On improving tropical cyclone track forecasts using a scale-selective data assimilation approach: a case study
Lai, ZJ; Hao, S; Peng, SQ; Liu, B; Gu, XQ; Qian, YK; speng@scsio.ac.cn
2014
发表期刊NATURAL HAZARDS
ISSN0921-030X
卷号73期号:3页码:1353-1368
摘要A dynamical downscaling approach based on scale-selective data assimilation (SSDA) is applied to tropical cyclone (TC) track forecasts. The results from a case study of super Typhoon Megi (2010) show that the SSDA approach is very effective in improving the TC track forecasts by fitting the large-scale wind field from the regional model to that from the global forecast system (GFS) forecasts while allowing the small-scale circulation to develop freely in the regional model. A comparison to the conventional spectral-nudging four-dimensional data assimilation (FDDA) indicates that the SSDA approach outperforms the FDDA in TC track forecasts because the former allows the small-scale features in a regional model to develop more freely than the latter due to different techniques used. In addition, a number of numerical experiments are performed to investigate the sensitivity of SSDA's effect in TC track forecasts to some parameters in SSDA, including the cutoff wave number, the vertical layers of the atmosphere being adjusted, and the interval of SSDA implementation. The results show that the improvements are sensitive in different extent to the above three parameters.
部门归属[Lai, Zhijuan ; Peng, Shiqiu ; Qian, Yu-Kun] Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou 510301, Guangdong, Peoples R China ; [Lai, Zhijuan ; Hao, Sai] Univ Chinese Acad Sci, Beijing 100049, Peoples R China ; [Hao, Sai] Chinese Acad Sci, Inst Atmospher Phys, LASG, Beijing 100029, Peoples R China ; [Liu, Bei] Guangdong Ocean Univ, Inst Ocean & Meteorol, Zhanjiang 524088, Peoples R China ; [Gu, Xiangqian] Chinese Acad Meteorol Sci, State Key Lab Sever Weather, Beijing 100081, Peoples R China
关键词Tropical Cyclone (Tc) Track Forecast Scale-selective Data Assimilation (Ssda) Improvement Sensitivity
学科领域Geology ; Meteorology & Atmospheric Sciences ; Water Resources
资助者Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences ; Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences ; Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences ; Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences
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收录类别sci
资助项目LTO
资助者Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences ; Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences ; Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences ; Innovation Key Program of the Chinese Academy of Sciences [KZCX2-EW-208]; Ministry of Science and Technology of the People's Republic of China (MOST) [2011CB403505]; National Natural Science Foundation of China [41076009, 41075080]; Hundred Talent Program of the Chinese Academy of Sciences
WOS记录号WOS:000340492700011
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.scsio.ac.cn/handle/344004/10512
专题热带海洋环境国家重点实验室(LTO)
通讯作者speng@scsio.ac.cn
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GB/T 7714
Lai, ZJ,Hao, S,Peng, SQ,et al. On improving tropical cyclone track forecasts using a scale-selective data assimilation approach: a case study[J]. NATURAL HAZARDS,2014,73(3):1353-1368.
APA Lai, ZJ.,Hao, S.,Peng, SQ.,Liu, B.,Gu, XQ.,...&speng@scsio.ac.cn.(2014).On improving tropical cyclone track forecasts using a scale-selective data assimilation approach: a case study.NATURAL HAZARDS,73(3),1353-1368.
MLA Lai, ZJ,et al."On improving tropical cyclone track forecasts using a scale-selective data assimilation approach: a case study".NATURAL HAZARDS 73.3(2014):1353-1368.
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