Spatial analysis of extreme sea states affecting Atlantic France: a critical assessment of the RFA approach

Abstract Spatial extremes assessment of geophysical variables represents a complex field largely because of the great variety of existing methodologies employed at different complexity levels, generally making use of multivariate techniques. This manuscript investigates the feasibility of a different approach, namely “Regional Frequency Analysis” (RFA), consisting into dividing the area of study into homogeneous regions whose normalized data are clustered and treated with univariate techniques. RFA is employed to analyse the spatial assessment of extreme significant wave heights within the north-east Atlantic Ocean. This expanse provides the physical basis for the determination of “homogeneous” regions, identified by means of typical storm footprints which allow the clustering of similar extreme events. Furthermore, a spatio-temporal criterion for storm tracking is implemented and incorporated into the analysis, since it is assumed that extreme marine events on a basin scale may be influenced by the same low pressure systems following similar trajectories. A 23-year wave hindcast database at high spatial resolution provided by the WWIII model on unstructured mesh grid covering the Celtic Sea, the English Channel and the Bay of Biscay was employed to perform the analysis. Due to the large size of the dataset (more than 110, 000 spatial locations), a limited number of points were selected, either uniformly or guided by the bathymetry). In both situations, RFA proves effective in clustering homogeneous regions physically and statistically. Its reliability is based on the varying impact of major meteorological events on different areas at different scales. The spatial assessment of return levels of significant wave heights achieved by means of RFA are consistent with results of a pointwise model, with findings generally more smoothed in proximity to steep gradients and when ranging from offshore to coastal areas. The adoption of a “spatio-temporal declustering” allows more detailed wave patterns to be reproduced on a smaller spatial scale, especially in the vicinity of channel systems. Effects of swell are also described accurately.