Statistical‐dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high‐resolution GFDL FLOR coupled model

Wei Zhang; Gabriele Villarini; Gabriel A Vecchi; Hiroyuki Murakami; Richard Gudgel

doi:10.1002/2015MS000607

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Statistical‐dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high‐resolution GFDL FLOR coupled model

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Statistical‐dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high‐resolution GFDL FLOR coupled model

Wei Zhang, Gabriele Villarini, Gabriel A Vecchi, Hiroyuki Murakami and Richard Gudgel

Journal of Advances in Modeling Earth Systems, Vol.8(2), pp.538-565

06/2016

DOI: 10.1002/2015MS000607

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Abstract

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. Key Points: Seven clusters are identified from the historical and predicted TC tracks for the period 1980–2013 The prediction of WNP TC frequency shows skill higher than FLOR‐FA in most of initialization months The prediction of TC landfall with hybrid models outperforms FLOR‐FA for all initialization months

tropical cyclone

western North Pacific

GFDL FLOR

landfall

Details

Title: Subtitle: Statistical‐dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high‐resolution GFDL FLOR coupled model
Creators: Wei Zhang - Ministry of Education, Nanjing University of Information Science and Technology
Gabriele Villarini - University of Iowa
Gabriel A Vecchi - Princeton University
Hiroyuki Murakami - Princeton University
Richard Gudgel - National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory
Resource Type: Journal article
Publication Details: Journal of Advances in Modeling Earth Systems, Vol.8(2), pp.538-565
DOI: 10.1002/2015MS000607
ISSN: 1942-2466
eISSN: 1942-2466
Number of pages: 28
Language: English
Date published: 06/2016
Academic Unit: Civil and Environmental Engineering
Record Identifier: 9983991976802771

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