An approach to estimating and extrapolating model error based on inverse problem methods: towards accurate numerical weather prediction
查看参考文献37篇
文摘
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Model error is one of the key factors restricting the accuracy of numerical weather prediction (NWP). Considering the continuous evolution of the atmosphere, the observed data (ignoring the measurement error) can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers' equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP. |
来源
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Chinese Physics. B
,2014,23(8):089201-1-089201-9 【核心库】
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DOI
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10.1088/1674-1056/23/8/089201
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关键词
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numerical weather prediction
;
model error
;
past data
;
inverse problem
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地址
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1.
College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000
2.
School of Mathematics and Statistics, Lanzhou University, Lanzhou, 730000
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语种
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英文 |
文献类型
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研究性论文 |
ISSN
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1674-1056 |
学科
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物理学 |
基金
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supported by the Special Scientific Research Project for Public Interest
;
the Fundamental Research Funds for the Central Universities, China
;
国家973计划
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文献收藏号
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CSCD:5198263
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参考文献 共
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