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Joint probability risk modelling of storm surge and cyclone wind along the coast of Bay of Bengal using a statistical copula
Author(s) -
Bushra Nazla,
Trepanier Jill C.,
Rohli Robert V.
Publication year - 2019
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.6068
Subject(s) - storm surge , surge , copula (linguistics) , climatology , tropical cyclone , storm , meteorology , typhoon , wind speed , landfall , environmental science , geology , geography , mathematics , econometrics
High winds and storm surges associated with torrential rain from tropical cyclones (TCs) cause massive destruction to property and cost the lives of many people. The coastline of the Bay of Bengal (BoB) ranks as one of the most susceptible to storm surges in the world due to low‐lying elevation and a high frequency of TC occurrence. This study uses data from 1885 to 2011 and a bivariate statistical copula to describe the relationship and dependency between empirical TC storm surge and reported wind speed before landfall at the BoB. Among the copulas and their families, an Archimedean, Gumbel copula with margins defined by the empirical distributions is specified as the most appropriate choice for the BoB. The model provides return periods for pairs of TC storm surge and 12‐hr pre‐landfall wind along the BoB coastline. On the shortest timescale, the BoB can expect a TC with 12‐hr pre‐landfall winds of at least 24 m/s and surge heights of at least 4.0 m, on average, once every 3.9 years. On the other hand, the long‐term, worst case scenario suggests the BoB can expect 12‐hr pre‐landfall winds of 62 m/s and surge heights of at least 8.0 m, on average, once every 311.8 years. Using a copula to model the combined frequency of cyclone wind speeds along with storm surges along the BoB coastline increases the understanding of the dangerous TC characteristics in this region, which can reduce fatalities and monetary losses.