This work examines the multiscale variability in sea level along the English Channel coasts (NW France) using a wavelet multiresolution decomposition of water level values and climate oscillations in order to gain insights in the connection between the global atmospheric circulation and the local-scale variability of the monthly extreme surges. Changes in surges have exhibited different oscillatory components from the intermonthly (∼3–6-months) to the interannual scales (∼1.5-years, ∼2–4-years, ∼5–8-years) with mean explained variances of ∼40% and ∼25% of the total variability respectively. The correlation between the multiresolution components of surges and 28 exceptional stormy events with different intensities has revealed that energetic events are manifested at all timescales while moderate events are limited to short scales.

By considering the two hypotheses of (1) the physical mechanisms of the atmospheric circulation change according to the timescales and (2) their connection with the local variability improves the prediction of the extremes, the multiscale components of the monthly extreme surges have been investigated using four different climate oscillations (Sea Surface Temperature (SST), Sea-Level Pressure (SLP), Zonal Wind (ZW), and North Atlantic Oscillation (NAO)); results show statistically significant correlations with ∼3–6-months, ∼1.5-years, ∼2–4-years, and ∼5–8-years, respectively. Such physical links, from global to local scales, have been considered to model the multiscale monthly extreme surges using a time-dependent Generalized Extreme Value (GEV) distribution. The incorporation of the climate information in the GEV parameters has considerably improved the fitting of the different timescales of surges with an explained variance higher than 30%. This improvement exhibits their nonlinear relationship with the large-scale atmospheric circulation.

这项工作使用水位值和气候振荡的小波多分辨率分解方法研究了英吉利海峡沿岸海平面的多尺度变化，以了解全球大气环流与当地尺度变化之间的联系。每月的极端激增。从月际（〜3–6个月）到年际量表（〜1.5年，〜2-4年，〜5-8年），波动的变化表现出不同的振荡成分，平均解释方差为〜40总变异性的％和〜25％。潮汐的多分辨率分量与强度不同的28个异常暴风雨事件之间的相关性表明，高能事件在所有时间尺度上都表现出来，而中度事件则局限于短尺度上。

通过考虑以下两个假设（1）大气时空变化的物理机制根据时间尺度，以及（2）它们与局部变率的联系改善了对极端事件的预测，研究了月度极端波动的多尺度分量。四种不同的气候振荡（海面温度（SST），海平面压力（SLP），地带风（ZW）和北大西洋涛动（NAO））；结果显示分别与约3-6个月，约1.5年，约2-4年和约5-8年具有统计学意义的相关性。人们已经考虑了从全球到本地的这种物理联系，以使用时间相关的广义极值（GEV）分布来模拟多尺度每月极端潮。将气候信息纳入GEV参数已大大改善了不同浪涌时间尺度的拟合度，其解释方差高于30％。这种改善表现出它们与大规模大气环流的非线性关系。