Modelling a storm surge under future climate scenarios: case study of extratropical cyclone Gudrun (2005)

Mäll, Martin; Suursaar, Ülo; Nakamura, Ryota; Shibayama, Tomoya

doi:10.1007/s11069-017-3011-3

Cited by 22 publications

(8 citation statements)

References 53 publications

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“…For example, the fetch and directional spectrum of sea surface waves are determined by the wind speed and direction (e.g., Kahma and Pettersson 2005;Pettersson et al 2010). Winds likewise affect the spatial distribution of the sea level rise (e.g., Johansson et al 2014), the occurrence of coastal storm surges (e.g., Gaslikova et al 2013;Mäll et al 2017;Särkkä et al 2017), coastal upwelling (Goubanova et al 2011Alvarez et al 2017), accumulation of pack ice on downwind coasts (Ronkainen et al 2018), and opening of coastal polynyas during offshore winds (Stössel et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations

2019

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Future changes in geostrophic winds over Europe and the North Atlantic region were studied utilizing output data from 21 CMIP5 global climate models (GCMs). Changes in temporal means, extremes, and the joint distribution of speed and direction were considered. In concordance with previous research, the time mean and extreme scalar wind speeds do not change pronouncedly in response to the projected climate change; some degree of weakening occurs in the majority of the domain. Nevertheless, substantial changes in high wind speeds are identified when studying the geostrophic winds from different directions separately. In particular, in northern Europe in autumn and in parts of northwestern Europe in winter, the frequency of strong westerly winds is projected to increase by up to 50%. Concurrently, easterly winds become less common. In addition, we evaluated the potential of the GCMs to simulate changes in the near-surface true wind speeds. In ocean areas, changes in the true and geostrophic winds are mainly consistent and the emerging differences can be explained (e.g., by the retreat of Arctic sea ice). Conversely, in several GCMs the continental wind speed response proved to be predominantly determined by fairly arbitrary changes in the surface properties rather than by changes in the atmospheric circulation. Accordingly, true wind projections derived directly from the model output should be treated with caution since they do not necessarily reflect the actual atmospheric response to global warming.

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Section: Introductionmentioning

confidence: 99%

Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations

2019

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“…Even the most catastrophic North European windstorms reach Estonia in dissipation phase and somewhat weakened (Mäll et al . ). Due to the relatively small size and irregular shape of the Baltic Sea, the wave climate is almost lacking in swell‐component and the highest locally generated storm waves may occasionally reach the significant height (H s ) of 9 m (Soomere et al .…”

Section: Study Area and Geological Backgroundmentioning

confidence: 97%

Cyclicity in ridge patterns on the prograding coasts of Estonia

Suursaar

Kall

Steffen

et al. 2019

Boreas

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Recent LiDAR surveys have revealed that on postglacially uplifting coasts of Estonia rhythmic coastal landforms (beach ridge sequences and foredune plains) occur to a considerable extent. We studied four of them to reveal age and periodicity in these multiple ridge systems and discussed their genesis in the Subatlantic (semi‐continental) conditions of the Baltic Sea area. Using recent models of Fennoscandian uplift due to glacial isostatic adjustment (GIA), we constructed Holocene apparent sea level curves for the study sites at Õngu, Mänspe, Haldi and Keibu; converted distance–height shore profiles into time series (including corrections on shore profile non‐linearity and variations in GIA‐eustasy balance); and analysed the patterns using spectral analysis. It was suggested that due to non‐tidal conditions, relatively low‐energy hydrodynamic forcing and small aeolian contribution, the ridges mark ancient shorelines. They are relatively modest in height (mostly 0.2–1 m), form regular and extensive (up to 150 ridges) patterns, and date back to ~9000 years before present. We studied <5‐ka‐old sections. The mean ridge spacing varied, depending also on coastal slope, between 21 and 39 m. Both simple counting and spectral analysis involved some specific limitations, yet the estimates for typical spacing were alike, at 32 (±5) years. The regular nature of the low‐ridge patterns originated from relative sea level lowering and gradual sediment accretion/erosion. However, the progradation was rather uplift‐ than accretion‐driven and the stepwise process in ridge formation was probably not autocyclic. It was governed or modulated by quasi‐periodic 25–40 year cyclicity in local wave forcing, relative sea level variations and wind conditions. Being most likely connected to the North Atlantic Oscillation, the quasi‐regular, decadal‐scale, similarly phased variations may magnify each other's effect on the westerly exposed coasts of Estonia. Additionally, some other (e.g. event‐driven) mechanisms may also be present.

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“…Strong dependence has been found between extreme rainfall and storm surge in coastal regions (Zheng et al, 2013;Mohanty et al, 2020). Overall, the compound storm surge and heavy rainfall events are associated with tropical cyclones, atmospheric rivers (Lin et al, 2010a), medicanes (Amores et al, 2020;Davolio et al, 2020;, and extreme extratropical cyclones (Danard et al, 2004;Colle et al, 2015;Mäll et al, 2017;Lin et al, 2019).…”

Section: Storm Surge and Heavy Rainfallmentioning

confidence: 98%

Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods

et al. 2021

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Compound extremes pose immense challenges and hazards to communities, and this is particularly true for compound hydrometeorological extremes associated with deadly floods, surges, droughts, and heat waves. To mitigate and better adapt to compound hydrometeorological extremes, we need to better understand the state of knowledge of such extremes. Here we review the current advances in understanding compound hydrometeorological extremes: compound heat wave and drought (hot-dry), compound heat stress and extreme precipitation (hot-wet), cold-wet, cold-dry and compound flooding. We focus on the drivers of these extremes and methods used to investigate and quantify their associated risk. Overall, hot-dry compound extremes are tied to subtropical highs, blocking highs, atmospheric stagnation events, and planetary wave patterns, which are modulated by atmosphere-land feedbacks. Compared with hot-dry compound extremes, hot-wet events are less examined in the literature with most works focusing on case studies. The cold-wet compound events are commonly associated with snowfall and cold frontal systems. Although cold-dry events have been found to decrease, their underlying mechanisms require further investigation. Compound flooding encompasses storm surge and high rainfall, storm surge and sea level rise, storm surge and riverine flooding, and coastal and riverine flooding. Overall, there is a growing risk of compound flooding in the future due to changes in sea level rise, storm intensity, storm precipitation, and land-use-land-cover change. To understand processes and interactions underlying compound extremes, numerical models have been used to complement statistical modeling of the dependence between the components of compound extremes. While global climate models can simulate certain types of compound extremes, high-resolution regional models coupled with land and hydrological models are required to simulate the variability of compound extremes and to project changes in the risk of such extremes. In terms of statistical modeling of compound extremes, previous studies have used empirical approach, event coincidence analysis, multivariate distribution, the indicator approach, quantile regression and the Markov Chain method to understand the dependence, greatly advancing the state of science of compound extremes. Overall, the selection of methods depends on the type of compound extremes of interests and relevant variables.

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Modelling a storm surge under future climate scenarios: case study of extratropical cyclone Gudrun (2005)

Cited by 22 publications

References 53 publications

Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations

Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations

Cyclicity in ridge patterns on the prograding coasts of Estonia

Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods

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