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	A Study on the Reduction of Forecast Error Variance by Three Adaptive Observation Approaches for Tropical Cyclone Prediction
	Qin, Xiaohao2; Mu, Mu1
	2011-07-01
发表期刊	MONTHLY WEATHER REVIEW
ISSN	0027-0644
卷号	139期号:7页码:2218-2232
文章类型	Article
摘要	Three adaptive approaches for tropical cyclone prediction are compared in this study: the conditional nonlinear optimal perturbation (CNOP) method, the first singular vector (FSV) method, and the ensemble transform Kalman filter (ETKF) method. These approaches are compared for 36-h forecasts of three northwest Pacific tropical cyclones (TCs): Matsa (2005), Nock-Ten (2004), and Morakot (2009). The sensitive regions identified by each method are obtained. The CNOPs form an annulus around the storm at the targeting time, the FSV targets areas north of the storm, and the ETKF closely targets the typhoon location itself. The sensitive results of both the CNOPs and FSV collocate well with the steering flow between the subtropical high and the TCs. Furthermore, the regions where the convection is strong are targeted by the CNOPs. Relatively speaking, the ETKF sensitive results reflect the large-scale flow.; Three adaptive approaches for tropical cyclone prediction are compared in this study: the conditional nonlinear optimal perturbation (CNOP) method, the first singular vector (FSV) method, and the ensemble transform Kalman filter (ETKF) method. These approaches are compared for 36-h forecasts of three northwest Pacific tropical cyclones (TCs): Matsa (2005), Nock-Ten (2004), and Morakot (2009). The sensitive regions identified by each method are obtained. The CNOPs form an annulus around the storm at the targeting time, the FSV targets areas north of the storm, and the ETKF closely targets the typhoon location itself. The sensitive results of both the CNOPs and FSV collocate well with the steering flow between the subtropical high and the TCs. Furthermore, the regions where the convection is strong are targeted by the CNOPs. Relatively speaking, the ETKF sensitive results reflect the large-scale flow. To identify the most effective adaptive observational network, numerous probes or flights were tested arbitrarily for the ETKF method or according to the calculated sensitive regions of the CNOP and FSV methods. The results show that the sensitive regions identified by these three methods are more effective for adaptive observations than the other regions. In all three cases, the optimal adaptive observational network identified by the CNOP and ETKF methods results in similar forecast improvements in the verification region at the verification time, while the improvement using the FSV method is minor.
学科领域	Meteorology & Atmospheric Sciences
DOI	10.1175/2010MWR3327.1
URL	查看原文
收录类别	SCI
语种	英语
WOS记录号	WOS:000292723000013
引用统计	被引频次：39[WOS]   [WOS记录]     [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/11555
专题	海洋环流与波动重点实验室
作者单位	1.Chinese Acad Sci, Key Lab Ocean Circulat & Wave, Inst Oceanol, Qingdao 266071, Peoples R China 2.Chinese Acad Sci, Inst Atmospher Phys, LASG, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Qin, Xiaohao,Mu, Mu. A Study on the Reduction of Forecast Error Variance by Three Adaptive Observation Approaches for Tropical Cyclone Prediction[J]. MONTHLY WEATHER REVIEW,2011,139(7):2218-2232.
APA	Qin, Xiaohao,&Mu, Mu.(2011).A Study on the Reduction of Forecast Error Variance by Three Adaptive Observation Approaches for Tropical Cyclone Prediction.MONTHLY WEATHER REVIEW,139(7),2218-2232.
MLA	Qin, Xiaohao,et al."A Study on the Reduction of Forecast Error Variance by Three Adaptive Observation Approaches for Tropical Cyclone Prediction".MONTHLY WEATHER REVIEW 139.7(2011):2218-2232.

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