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基于增长模繁殖法的集合预报试验
引用本文:关吉平,张立凤.基于增长模繁殖法的集合预报试验[J].气象科学,2006,26(3):272-278.
作者姓名:关吉平  张立凤
作者单位:1. 解放军理工大学气象学院,南京,211101
2. 解放军理工大学气象学院,南京,211101;中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室,北京,100029
基金项目:国家研究发展基金;国家重点实验室基金
摘    要:利用微机版本的T63L9全球谱模式,首先进行了用增长模繁殖法(BGM)制作集合预报的方案设计,然后用确定的方案进行了中期数值预报的集合预报试验。繁殖循环的初始扰动为T63L9谱模式各层24 h预报的均方根误差乘随机数,该随机数服从-1, 1]区间上的均匀分布,繁殖循环每12 h 1次,繁殖循环的周期为3 d,集合成员为9个。结果表明:在1~8 d的预报中,集合预报可以比控制预报的时效延长1 d,集合预报无论是距平相关系数还是预报均方根误差都明显优于控制预报,集合预报对形势场的预报较控制预报更为接近实况分析场。

关 键 词:中期数值预报  集合预报  增长模繁殖法
收稿时间:2004-11-08
修稿时间:2005-04-06

ENSEMBLE FORECASTING EXPERIMENTS BASED ON THE BGM METHOD
Guan Jiping and Zhang Lifeng.ENSEMBLE FORECASTING EXPERIMENTS BASED ON THE BGM METHOD[J].Scientia Meteorologica Sinica,2006,26(3):272-278.
Authors:Guan Jiping and Zhang Lifeng
Institution:1.Meteorological College, PLA University of Science and Technology, Nanjing 211101 ;2.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics ,Beijing 100029
Abstract:Firstly,a scheme of ensemble forecasting using the method of breeding of growing mode(BGM) is designed,using the global spectral model T63L9 based on microcomputer.Secondly,some experiments of ensemble forecast about medium-range numerical forecasting are done using the scheme.The first day's forecasting error of the model times random number is regarded as the initial disturbance of the breeding cycles and these random numbers meet uniform distribution between 1 and 1.The breeding period is 12h,so twice one day,the total time of breeding is 3 days and the number of ensemble members is 9.Ensemble forecast is made by the equivalent weight average with 9 members.Results show that from the 1st day to 8th day's forecasting,the forecast term from ensemble forecasting is one day longer than that from control forecast.Within 8 days,whether for anomaly correlation coefficient or forecasting rmse error,the ensemble forecasting is better than control forecasting and the posture field from ensemble forecasting is more similar to analysis field than that from control forecast.
Keywords:Medium-range numerical forecasting Ensemble forecasting Method of breeding of growing mode
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