基于年际增量方法的云南省普洱雨季开始期气候预测
投稿时间:2018-12-30  修订日期:2019-03-02  点此下载全文
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作者单位E-mail
王秀英 普洱市气象局 410518631@qq.com 
田宝强 中国科学院大气物理研究所 tianbq@mail.iap.ac.cn 
范可 中国科学院大气物理研究所  
基金项目:公益性行业(气象)科研重大专项“干旱气象科学研究--我国北方干旱致灾过程及机理”GYHY (QX) 201506001,国家自然科学基金(41605053),云南省普洱市气象局李崇银院士工作站(2018IC150),贵州省科技厅项目[黔科合支撑2017(2593)
中文摘要:普洱位于云南西南部,其雨季开始期的早晚对西南农作物和茶叶产量影响非常大。本文采用年际增量的方法,基于普洱雨季开始期年际增量变化规律和影响雨季开始期的环流形势及物理过程,利用多元线性回归分析建立雨季开始期预测模型。选取了5个具有物理意义的预测因子,包括前期1月南半球绕极环流、前期2月南太平洋高压、前期4月孟加拉湾至南海海平面气压、前期冬季加拿大北部海冰和前期冬季伊朗高原积雪深度,来建立普洱雨季开始期的预测模型。并对预测模型进行1967~2017年(51年)的交叉检验和1998~2017年逐年独立样本检验。交叉检验中雨季开始期预测值和观测值年际增量的相关系数为0.84,相对均方根误差为24%。独立样本检验中,雨季开始期年际增量的相对均方根误差为15%,模型对雨季开始期异常年份预测误差小于7 d,能够很好的再现1967~2017年的变化趋势。
中文关键词:年际增量方法 云南普洱雨季开始期 气候预测
 
Climatic prediction for the onset of the rainy season in Puer city of Yunnan province based on the method of the year-to-year increment
Abstract:As Pu'er is located in Southwest in Yunnan, the onset of summer rainfall is very important for the crop and tea production. Based on the method of the year-to-year increment, and then by predicting the year-to-year increment of the onset of the rainy season that can be predicted in Pu'er. Firstly, it is indispensable that analyses the changes and physical process affected of year-to-year increment about the onset of the rainy season and atmospheric circulation. The prediction model is established based on the method of multiple linear regression analysis. Five predictors include the anomaly of the southern hemisphere circumpolar circulation in January, the south Pacific high in February, the sea level pressure of bay of Bengal to the south China sea, the previous winter sea ice in northern Canada, and the previous winter snow depth on the Iranian plateau. Using the above five predictors, the prediction model about the onset of the rainy season can be established. In addition, the prediction model is not only crossing-test verification about independent-samples during 1965 to 2017, but also prediction test verification during 1998 to 2017. In the crossing-test verification, the correlation coefficients of the interannual increment between predictand and observation of the onset of the rainy season is 0.84, and the root mean square relative error is 24%. In the prediction test verification, the root mean square relative error of is only 15%. The prediction model makes good predictions about the onset of the rainy season anomaly, and the prediction error is less than 7 d. The prediction model can reproduce the change trend from 1967 to 2017.
keywords:the year-to-year increment, the onset of the rainy season in Puer city of Yunnan province, climatic prediction
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