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Extreme sea levels, coastal flooding and climate change with a focus on Atlantic Canada

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  • Keith Thompson
  • Natacha Bernier
  • Paul Chan

Abstract

Estimation of the probability distribution of extreme sea levels, for the present time and the next century, is discussed. Two approaches are described and their strengths and weaknesses are compared. The first approach is based on dynamics and uses a storm surge model forced by tides, winds and air pressure fields. The second approach is based on the statistical analysis of observed hourly sea level records using a new first-order Markov process that can capture non-Gaussian characteristics (such as skewness) in the non-tidal component of the observed sea level record. It is shown that both approaches can provide good estimates of present day flooding probabilities for regions with relatively strong tides. The limitations of both approaches in terms of assessing the effect of global sea level rise, glacial-isostatic adjustment of the land, and changes in the frequency and severity of storms and hurricanes, are illustrated using recent results for the Northwest Atlantic. Some sensitivity studies are carried out to transform uncertainty in climate change projections into uncertainties in the probability of coastal flooding. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • Keith Thompson & Natacha Bernier & Paul Chan, 2009. "Extreme sea levels, coastal flooding and climate change with a focus on Atlantic Canada," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 51(1), pages 139-150, October.
    • Handle: RePEc:spr:nathaz:v:51:y:2009:i:1:p:139-150
    DOI: 10.1007/s11069-009-9380-5
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    References listed on IDEAS

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    1. Adelchi Azzalini & Antonella Capitanio, 2003. "Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t‐distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 367-389, May.
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