Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society

Santo, H.; Taylor, Paul H.; Gibson, Richard

doi:10.1098/rspa.2016.0376

Cited by 11 publications

(8 citation statements)

References 29 publications

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“…Figure 5 shows the Spearman rank correlation coefficient between the station-based NAO index and the 95th percentile of H s for DJFM for the historical period (1980 to 2009) and the period 2070-2099 under RCP4.5 and RCP8.5 for each ensemble member. Previous studies have shown a strong correlation between NAO and H s for the present wave climate off the west coast of Ireland (Gallagher et al, 2014), and for more extreme wave heights in the Northeast Atlantic and North Sea regions (Santo et al, 2016b). This is consistent with Figure 5a-c which shows the strong positive correlation coefficient, by ensemble member, between NAO and H s averaged over the historical period.…”

Section: North Atlantic Oscillation (Nao)supporting

confidence: 80%

“…Le Cozannet et al (2011) carried out a regional study using the ERA-40 dataset (Uppala et al, 2005) to drive the WAve Model (WAM) for the Bay/Gulf of Biscay (west of France) and also found a strong influence of the NAO/EA on the wave climatology in that region. The East Atlantic Western Russian (EAWR) pattern and the Scandinavian pattern are other modes of Northern Hemisphere atmospheric variability, and along with the EA have a weaker influence on the North Atlantic than the NAO (Santo et al, 2016b). For the purpose of the study presented in this paper, we focus on the NAO which is the most important North-24 E. Gleeson et al: Extreme waves in the North Atlantic Ocean ern Hemisphere mode of variability (Greatbatch, 2000;van Loon and Rogers, 1978;Hurrell, 1996).…”

Section: Introductionmentioning

confidence: 99%

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NAO and extreme ocean states in the Northeast Atlantic Ocean

et al. 2017

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Abstract. Large scale atmospheric oscillations are known to have an influence on waves in the North Atlantic. In quantifying how the wave and wind climate of this region may change towards the end of the century due to climate change, it is useful to investigate the influence of large scale oscillations using indices such as the North Atlantic Oscillation (NAO: fluctuations in the difference between the Icelandic low pressure system and the Azore high pressure system). In this study a statistical analysis of the station-based NAO index was carried out using an ensemble of EC-Earth global climate simulations, where EC-Earth is a European-developed atmosphere ocean sea-ice coupled climate model. The NAO index was compared to observations and to projected changes in the index by the end of the century under the RCP4.5 and RCP8.5 forcing scenarios. In addition, an ensemble of EC-Earth driven WAVEWATCH III wave model projections over the North Atlantic was analysed to determine the correlations between the NAO and significant wave height (H s ) and the NAO and extreme ocean states. For the most part, no statistically significant differences were found between the distributions of observed and modelled station-based NAO or in projected distributions of the NAO.Means and extremes of H s are projected to decrease on average by the end of this century. The 95th percentile of H s is strongly positively correlated to the NAO. Projections of H s extremes are location dependent and in fact, under the influence of positive NAO the 20-year return levels of H s were found to be amplified in some regions. However, it is important to note that the projected decreases in the 95th percentile of H s off the west coast of Ireland are not statistically significant in one of the RCP4.5 and one of the RCP8.5 simulations (me41, me83) which indicates that there is still uncertainty in the projections of higher percentiles.

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Section: North Atlantic Oscillation (Nao)supporting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

NAO and extreme ocean states in the Northeast Atlantic Ocean

et al. 2017

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“…Extrapolation into the future assumes a continuous linear trend in extreme wave heights, as has been detected for the available dataset, though neglecting the decadal variation due to the NAO fluctuation and the other cyclical atmospheric modes highlighted by Santo et al . [35]. The omission of these further factors will increase the uncertainty of the 2067 design wave heights.…”

Section: Wave Loadingmentioning

confidence: 99%

Wolf Rock lighthouse: past developments and future survivability under wave loading

Raby

Antonini

Pappas

et al. 2019

Phil. Trans. R. Soc. A.

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Lighthouses situated on exposed rocky outcrops warn mariners of the dangers that lurk beneath the waves. They were first constructed when approaches to wave loading and structural response were relatively unsophisticated, essentially learning from previous failures. Here, we chart the evolution of lighthouses on the Wolf Rock, situated between Land's End and the Isles of Scilly in the UK. The first empirical approaches are described, followed by design aspects of the present tower, informed by innovations developed on other rocky outcrops. We focus on a particular development associated with the automation of lighthouses: the helideck platform. The design concept is described and the structure then scrutinized for future survivability, using the latest structural modelling techniques of the entire lighthouse and helideck. Model validation data were obtained through a complex logistical field operation and experimental modal analysis. Extreme wave loading for the model required the identification of the 250-year return period wave using a Bayesian method with informative prior distributions, for two different scenarios (2017 and 2067). The structural models predict responses of the helideck to wave loading which is characterized by differential displacements of 0.093 m (2017) and 0.115 m (2067) with associated high tension forces and plastic strain. This article is part of the theme issue ‘Environmental loading of heritage structures’.

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“…The average H max value (measured over the typical duration of a storm, for example) could allow for assessing the severity of a sea condition, similarly to the so-called most probable maximum individual wave height [16], and hence be used as a criterion to enter survival mode.…”

Section: B Survival Modementioning

confidence: 99%