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题名: Numerical model error estiamtion by derivative-free optimization method
其他题名: 基于无导数优化方法的数值模式误差估计
作者: Huang, QC; Hu, SJ(胡淑娟); Qiu, CY; Li, K; Yu, HP; Chou, JF(丑纪范)
收录类别: SCIE ; EI ; CSCD
出版日期: 2014-07
刊名: ACTA PHYSICA SINICA
卷号: 63, 期号:14, 页码:149203-1-149203-11
期刊主办单位: 中国物理学会
出版者: CHINESE PHYSICAL SOC
出版地: BEIJING
中文摘要: 初始场误差和模式误差是制约数值预报准确率的两个关键因素,本文主要考虑利用历史观测资料实现时空演变的模式误差的估计问题.通过把模式误差综合考虑成为准确模式中的未知项,把历史资料看作是带有未知项的准确模式的特解,构造了求解时空演变的模式误差项的反问题及其最优控制问题.给出了一个解决最优控制问题的无导数优化方法,该方法的优点是不需要建立原数值模式的切线性模式与伴随模式,它只需在增加一个外强迫项的基础上运行原数值模式即可实现模式误差项的最优估计.关于Burgers方程的算例表明,无论模式的初始状态是否准确已知,无导数优化方法都能有效解决时空演变的模式误差的最优估计问题,它为实际业务模式利用历史数据提取...
英文摘要: Initial error and model error are key factors restricting the accuracy of numerical weather prediction (NWP). The purpose of the present study is to estimate the errors of spatiotemporal evolution model by using recent observations. By considering the continuous evolution of atmosphere, the observed data (ignoring the measurement error) can be viewed as a series of solutions of accurate model governing the actual atmosphere, and the model errors can be objectively assumed to be an unknown functional term (a missing forcing term) of the numerical model, thus the NWP can be considered as an inverse problem to uncover the unknown model error term by using the long periods of observed data. In this study, we first construct an inverse problem model with its optimization problem, which is constrained by the numerical model, to estimate the errors of spatiotemporal evolution model, then we present a derivative-free optimization (DFO) method to find the minimum solution of the optimization problem by running the numerical model with an external forcing term. The DFO method does not need to compute the gradient of the objective functional and the tangent linear model or adjoint model of the original numerical model. The numerical study of Burgers equation indicates that the presented methods can effectively uncover the model errors from the past data and evidently improve the numerical prediction. The precedures described in this paper open up possibilities for utilizing the past observation data to extract useful information about model errors and enhance the prediction efficiency in the operational models.
关键词: model error ; past data ; inverse problem ; derivative-free optimization
作者部门: [Huang Qi-Can ; Hu Shu-Juan ; Qiu Chun-Yu ; Yu Hai-Peng ; Chou Ji-Fan] Lanzhou Univ, Coll Atmospher Sci, Lanzhou 730000, Peoples R China ; [Huang Qi-Can ; Qiu Chun-Yu ; Li Kuan] Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Peoples R China
通讯作者: Hu, SJ (reprint author), Lanzhou Univ, Coll Atmospher Sci, Lanzhou 730000, Peoples R China.
学科分类: Physics
文章类型: Article
所属项目编号: Special Scientific Research Project for Public Interest of China [GYHY201206009] ; Fundamental Research Funds for the Central Universities, China [lzujbky-2013-11] ; National Basic Research Program of China [2012CB955902, 2013CB430204]
所属项目名称: 国家重点基础研究发展计划以及国家重大科学研究计划(973计划) ; 公益性行业科研专项 ; 中央高校基本科研业务费专项资金
项目资助者: MOST ; LZU
语种: 中文
DOI: 10.7498/aps.63.149203
ISSN号: 1000-3290
WOS记录号: WOS:000340638900058
CSCD记录号: CSCD:5194234
EI记录号: 20143017985523
IR记录号: CNKI:0001935
第一机构:
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内容类型: 期刊论文
URI标识: http://ir.lzu.edu.cn/handle/262010/119429
Appears in Collections:大气科学学院_期刊论文

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Recommended Citation:
Huang, QC,Hu, SJ,Qiu, CY,et al. Numerical model error estiamtion by derivative-free optimization method[J]. ACTA PHYSICA SINICA/物理学报,2014,63(14):-.
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