| The Sensitive Regions Identified by CNOPs of Three Typhoon Events |
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| 作者姓名： | QIN Xiao-Hao |
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| 作者单位： | 中国科学院大气物理研究所 |
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| 基金项目： | sponsored by the National Natural Science Foundation of China (Grant Nos. 40830955 and 40821092);the Project of China Meteorological Administration (Grant No. GYHY200906009) |
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| 摘 要： | In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.
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| 关 键 词： | adaptive observations conditional nonlinear optimal perturbation sensitive regions Observing system simulation experiments typhoon forecast |
The Sensitive Regions Identified by CNOPs of Three Typhoon Events |
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| Authors: | QIN Xiao-Hao |
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| Institution: | 1. The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts. |
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| Keywords: | adaptive observations conditional nonlinear optimal perturbation sensitive regions Observing system simulation experiments typhoon forecast |
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