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

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 (straightmoving 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.

The western Pacific subtropical high and tropical cyclone landfall: Seasonal forecasts using the Met Office GloSea5 system

“…These forecasts are produced using a range of techniques, including statistical methods (e.g., Chan et al ; ; Fan and Wang, ; Choi et al ), dynamical models (Vitart and Stockdale, ; Vecchi et al ; Camp et al ; Manganello et al ) and “hybrid” statistical–dynamical models (e.g., Kim et al ; ; Li et al ; Zhan and Wang, ; Choi et al ; Zhang et al ). Seasonal forecasts of TC landfall risk have also been developed for East Asia (Goh and Chan, ; Huang and Chan, ; Zhang et al ; , Lok and Chan, ) and for specific regions including Taiwan (Lu et al ; Choi et al ), Korea and Japan (Goh and Chan, ), China (Liu and Chan, ; Goh and Chan, ; Sun and Ahn, ), Vietnam (Duong et al ; Tan et al ), the South China Sea (Lok and Chan, ) and the East China Sea (Kim et al ).…”

Dominant Role of Atlantic Multidecadal Oscillation in the Recent Decadal Changes in Western North Pacific Tropical Cyclone Activity

“…It is therefore reasonable to postulate that the observed decadal change in WNP TC frequency may be linked to the observed recent changes in these climate modes. The climate system response to anthropogenic forcing occurs in the presence of substantial natural climate variability, and it is difficult to unambiguously separate forced climate change from natural variability (Delworth et al, ; Deser et al, ; Jia et al, ; Kay et al, ; Murakami et al, ; Zhang, Vecchi, Murakami, Delworth, et al, ). Large‐ensemble simulations using the same model and the same forcing provide an opportunity to assess the impacts of internal climate variability and forced climate change on the climate system (Deser et al, ; Kay et al, ).…”

Towards Dynamical Seasonal Forecast of Extratropical Transition in the North Atlantic

“…The successful seasonal forecast of TC activity by dynamical models is hypothesized to be associated with skillful predictions of two important aspects: large‐scale climate conditions that influence TCs and response of TCs to the climatological and/or anomalous climate conditions (e.g., Vecchi et al, ). This hypothesis provides the physical basis for statistical‐dynamical models for seasonal forecasts of TCs (see Murakami, Villarini, et al, ; Vecchi et al, , , ; Villarini & Vecchi, ; Wang et al, ; Zhang et al, ; Zhao et al, ). There are fewer studies on modulations of large‐scale climate conditions on ET and non‐ET activity relative to TC activity.…”

“…Grouping TCs to clusters in terms of tracks and genesis locations enables the finding that these clusters exhibit distinct responses to large‐scale climate conditions (see Colbert & Soden, ; Kossin et al, ). This technique has been successfully used to develop statistical‐dynamical models for the seasonal forecast of landfalling TCs in the North Atlantic (Murakami, Villarini, et al, ) and Western North Pacific (Zhang et al, ) through finding predictors for each TC cluster. Because tracks of ET and non‐ET storms show distinct characteristics in many aspects (e.g., curvature and latitude coverage), the clustering technique may provide a useful path for improved understanding of climate modulation on ET and non‐ET activity and seeking predictors to building hybrid models for seasonal forecasts.…”