Mapping Dependence Between Extreme Rainfall and Storm Surge

Wu, Wenyan; McInnes, Kathleen L.; O’Grady, Julian; Hoeke, Ron; Leonard, Michael; Westra, Seth

doi:10.1002/2017jc013472

Cited by 95 publications

(100 citation statements)

References 37 publications

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“…This study follows previous work by the authors on the quantification of compound flood risk in coastal regions caused by extreme rainfall and storm surge based on their dependence (Zheng et al 2013, Zheng et al 2015 and the estimation of dependence between the two coastal food drivers around Australia using both observed and simulated surge data (Wu et al 2018). The objectives of this study are therefore (1) to investigate potential impact of ENSO on the dependence between storm surge and rainfall, with Australia as a case study;…”

Section: Introductionmentioning

confidence: 79%

“…Therefore, the storm surge data are the difference between the sea level values and the tide values, referred to as non-tidal residuals. Mean sea level changes were represented using a linear trend term (Wu et al 2018). ENSO's influences on the mean sea level (White et al 2014) could influence the results but are outside the scope of this study.…”

Section: Observed Storm Surge Datamentioning

confidence: 99%

“…Coastal flood risk attributed to storm surge and rainfall (through pluvial or fluvial processes) has been reported in many regions around the world, including Asia (Lian et al 2013, Ikeuchi et al 2017, Xu et al 2018, Ghosh et al 2019, Europe (Svensson and Jones 2004, Klerk et al 2015, Van den Hurk et al 2015, Bevacqua et al 2017, Hu et al 2019, North America (Wahl et al 2015, Bass and Bedient 2018, Shao et al 2019, North Africa (Zellou and Rahali 2019) and Australia (Zheng et al 2013, Kumbier et al 2018, Wu et al 2018. There is strong evidence that the joint occurrence of extreme storm surge and heavy rainfall is related to large scale weather patterns, such as tropical cyclones, ex-tropical cyclones, frontal systems and East Coast Lows in Australia (McInnes et al 2002, Van den Hurk et al 2015, Wahl et al 2015, Kumbier et al 2018, Wu et al 2018. The weather patterns are a function of incipient climate conditions and are influenced by year-to-year climate variability from large scale climate phenomena (or climate drivers), such as the El Niño Southern Oscillation (ENSO) (Evans andBoyer-Souchet 2012, Santoso et al 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The impact of ENSO on rainfall variability has been the topic of many studies (Risbey et al 2009, Verdon-Kidd and Kiem 2009, Cai et al 2012, Evans and Boyer-Souchet 2012 Muis et al 2018). However, there have been no studies on the climatic influence of the dependence between extreme rainfall and surge, which can subsequently influence the risk of compound floods (Wu et al 2018). Therefore, understanding the impact of ENSO on the dependence between storm surge and rainfall is especially important for understanding future coastal flood risk when the occurrence of extreme ENSO events is projected to become more frequent in the future (Power et al 2013, Cai et al 2014, Wittenberg 2015.…”

Section: Introductionmentioning

confidence: 99%

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Impact of ENSO on dependence between extreme rainfall and storm surge

Leonard

2019

Environ. Res. Lett.

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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 Niño 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 of the 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 modelthe 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 Niña in Australia, with increased dependence observed during La Niña along most of the Australian coastline. However, there can be increased dependence during El Niño 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 of whether extremes are more likely to co-occur and exacerbate compound flood risk.

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Section: Introductionmentioning

confidence: 79%

Section: Observed Storm Surge Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of ENSO on dependence between extreme rainfall and storm surge

Leonard

2019

Environ. Res. Lett.

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“…The MTWL estimates provided in this study should be used with caution for bathtub type inundation studies as waves will have a more dynamic interaction with the inundated coastline (dunes and seawalls) than the rising storm tide. Inundation studies should also consider terrestrial sources during coincided storm events (Wu et al, ).…”

Section: Discussionmentioning

confidence: 99%

Extreme Water Levels for Australian Beaches Using Empirical Equations for Shoreline Wave Setup

et al. 2019

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Empirical equations for wave breaking and wave setup are compared with archived shoreline wave setup measurements to investigate the contribution of wind waves to extreme Mean Total Water Levels (MTWL, the mean height of the shoreline), for natural beaches exposed to open ocean wind waves. A broad range of formulations is compared through linear regression and quantile regression analysis of the highest measured values. Shoreline wave setup equations are selected based on the availability of local beach slope data and the ability of the quantile regression to show a good representation of the highest measured levels. Wave parameters from an existing spectral wave hindcast are used as input to the selected equations and are combined with a storm tide time series to quantify the relative contribution of shoreline wave setup to the extreme MTWL climate along Australian beaches. A multipass analysis is provided to understand the ability to capture the shoreline wave setup estimates with and without considering beach slope. The national scale analysis which does not include beach slope indicates there are multiple contributing factors to MTWL. Examples are provided at two locations of differing local beach slope to show the importance of including local beach slope in determining the contribution of waves to MTWL. A tool is in development for further investigation of wave setup for Australian beaches.

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Daily synoptic conditions associated with occurrences of compound events in estuaries along North Atlantic coastlines

Camus

Haigh

Wahl

et al. 2022

Intl Journal of Climatology

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Coastal compound flooding events occur when extreme events of rainfall, river discharge and sea level coincide and collectively increase water surface elevation, exacerbating flooding. The meteorological conditions that generate these events are usually low-pressure systems that generate high winds and intense rainfall. In this study, we identify the types of synoptic atmospheric conditions that are typically associated with coastal compound events using a weathertype approach, for the North Atlantic coastlines (encompassing northwest Europe and the east coast of the United States). Compound events are identified along the estuaries of the study region from 1980 to 2014 based on an impact function defined by water surface elevation that resulted from the combination of river discharge and sea level. We find that compound events are more frequent along European as opposed to U.S. coastlines. In both cases, they are associated with a few dominant weather patterns. European hotspots of compound events are concentrated in the west coast of United Kingdom, the northwest coast of the Iberian Peninsula and around the Strait of Gibraltar.These areas share the same weather patterns which represent the main pathways of storms that cross the North Atlantic Ocean. In the case of U.S. locations, the areas with highest number of compound events are located mainly in the Gulf of Mexico and along Mexico and along the mid-eastern U.S. coastlines. In these areas, compound events are produced by transitional weather patterns, which describe storms that travel northward parallel to the coastline. Splitting the occurrence of compound events in the corresponding weather types discriminates the interannual variability based on the relationship with dominant climate indices in the North Atlantic Ocean.

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Mapping Dependence Between Extreme Rainfall and Storm Surge

Cited by 95 publications

References 37 publications

Impact of ENSO on dependence between extreme rainfall and storm surge

Impact of ENSO on dependence between extreme rainfall and storm surge

Extreme Water Levels for Australian Beaches Using Empirical Equations for Shoreline Wave Setup

Daily synoptic conditions associated with occurrences of compound events in estuaries along North Atlantic coastlines

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