Tide-surge interaction in the English Channel

Idier, Déborah; Dumas, Franck; Müller, Héloïse

doi:10.5194/nhess-12-3709-2012

Cited by 83 publications

(76 citation statements)

References 30 publications

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“…Tide-surge interaction has been most studied in the southern North Sea, where the largest positive NTR are observed to occur on the rising tide (Horsburgh and Wilson, 2007). Tide-surge interactions have also been observed across other continental shelf regions and in shallow water areas, including: the English Channel (Haigh et al, 2009b;Idier et al, 2012); Canada (Bernier and Thompson, 2007); Australia ; the South China Sea (Feng and Tsimplis, 2014); the Bay of Bengal (Antony and Unnikrishnan, 2013); and was observed during Hurricane Sandy off the USA east coast (Valle-Levinson et al, 2013). However, the extent to which tide-surge interactions occur has not been assessed for large stretches of the world's coastline.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variability and Long-Term Trends in Skew Surges Globally

Mawdsley

Haigh

2016

Front. Mar. Sci.

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Storm surges and the resulting extreme high sea levels are among the most dangerous natural disasters and are responsible for widespread social, economic and environmental consequences. Using a set of 220 tide gauges, this paper investigates the temporal variations in storm surges around the world and the spatial coherence of its variability. We compare results derived from two parameters used to represent storm surge: skew surge and the more traditional, non-tidal residual. We determine the extent of tide-surge interaction, at each study site, and find statistically significant (95% confidence) levels of tide-surge interaction at 59% of sites based on tidal level and 81% of sites based on tidal-phase. The tide-surge interaction was strongest in regions of shallow bathymetry such as the North Sea, north Australia and the Malay Peninsula. At most sites the trends in the skew surge time series were similar to those of non-tidal residuals, but where there were large differences in trends, the sites tended to have a large tidal range. Only 13% of sites had a statistically significant trend in skew surge, and of these approximately equal numbers were positive and negative. However, for trends in the non-tidal residual there were significantly more negative trends. We identified 8 regions where there were strong positive correlations in skew surge variability between sites, which meant that a regional index could be created to represent these groups of sites. Despite strong correlations between some regional skew surge indices, none were significant at the 95% level, however, at the 80% level there was significant positive correlation between the north-west Atlantic-south and the North Sea. Correlations between the regional skew surge indices and climate indices only became significant at the 80% level, where Niń o 4 was positively correlated with the Gulf of Mexico skew surge index and negatively correlated with the east Australia skew surge index. The inclusion of autocorrelation in the calculation of correlation greatly reduced their significance, especially in the short time-series used for the regional skew surge indices. Skew surge improved the representation of storm surge magnitudes, and therefore allows a more accurate detection of changes on secular and inter-annual time scales.

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Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variability and Long-Term Trends in Skew Surges Globally

Mawdsley

Haigh

2016

Front. Mar. Sci.

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“…Such an indi-rect method assumes surges and tides are independent. This assumption being wrong in some places (Idier et al, 2012), methods have been developed to take into account this partial dependency (Mazas et al, 2014). However, the results are not yet fully satisfactory, with for instance a notable offset between direct and indirect methods within the interpolation domain (i.e.…”

Section: Introductionmentioning

confidence: 99%

How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France)

Bulteau

Idier

Lambert

et al. 2015

Nat. Hazards Earth Syst. Sci.

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Abstract. The knowledge of extreme coastal water levels is useful for coastal flooding studies or the design of coastal defences. While deriving such extremes with standard analyses using tide-gauge measurements, one often needs to deal with limited effective duration of observation which can result in large statistical uncertainties. This is even truer when one faces the issue of outliers, those particularly extreme values distant from the others which increase the uncertainty on the results. In this study, we investigate how historical information, even partial, of past events reported in archives can reduce statistical uncertainties and relativise such outlying observations. A Bayesian Markov chain Monte Carlo method is developed to tackle this issue. We apply this method to the site of La Rochelle (France), where the storm Xynthia in 2010 generated a water level considered so far as an outlier. Based on 30 years of tide-gauge measurements and 8 historical events, the analysis shows that (1) integrating historical information in the analysis greatly reduces statistical uncertainties on return levels (2) Xynthia's water level no longer appears as an outlier, (3) we could have reasonably predicted the annual exceedance probability of that level beforehand (predictive probability for 2010 based on data until the end of 2009 of the same order of magnitude as the standard estimative probability using data until the end of 2010). Such results illustrate the usefulness of historical information in extreme value analyses of coastal water levels, as well as the relevance of the proposed method to integrate heterogeneous data in such analyses.

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“…Modeled surges are the differences between the simulation with both tide and meteorological forcing (wind and atmospheric pressure) and the simulation with only tide. This way, surges include also tide-surge interaction (Idier et al 2012a). Measured surges have been computed from tide gauges.…”

Section: Methodsmentioning

confidence: 99%

“…Such phenomenon happens in the presence of significant tide range (and induced tidal currents) and surge. SaintMalo is characterized by a strong tidal range (about 10.7 m for a mean spring tide) and annual surges of 0.8 m. This is thus a site which can be subject to this type of phenomena (Idier et al 2012a). This can also be due to harmonic analysis made on old water level measurements (before numeric tide gauges).…”

Section: Methodsmentioning

confidence: 99%

“…The mean water level along the coast results from tide, surge, and wave setup. Most of the forecast systems provide water level including tide and surge components, based on different strategies taking tide-surge interaction or not into account (Idier et al 2012a). Moreover, operational surge models whose spatial resolution is about a few kilometers use either a constant sea surface drag coefficient or those issued from Wu (1982), Smith and Banke (1975), or Charnock (1955) formulations without taking into account the sea state.…”

Section: Introductionmentioning

confidence: 99%

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Atmospheric storm surge modeling methodology along the French (Atlantic and English Channel) coast

et al. 2014

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Storm surge modeling and forecast are the key issues for coastal risk early warning systems. As a general objective, this study aims at improving high-frequency storm surge variations modeling within the PREVIMER system (www.previmer.org), along the French Atlantic and English Channel coasts. The paper focuses on (1) sea surface drag parameterization and (2) uncertainties induced by the meteorological data quality. The modeling is based on the shallowwater version of the model for applications at regional scale (MARS), with a 2-km spatial resolution. The model computes together tide and surge, allowing properly taking into account tide-surge interactions. To select the most appropriate parameterization for the study area, a sensitivity analysis on sea surface drag parameterizations is done, based on comparisons of modeled storm surges (extracted with a tidal component analysis) with four tidal gauges, during four storm events, and over about 7.5 years, where the observed water level is processed in the same way as the modeling results. The tested drag parameterizations are a constant one, as reported by Moon et al. (J Atmos Sci 61: 2321-2333, 2007, Makin (BoundLayer Meteorol 115: 169-176, 2005), and Charnock (J Roy Meteor Soc 81: 639-640, 1955). Charnock's parameterization, either constant with high value (0.022) or relying on a full statistical description of the sea state, enables to improve storm surges forecast with peak errors 10 cm smaller than those computed with the other drag coefficient formulations. The impact of the meteorological forcing quality is evaluated over January 2012 from the comparison between surges modeled with different meteorological data (ARPEGE, ARPEGE High Resolution and AROME) and observations. For event time scale, storm surge computation is highly improved with ARPEGE High Resolution data. For month time scale, statistics of model accuracy are less sensitive to the choice of meteorological forcing. As a conclusion, the Charnock's parameterization is advised to model storm surges on the French Atlantic and English Channel coasts, whereas the quality requirements regarding meteorological inputs depend on the time scale of interest. Within the PREVIMER system, aiming at forecasting events, ARPEGE High Resolution data are used.

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Tide-surge interaction in the English Channel

Cited by 83 publications

References 30 publications

Spatial and Temporal Variability and Long-Term Trends in Skew Surges Globally

Spatial and Temporal Variability and Long-Term Trends in Skew Surges Globally

How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France)

Atmospheric storm surge modeling methodology along the French (Atlantic and English Channel) coast

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