A nonstationary analysis for investigating the multiscale variability of extreme surges: case of the English Channel coasts

• Published in: Natural Hazards and Earth System Sciences
• Main Authors: I. Turki, L. Baulon, N. Massei, B. Laignel, S. Costa, M. Fournier, O. Maquaire
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2020
• Subjects: envir; geo; North Atlantic; North Atlantic oscillation
• Online Access: https://doi.org/10.5194/nhess-20-3225-2020; https://nhess.copernicus.org/articles/20/3225/2020/nhess-20-3225-2020.pdf; https://doaj.org/article/e6c3c515226c4678a5f9810c230fb5e4

This research examines the nonstationary dynamics of extreme surges along the English Channel coasts and seeks to make their connection to the climate patterns at different timescales by the use of a detailed spectral analysis in order to gain insights into the physical mechanisms relating the global atmospheric circulation to the local-scale variability of the monthly extreme surges. This variability highlights different oscillatory components from the interannual (∼1.5, ∼2–4, ∼5–8 years) to the interdecadal (∼12–16 years) scales with mean explained variances of ∼25 %–32 % and ∼2 %–4 % of the total variability, respectively. Using the two hypotheses that the physical mechanisms of the atmospheric circulation change according to the timescales and their connection with the local variability improves the prediction of the extremes, we have demonstrated statistically significant relationships of ∼1.5, ∼2–4, ∼5–8 and 12–16 years with the different climate oscillations of sea level pressure, zonal wind, North Atlantic Oscillation and Atlantic Multidecadal Oscillation, respectively. Such physical links have been used to implement the parameters of the time-dependent generalized extreme value (GEV) distribution models. The introduced climate information in the GEV parameters has considerably improved the prediction of the different timescales of surges with an explained variance higher than 60 %. This improvement exhibits their non-linear relationship with the large-scale atmospheric circulation.