A Multivariate Scaling System Is Essential to Characterize the Tropical Cyclones' Risk

Abstract

The current Tropical Cyclones (TCs) scaling system, Saffir‐Simpson Hurricane Wind Scale (SSHWS), characterizes the hazardousness of these events solely based on wind speed. This is despite the fact that TCs are classic examples of compound hazards during which multiple hazard drivers that are wind, storm surge, and intense rainfall interact and yield in impacts greater than the sum of individuals. Studies have shown that people's decision to evacuate is highly related to the estimated SSHWS category. Thus, the current SSHWS ‐based classification of TCs yields an underestimation of the hazardousness of TCs and so may misguide the threatened communities. Here, we propose a new scaling system that uses Copulas for categorizing TCs based on the likelihood of a given set of severity for rainfall, surge, and wind speed. We use a variety of data sources to obtain the timing and intensity of wind speed, rainfall along the track, and the associated maximum surge for 102 TCs that have made landfall in the United States' Atlantic and Gulf coasts between 1979 and 2020. Comparing the outputs of our scaling system with official damage reporting for the costliest TCs in the history of the United States, we show that the proposed approach significantly improves TC hazard communication and can be useful for informing decision makers and emergency responders.

A Vine Copula‐Based Ensemble Projection of Precipitation Intensity–Duration–Frequency Curves at Sub‐Daily to Multi‐Day Time Scales

“…This approach constructs a joint multivariate probability distribution of rainfall extremes from multiple downscaled precipitation model outputs and observations. The basic idea of this approach is to implement repeated conditional sampling from the well‐calibrated vine copula given the extremes extracted from downscaled precipitation, thus generating multi‐model ensemble simulations of extreme precipitation (Alipour et al., 2022; Zhang et al., 2021). Assume that r = ( r 1 ,…, r n −1 , r n ) signifies rainfall extremes generated from n −1 downscaled precipitation outputs and the corresponding observation.…”

A Framework of Dependence Modeling and Evaluation System for Compound Flood Events

“…Alipour et al. (2022) proposed a new Tropical Cyclones (TCs) hazard scaling system that takes into account the compound hazard of TCs, and defined the Multihazard Hurricane Index using the non‐exceedance probability from the vine copula model. Similar to existing literature regarding hydrometeorological simulation based on vine copulas (Ahn, 2021; Y. Tao et al., 2021; Vernieuwe et al., 2015; W. Wang et al., 2019; B. Zhang et al., 2022), vine structure in above studies is completely determined by maximum spanning tree algorithm with Kendall’s tau rank correlation coefficient as weight factor, which indicates that the vine structure cannot reflect specific copulae relationships between different variables.…”

A Multivariate Frequency Analysis Framework to Estimate the Return Period of Hurricane Events Using Event‐Based Copula

“…In bivariate and trivariate probability estimates, copula theory is commonly used to interpret precipitation, wind speed, flow discharge, and storm surge data (Alipour et al., 2022; Harr et al., 2022; Latif & Simonovic, 2022; Meng et al., 2021; Phillips et al., 2022; Sebastian et al., 2017; Trepanier et al., 2015; Wahl et al., 2015; B. Zhang et al., 2022). For example, Trepanier et al.…”