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.