globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2015MS000607
Scopus记录号: 2-s2.0-84963595148
论文题名:
Statistical-dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high-resolution GFDL FLOR coupled model
作者: Zhang W; , Villarini G; , Vecchi G; A; , Murakami H; , Gudgel R
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2016
卷: 8, 期:2
起始页码: 538
结束页码: 565
语种: 英语
英文关键词: Atmospheric temperature ; Cluster analysis ; Hurricanes ; Oceanography ; Regression analysis ; Storms ; Surface waters ; Tropics ; Geophysical fluid dynamics laboratories ; GFDL FLOR ; Landfall ; Landfalling tropical cyclones ; Poisson regression models ; Sea surface temperature (SST) ; Tropical cyclone ; Western North Pacific ; Forecasting ; climate prediction ; cluster analysis ; fluid dynamics ; flux measurement ; landslide ; numerical model ; regression analysis ; resolution ; seasonal variation ; tropical cyclone ; weather forecasting ; Far East ; Pacific Ocean ; Pacific Ocean (North)
英文摘要: This study examines the seasonal prediction of western North Pacific [WNP) and East Asia landfalling tropical cyclones (TCs) using the Geophysical Fluid Dynamics Laboratory(GFDL) Forecast-oriented Low Ocean Resolution version of CM2.5 with Flux Adjustment (FLOR-FA) and finite-mixture-model (FMM)-based statistical cluster analysis. Using the FMM-based cluster analysis, seven clusters are identified from the historical and FLOR-FA-predicted TC tracks for the period 1980–2013. FLOR-FA has significant skill in predicting year-to-year variations in the frequency of TCs within clusters 1 (recurving TCs) and 5 (straight-moving TCs). By building Poisson regression models for each cluster using key predictors (i.e., sea surface temperature, 500 hPa geopotential height, and zonal vertical wind shear), the predictive skill for almost all the clusters at all initialization months improves with respect to the dynamic prediction. The prediction of total WNP TC frequency made by combining hybrid predictions for each of the seven clusters in the hybrid model shows skill higher than what achieved using the TC frequency directly from FLOR-FA initialized from March to July. However, the hybrid predictions for total WNP TC frequency initialized from January to February exhibit lower skill than FLOR-FA. The prediction of TC landfall over East Asia made by combining the hybrid models of TC frequency in each cluster and its landfall rate over East Asia also outperforms FLOR-FA for all initialization months January through July. © 2016. The Authors.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75899
Appears in Collections:影响、适应和脆弱性
气候变化与战略

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作者单位: National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States; Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ, United States; Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and TechnologyNanjing, China; IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, IA, United States

Recommended Citation:
Zhang W,, Villarini G,, Vecchi G,et al. Statistical-dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high-resolution GFDL FLOR coupled model[J]. Journal of Advances in Modeling Earth Systems,2016-01-01,8(2)
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