Detecting long-term changes in extreme wave climate is essential for coastal engineering and hazard assessment, yet robust trend identification remains challenging due to strong natural variability and limited observational records. This study evaluates the robustness of trend detection in wave conditions along the Bay of Biscay using in situ measurements for a direct comparison with atmospheric climate indices such as North Atlantic Oscillation (NAO), East Atlantic pattern (EA), and El Niño-Southern Oscillation index (ENSO). A 32-year-long deep-water buoy record of wave parameters (1990–2022) is first analyzed and systematically compared with a nearby and shorter record (2007–2018) to quantify the influence of record length on extreme value estimates and trend inference. Extreme events are identified using a peak-over-threshold approach, and trends in significant wave height (HS), peak period (TP), wave steepness (S), and storm-related metrics are assessed through non-parametric methods. No statistically significant long-term trend is detected in the monthly averaged HS. In contrast, significant increases are found in storm frequency and storm wave power, together with a decreasing trend in TP and increasing wave steepness, indicating changes in storminess rather than in wave height alone. The shorter record exhibits substantially wider confidence intervals in return levels and inconsistent trend signals, highlighting the structural sensitivity of statistics to temporal coverage. Additionally, correlation analysis with large-scale atmospheric indices reveals that wave-parameters variability is more closely associated with the EA pattern than with the NAO or the ENSO, although the overall explained variance remains limited.
Viñes et al. (Tue,) studied this question.