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Analogue Correction Method of Errors by Combining Statistical and Dynamical Methods

ISSN号：2095-6037
期刊名称：《气象学报：英文版》
时间：0
分类：P456.7[天文地球—大气科学及气象学]
作者机构：[1]Laboratory for Climate Studies, National Climate Center, China Meteorological Administration,Beijing 100081, [2]College of Atmospheric Sciences, Lanzhou University, Lanzhou 73000
相关基金：Supported jointly by the National Natural Science Foundation of China under Grant Nos. 40233031, 40575036 and 40675039. Acknowledgments. The authors thank Drs. Zhang Peiqun and Bao Ming very much for their valuable comments and help on the present paper.

关键词：反转法, 数值预报, 天气预报, 动力模型, 偏差, combination of statistical and dynamical methods, inverse problem, numerical prediction,analogue correction of errors （ACE）

中文摘要：

基于大气的类比原则，历史的类似物数据的信息被利用估计模型错误被提出的反的问题和模型的错误(王牌) 的类比法修正在这篇论文被开发。王牌能联合有效地统计、动态的方法，并且不必改变当前的数字预言模型。新方法不仅足够地相当利用动态成就而且罐头专心于许多类似物的信息历史的数据以便减少模型错误并且改善预报技巧。而且， ACE 可以以当前的预报的个性为反的问题的答案识别特定的历史的数据。Thequalitative 分析证明 ACE 理论上等价于 previousanalogue 动态的模型的原则，但是不必重建复杂类似物偏差模型，更好的可行性和运作的前景也一样。而且在理想的状况下面，当数字模型或历史的类似物是完美的时， ACE 的预报将转变成预报动态或统计法分别地。

英文摘要：

Based on the atmospheric analogy principle, the inverse problem that the information of historical analogue data is utilized to estimate model errors is put forward and a method of analogue correction of errors （ACE） of model is developed in this paper. The ACE can combine effectively statistical and dynamical methods, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasonably absorb the information of a great many analogues in historical data in order to reduce model errors and improve forecast skill. Purthermore, the ACE may identify specific historical data for the solution of the inverse problem in terms of the particularity of current forecast. The qualitative analyses show that the ACE is theoretically equivalent to the principle of the previous analogue-dynamical model, but need not rebuild the complicated analogue-deviation model, so has better feasibility and operational foreground. Moreover, under the ideal situations, when numerical models or historical analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively.

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