Publication Date:
2015-01-01
Description:
Forecasting rapid intensification (hereafter referred to as RI) of tropical cyclones in the Atlantic Basin is still a challenge due to a limited understanding of the meteorological processes that are necessary for predicting RI. To address this challenge, this study considered large-scale processes as RI indicators within tropical cyclone environments. The large-scale processes were identified by formulating composite map types of RI and non-RI storms using NASA MERRA data from 1979 to 2009. The composite fields were formulated by a blended RPCA and cluster analysis approach, yielding multiple map types of RI’s and non-RI’s. Additionally, statistical differences in the large-scale processes were identified by formulating permutation tests, based on the composite output, revealing variables that were statistically significantly distinct between RI and non-RI storms. These variables were used as input in two prediction schemes: logistic regression and support vector machine classification. Ultimately, the approach identified midlevel vorticity, pressure vertical velocity, 200–850 hPa vertical shear, low-level potential temperature, and specific humidity as the most significant in diagnosing RI, yielding modest skill in identifying RI storms.
Print ISSN:
1687-9309
Electronic ISSN:
1687-9317
Topics:
Geosciences
,
Physics
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