April and from 1 October to 4 November is defined as late spring and early autumn class; the period from 5 December to 10 February is defined as winter class. The proposed seasonal partition is significantly different from traditional seasonal partition especially on periods of time from March to May and from September to November. The two kinds of seasonal partition definition are compared and analyzed. MOS prediction equations with new seasonal partition are founded by T213 model data, maximum and minimum temperature data of 154 stations in North China from 2003 to 2008, and verification of extreme temperature forecast in 2009 is conducted.Mean absolution error of maximum temperature forecast from September to November and minimum temperature forecast from March to May and from September to November made by new seasonal partition is less than that by traditional one. Using the new seasonal partition, there are more stations with the absolute error of MOS forecast less than 2℃ for maximum and minimum temperature from March to May and from September to November. Average error of extreme temperature forecast based on two kinds of seasonal partition ways doesn't have great differences, and their absolute error also isn't large at the same time. It shows that the system error is not significant. However, compared with traditional MOS forecast, mean absolute error of maximum temperature forecast made by new seasonal partition from March to May is larger. The cause maybe relates with great changes of temperature in spring of 2009 or cluster analysis program. More study and improvement will be carried out in order to solve the problem. The test result indicates that the overall effect of MOS forecast for maximum and minimum temperature made by new seasonal partition way is better than the traditional one, and shows that the new seasonal partition way is more suitable for MOS extreme temperature forecast.

     

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