4.7 Article

Impact of ENSO on dependence between extreme rainfall and storm surge

Journal

ENVIRONMENTAL RESEARCH LETTERS
Volume 14, Issue 12, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/1748-9326/ab59c2

Keywords

compound flood risk; coastal flood risk; ENSO; dependence analysis; extreme storm surge; extreme rainfall

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Dependence between extreme rainfall and storm surge can have significant implications for coastal floods, which are often caused by joint occurrence of these flood drivers (through pluvial or fluvial processes). The effect of multiple drivers leading to a compound flood event poses higher risk than those caused by a single flood-driving process. There is strong evidence that compound floods caused by joint occurrence of extreme storm surge and heavy rainfall are related to meteorological forcing (e.g. large scale pressure systems and wind) and climate phenomena (e.g. the El Nifio Southern Oscillation or ENSO). Therefore, understanding how climate phenomena affect the co-occurrence of coastal flood drivers is an important step towards understanding future coastal flood risk under climate change. Here we examine the impact of one ofthe most important climate phenomena ENSO on dependence between storm surge and rainfall in Australia, using both observed surge and modelled surge from a linked ocean-climate model the Regional Ocean Modeling System. Our results show that ENSO has a significant impact on the dependence between extreme rainfall and storm surge, thus flood risk resulted from these drivers. The overall dependence is largely driven by La Nina in Australia, with increased dependence observed during La Nina along most of the Australian coastline. However, there can be increased dependence during El Nifio in some locations. The results demonstrate dependence is contributed by unequally-weighted mechanisms due to the interaction between climate phenomena and local features, indicating the need for greater understanding of composition of compound flood risk. Where climate phenomena are anticipated to change into the future, it is possible to use integrated process-driven models to establish a better understanding ofwhether extremes are more likely to co-occur and exacerbate compound flood risk.

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