| 在数值预报中应用卫星反演资料的质量控制研究 |
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| 引用本文： | 李华宏,沈桐立,王曼.在数值预报中应用卫星反演资料的质量控制研究[J].南京气象学院学报,2003,26(6):749-758. |
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| 作者姓名： | 李华宏 沈桐立 王曼 |
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| 作者单位： | 南京气象学院,气象灾害和环境变化重点开放实验室,江苏,南京,210044 |
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| 基金项目： | 国家自然科学基金资助项目(40075023);国家重点基础发展规划项目(G1998040910) |
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| 摘 要： | 资料变分同化作为提高数值预报准确率的有效手段之一，受到了越来越多的关注。如何将分辨率较高的卫星资料应用到数值预报中，弥补常规观测网时空分辨率的不足，成为数值天气预报的重要课题。以1996年6月28-29日发生在江淮流域的暴雨过程为例，依据其中尺度场和能量场特征，分别以低云量、急流、湿静力能为标准设计了三套质量控制方案。将质量控制后的反演湿度场变分同化并应用到中尺度MM5模式中，结果表明：经质量控制后，可以明显地改善降水区域及降水量的预报；对降水预报，特别是强降水天气过程的预报，该质量控制方案具有普遍意义。
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| 关 键 词： | 数值预报 卫星资料 质量控制 资料变分同化 |
| 文章编号： | 1000-2022(2003)06-0749-10 |
| 修稿时间： | 2003年1月3日 |
A Study on Quality Control of Satellite Retrieved Data in Numerical Weather Prediction |
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| LI Hua-hong,SHEN Tong-li,WANG Manal Variation,NIM,Nanjing,China.A Study on Quality Control of Satellite Retrieved Data in Numerical Weather Prediction[J].Journal of Nanjing Institute of Meteorology,2003,26(6):749-758. |
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| Authors: | LI Hua-hong SHEN Tong-li WANG Manal Variation NIM Nanjing China |
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| Institution: | LI Hua-hong,SHEN Tong-li,WANG Manal Variation,NIM,Nanjing210044,China) |
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| Abstract: | As an efficient approach to improve the accuracy of numerical weather prediction (NWP),data assimilation has been received more and more attention.The application of high resolution satellite data to compensate the deficiencies of spatial and temporal resolution in conventional observations in NWP becomes a key subject in this field.As a case,a heavy rainfall process during 28-29 June 1996 occurring in Yangtze-Huaihe river basin is studied with MM5 model.According to the features of physical and energy fields,three sets of quality controlling schemes are designed based on low cloud amount,low level jet and wet static energy respectively.The retrieved relative humidity fields after quality controlling and variational assimilation are used in MM5 model.It is found that the quality controlling improve the prediction of the region and amount of the rainfall greatly.The three quality controlling schemes are effective for rainfall forecast,especially the heavy rainfall. |
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| Keywords: | satellite data variational assimilation quality control |
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