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Monthly Extended Predicting Experiments with Nonlinear Regional Prediction.PartⅠ:Prediction of Zonal Mean Flow
引用本文:陈伯民,纪立人,杨培才,张道民.Monthly Extended Predicting Experiments with Nonlinear Regional Prediction.PartⅠ:Prediction of Zonal Mean Flow[J].Acta Meteorologica Sinica,2006(3).
作者姓名:陈伯民  纪立人  杨培才  张道民
作者单位:Shanghai Climate Center Shanghai Meteorological Bureau,LASG Institute of Atmospheric Physics Chinese Academy of Sciences,LASG Institute of Atmospheric Physics,Chinese Academy of Sciences,LASG Institute of Atmospheric Physics,Chinese Academy of Sciences,Shanghai 200030 LASG,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,Beijing 100029,Beijing 100029,Beijing 100029
基金项目:Supported by the National Natural Science Foundation of China under Grant No. 40175013,the National Key Project for Development of Science and Technology (96-908-02-01),the Project of Chinese Academy of Sciences (ZKCX2-SW-210).
摘    要:Systematic errors have recently been founded to be distinct in the zonal mean component forecasts, which account for a large portion of the total monthly-mean forecast errors. To overcome the difficulty of numerical model, the monthly pentad-riean nonlinear dynamic regional prediction models of the zonal mean geopotential height at 200, 300, 500, and 700 hPa based on a large number of historical data (NCEP/NCAR reanalysis data) were constituted by employing the local approximation of the phase space reconstruction theory and nonlinear spatio-temporal series prediction method. The 12-month forecast experiments of 1996 indicated that the results of the nonlinear model are better than those of the persistent, climatic prediction, and T42L9 model either over the high- and mid-latitude areas of the Northern and Southern Hemispheres or the tropical area. The root-mean-square of the monthly-mean height of T42L9 model was considerably decreased with a change of 30.4%, 26.6%, 82.6%, and 39.4%, respectively, over the high- and mid-latitudes of the Northern Hemisphere, over the high- and mid-latitudes of the Southern Hemisphere, over the tropics and over the globe, and also the corresponding anomaly correlation coefficients over the four areas were respectively increased by 0.306-0.312, 0.304-0.429, 0.739-0.746, and 0.360-0.400 (averagely a relative change of 11.0% over the globe) by nonlinear correction after integration, implying that the forecasts given by nonlinear model include more useful information than those of T42L9 model.

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