Linking regional extreme sea level variability in North-Western Europe to large scale climate modes

Extreme sea level (ESL) events pose the highest risk to coastal communities and infrastructure, with their frequency and intensity projected to increase in the future. These events result from a combination of tidal height, mean sea level, wave height, and storm contributions. However, the spatiotemporal variability of regional extreme sea-level events and its connection to climate teleconnections and large-scale weather processes remain poorly understood.
In this work, we demonstrate that regional ESL variability can be attributed to large-scale teleconnections and traced back to atmospheric and oceanographic patterns in the North-Atlantic. 

Applying Empirical Orthogonal Function (EOF) analysis on the daily maximum of hourly detrended and detided sea level from the CODEC dataset, we found that the first three modes explain 90% of the variance (53%, 20%, and 9%, respectively).  Clustering using Gaussian Mixture models reveals five distinct regions of sea level variability. The top three EOF modes show significant correlations using linear regression with climate indices, most significantly the North Atlantic Oscillation, Arctic Oscillation, and the Eastern Atlantic. Composite analysis of these modes attributes each mode variability to large-scale atmospheric and oceanographic variables. This highlights significant weather patterns in the North Atlantic, connecting non-local weather sources to regional variability of sea level extremes.

Our findings illustrate how regional sea level variability is driven by large-scale weather and climate patterns. By linking distinct spatial modes to significant drivers and changes in weather variables, we provide new insights on the causes and climatology of high sea levels. This understanding offers valuable applications for early warning systems and coastal planning. Furthermore, understanding the drivers of ESL variability can improve long-term predictions of regional coastal flooding risk. Given the global nature of ESL events and the increasing need for adaptation, our research contributes to a critical foundation for future resilience planning.