任宏利,丑纪范. 2005. 统计-动力相结合的相似误差订正法[J]. 气象学报, 63(6):988-993, doi:10.11676/qxxb2005.094
统计-动力相结合的相似误差订正法
ANALOGUE CORRECTION METHOD OF ERRORS BY COMBINING BOTH STATISTICAL AND DYNAMIC AL METHODS TOGETHER
投稿时间:2005-01-21  修订日期:2005-05-26
DOI:10.11676/qxxb2005.094
中文关键词:  统计-动力相结合,反问题,数值预报,相似误差订正法
英文关键词:Combination of statistical and dynamical method, Inverse problem , Numerical prediction, Analogue correction method of errors.
基金项目:国家自然科学基金项目(40233031和40375025)
作者单位
任宏利 兰州大学大气科学学院兰州730000 
丑纪范 兰州大学大气科学学院兰州730000 
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中文摘要:
      根据大气相似性原理,提出了利用历史资料的相似信息估计模式误差的反问题,并发展了一 种相似误差订正(ACE)方法。该方法将统计和动力两种方法有机结合,在不改变现有数值预报模式的前提下,既充分利用了动力学发展的成就,又能够有效提取大量历史资料中的相似信息,达到减小模式误差、改进当前预报的目的。而且,ACE方法能够针对当前预报的特殊 性来区分所利用过去资料的特殊性,提取历史相似信息间接求解反问题。定性分析表明,AC E方法与以往相似 动力模式原理是等价的,但无需重新建立复杂的相似离差预报模式,更 具 可行性和业务应用前景。在理想化的极限情形下,当数值模式或历史相似完全准确时,ACE 方法的预报结果将分别蜕变为动力或统计学方法的预报结果。
英文摘要:
      Based on the atmospheric analogy principle, the inverse problem that the in formation of historical analogue data is utilized to estimate model errors is pu t forward and a method of Analogue Correction of model Errors (ACE) is developed . The ACE can combine effectively both statistical and dynamical metho d together, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasona bly extract the information of a lot of analogues in historical data in order to reduce model errors and improve forecast skill. urthermore, the ACE may identify specific historical data for the so lution of the inverse problem in terms of the particularity of current forecast. The qualitative analyse show that, the ACE is theoretically equivalent to the previous analogue-ynamical model principle, but need not rebuild the com p licated analogue-eviation model, so has better feasibility and operational for e ground. Moreover, under the ideal situations, when numerical models or historica l analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively.
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