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contributor authorLin, Ning
contributor authorJing, Renzhi
contributor authorWang, Yuyan
contributor authorYonekura, Emmi
contributor authorFan, Jianqing
contributor authorXue, Lingzhou
date accessioned2017-06-09T17:34:37Z
date available2017-06-09T17:34:37Z
date issued2017
identifier issn0027-0644
identifier otherams-87439.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231108
description abstracte apply a progression of advanced statistical methods to investigate the dependence of the 6-hour tropical cyclone (TC) intensity change on various environmental variables, including the recently developed Ventilation Index (VI). The North Atlantic (NA) and western North Pacific (WNP) observations from 1979-2014 are used. We first develop a model of the intensity change as a linear function of 13 variables used in operational models, obtaining statistical R2 values of 0.26 for NA and 0.3 for WNP. Statistical variable selection techniques are then applied to significantly reduce the number of predictors (to 5-11), while keeping similar R2 with linear or nonlinear models. Further reduction of the number of predictors (to 5-7) and significant improvement of R2 (0.41-0.53) are obtained with mixture modeling, indicating that the dependence of TC intensification on the environment is nonhomogeneous. Applying VI as the environmental predictor in the mixture modeling gives R2 (0.41-0.74) similar to or better than those with more environmental variables, confirming that VI is a dominant environmental variable, but its effect on TC intensification is quite heterogeneous. However, the overall predictive R2 of the mixture models are relatively low (< 0.3), as the considered environmental variables have limited predictability for the occurrence of extreme/rapid intensification. Finally, nonparametric regression with 6 predictors (current intensity, previous intensity change, the three components of VI (maximum potential intensity, shear, and entropy deficit), and 200-hPa zonal wind) performs relatively well with predictive R2 of 0.37 for NA and 0.36 for WNP. The predictability of these statistical models may be further improved by adding oceanic and inner-core process predictors.
publisherAmerican Meteorological Society
titleA statistical investigation of the dependence of tropical cyclone intensity change on the surrounding environment
typeJournal Paper
journal volume145
journal issue007
journal titleMonthly Weather Review
identifier doi10.1175/MWR-D-16-0368.1
journal fristpage2813
journal lastpage2831
treeMonthly Weather Review:;2017:;volume( 145 ):;issue: 007
contenttypeFulltext


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