Increased Extreme Coastal Water Levels Due to the Combined Action of Storm Surges and Wind Waves

Marcos, Marta; Rohmer, Jérémy; Vousdoukas, Michalis; Mentaschi, Lorenzo; Cozannet, Gonéri Le; Amores, Ángel

doi:10.1029/2019gl082599

Cited by 112 publications

(84 citation statements)

References 51 publications

(70 reference statements)

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“…Then, correlation is assessed with the Kendall rank correlation. Previous studies in the US coast and globally have suggested that an indicative value of 0.2 may be already significant enough (Wahl and Chambers, 2014) to require the computation of the joint probability using a multivariate approach such as the Copula functions (e.g., Sayol and Marcos, 2018;Enríquez et al, 2019;Marcos et al, 2019). Correlations for those independent events are shown in Figure 4C for all percentiles being in all cases very low with FIGURE 5 | Schematic representation of the approach followed in the study.…”

Section: Correlation Between Skew-surges and H Smentioning

confidence: 99%

Coastal Impacts Driven by Sea-Level Rise in Cartagena de Indias

et al. 2019

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This work analyzes the coastal impacts of the combined effect of extreme waves and sea level extremes, including surges and projected mean sea level rise in Bocagrande, Cartagena (Colombia). Extreme waves are assessed from a wave reanalysis that are propagated from deep waters to the beach considering the hydrodynamic processes and taking into account the interaction between waves and the coastal elevation within the study area. First, we consider present sea level, storm surges and waves affecting the area. Next, we analyze the effect of sea level rise according to a moderate (RCP4.5) climate change scenario for the 21st century (years 2025, 2050, 2075, and 2100). The most pessimistic scenario (year 2100) yields a percentage of flooded area of 97.2%, thus revealing the major threat that represents sea level rise for coastal areas in the Caribbean Sea.

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Section: Correlation Between Skew-surges and H Smentioning

confidence: 99%

Coastal Impacts Driven by Sea-Level Rise in Cartagena de Indias

et al. 2019

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“…The majority of these studies have been undertaken on a small spatial scale for specific localised regions, e.g. Fuzhou, China (Lian et al, 2013); Tsengwen River basin, Taiwan (Chen and Liu, 2014); Hudson River, USA (Orton et al, 2015); Shoalhaven River, Australia (Kumbier et al, 2018); the Rhine delta, Netherlands (Kew et al, 2013 andKhanal et al, 2018); Brest, France (Mazas and Hamm, 2017); Santander, Spain (Rueda et al, 2016); Ravenna, Italy (Bevacqua et al, 2017); and the river Trent, the Yare basin, the river Ancholme, and the rivers Taff and Lewes in East Sussex in the UK (Granger, 1959;Mantz and Wakeling, 1979;Thompson and Law, 1983;Samuels and Burt, 2002;and White, 2007, respectively). These studies have typically examined the dependence between two source variables only, such as storm surge (or storm tide) and river discharge, between storm surge and waves, or between storm surge and rainfall (as a proxy for run-off).…”

Section: Introductionmentioning

confidence: 99%

Assessing the characteristics and drivers of compound flooding events around the UK coast

Hendry

Haigh

Nicholls

et al. 2019

Hydrol. Earth Syst. Sci.

151

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Abstract. In low-lying coastal regions, flooding arises from oceanographic (storm surges plus tides and/or waves), fluvial (increased river discharge), and/or pluvial (direct surface run-off) sources. The adverse consequences of a flood can be disproportionately large when these different sources occur concurrently or in close succession, a phenomenon that is known as “compound flooding”. In this paper, we assess the potential for compound flooding arising from the joint occurrence of high storm surge and high river discharge around the coast of the UK. We hypothesise that there will be spatial variation in compound flood frequency, with some coastal regions experiencing a greater dependency between the two flooding sources than others. We map the dependence between high skew surges and high river discharge, considering 326 river stations linked to 33 tide gauge sites. We find that the joint occurrence of high skew surges and high river discharge occurs more frequently during the study period (15–50 years) at sites on the south-western and western coasts of the UK (between three and six joint events per decade) compared to sites along the eastern coast (between zero and one joint events per decade). Second, we investigate the meteorological conditions that drive compound and non-compound events across the UK. We show, for the first time, that spatial variability in the dependence and number of joint occurrences of high skew surges and high river discharge is driven by meteorological differences in storm characteristics. On the western coast of the UK, the storms that generate high skew surges and high river discharge are typically similar in characteristics and track across the UK on comparable pathways. In contrast, on the eastern coast, the storms that typically generate high skew surges are mostly distinct from the types of storms that tend to generate high river discharge. Third, we briefly examine how the phase and strength of dependence between high skew surge and high river discharge is influenced by the characteristics (i.e. flashiness, size, and elevation gradient) of the corresponding river catchments. We find that high skew surges tend to occur more frequently with high river discharge at catchments with a lower base flow index, smaller catchment area, and steeper elevation gradient. In catchments with a high base flow index, large catchment area, and shallow elevation gradient, the peak river flow tends to occur several days after the high skew surge. The previous lack of consideration of compound flooding means that flood risk has likely been underestimated around UK coasts, particularly along the south-western and western coasts. It is crucial that this be addressed in future assessments of flood risk and flood management approaches.

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“…Each process is forced by different environmental processes (oceanographic, meteorological, and hydrological) acting at varying spatial (local to global) and temporal scales (hours to centuries; Leonard et al, ). Extreme water levels on beaches are underestimated without considering wave run‐up and setup (e.g., Marcos et al, ), yet wave climates can include both local and distant swell components generated by faraway storms on the order of weeks prior to arrival (Hegermiller et al, ). Similarly, nontidal residuals are a product of regional wind stresses and barometric pressure anomalies occurring in the weather‐band timescale, as well as regional processes such as seasonally varying upwelling and downwelling, and large‐scale climate phenomena affecting basin‐wide circulations (i.e., El Niño Southern Oscillation [ENSO] and Pacific Decadal Oscillation; Merrifield et al, ).…”

Section: Introductionmentioning

confidence: 99%

Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

et al. 2019

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Rising seas coupled with ever increasing coastal populations present the potential for significant social and economic loss in the 21st century. Relatively short records of the full multidimensional space contributing to total water level coastal flooding events (astronomic tides, sea level anomalies, storm surges, wave run-up, etc.) result in historical observations of only a small fraction of the possible range of conditions that could produce severe flooding. The Time-varying Emulator for Short-and Long-Term analysis of coastal flood hazard potential is presented here as a methodology capable of producing new iterations of the sea-state parameters associated with the present-day Pacific Ocean climate to simulate many synthetic extreme compound events. The emulator utilizes weather typing of fundamental climate drivers (sea surface temperatures, sea level pressures, etc.) to reduce complexity and produces new daily synoptic weather chronologies with an auto-regressive logistic model accounting for conditional dependencies on the El Niño Southern Oscillation, the Madden-Julian Oscillation, seasonality, and the prior two days of weather progression. Joint probabilities of sea-state parameters unique to simulated weather patterns are used to create new time series of the hypothetical components contributing to synthetic total water levels (swells from multiple directions coupled with water levels due to wind setup, temperature anomalies, and tides). The Time-varying Emulator for Short-and Long-Term analysis of coastal flood hazard potential reveals the importance of considering the multivariate nature of extreme coastal flooding, while progressing the ability to incorporate large-scale climate variability into site specific studies assessing hazards within the context of predicted climate change in the 21st century.Plain Language Summary Predicting extreme coastal flooding is a present-day societal need and will only become more relevant as mean water levels increase due to sea level rise. However, the number of processes contributing to such events is too high for relatively short observational records to have measured all of the constructive combinations of waves, surge, wind, and sea level anomalies. We present a framework designed to create hypothetical combinations of relevant flood hazard potential processes by simulating the climate and weather patterns that drive coastal flooding. Including large-scale oceanic and atmospheric patterns as the drivers of coastal hazards reveals the climate a coastal community is most vulnerable to, which will be increasingly more important to understand as the climate changes during the 21st century.

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Increased Extreme Coastal Water Levels Due to the Combined Action of Storm Surges and Wind Waves

Cited by 112 publications

References 51 publications

Coastal Impacts Driven by Sea-Level Rise in Cartagena de Indias

Coastal Impacts Driven by Sea-Level Rise in Cartagena de Indias

Assessing the characteristics and drivers of compound flooding events around the UK coast

Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

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