Synoptic-Scale Precursors to Tropical Cyclone Rapid Intensification in the Atlantic Basin

Abstract

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.

Evolution of the upper tropospheric outflow in Hurricanes Iselle and Julio (2014) in the Navy Global Environmental Model (NAVGEM) analyses and in satellite and dropsonde observations

“…This relationship between increase in outflow magnitude and increase in TC intensity is in good agreement with many studies that previously identified such a relationship [e.g., Sadler, 1976;Chen and Gray, 1986;Merrill, 1988;Molinari and Vollaro, 1989;Pfeffer and Challa, 1992;Wu and Emanuel, 1994;Frank and Ritchie, 1999;Hanley et al, 2001;Kimball and Evans, 2002;Rappin et al, 2011]. The inward radial progression during intensification noted in both TCs is a result that has not received as much attention, but that agrees with the enhanced divergence (and subsequent mass evacuation from the core) arguments of Molinari et al [1995] and Grimes and Mercer [2015]. Indeed, as was found by Emanuel [2012] and Wang et al [2014], greater outflow provides a critical connection between the TC boundary layer and the upper troposphere environment.…”

“…The inward radial progression during intensification noted in both TCs is a result that has not received as much attention, but that agrees with the enhanced divergence (and subsequent mass evacuation from the core) arguments of Molinari et al . [] and Grimes and Mercer []. Indeed, as was found by Emanuel [] and Wang et al .…”

Diagnosing Tropical Cyclone Rapid Intensification Through Rotated Principal Component Analysis of Synoptic-Scale Diagnostic Fields

“…As the primary goal of this research was the identification of variables and spatial locations most favorable for distinguishing RI and non-RI storms, discriminatory statistical methods were needed. One method, rotated principal component analysis (RPCA), has been shown to be useful in discriminating meteorological environments of different types [11][12][13][14]. These studies also used permutation testing to evaluate magnitude differences in diagnostic variables for each environment.…”

“…While S-mode helped reveal the difficulties in identifying relevant RI/non-RI distinguishing characteristics, the results did not provide the necessary discrimination capability of interest in this work. Recent work has shown the value of composite analysis with T-mode RPCA in identifying discriminating characteristics for different meteorological event types [11,12]. Following the methodology of [11,12], a T-mode varimax-rotated RPCA [11,16], conducted simultaneously on all GEFS reforecast fields, was completed on all RI events and all non-RI events separately.…”

“…Recent work has shown the value of composite analysis with T-mode RPCA in identifying discriminating characteristics for different meteorological event types [11,12]. Following the methodology of [11,12], a T-mode varimax-rotated RPCA [11,16], conducted simultaneously on all GEFS reforecast fields, was completed on all RI events and all non-RI events separately. T-mode contrasts S-mode in that in T-mode, the relationships between events, as opposed to spatial locations, are of interest, and thus the correlation matrix is computed on the event dimension of the data.…”