Linking large-scale climate modes to local wave climate and storm surge: insights from a weather typing approach

Abstract

Understanding temporal variations in nearshore sea states is crucial, as they affect shoreline evolution and coastal hazard potential. Local sea state conditions are influenced by large-scale climate modes, yet the underlying mechanisms remain not fully understood. Previous studies have mainly established the climate–sea state links through correlation analyses or other statistical methods. This study investigates whether weather typing, a statistical downscaling method, can provide a physically interpretable link between climate modes and local wave and storm surge variability. The analysis was conducted at Hartlepool, UK, where 36 weather types were previously developed to assess the exposure to coastal hazards for a local nuclear power station. Six climate indices were examined, and we found that the North Atlantic Oscillation (NAO) and the Scandinavian pattern (SCAND) have significant correlations with local wave and storm surge variables. The analysis reveals that, in response to the phases of NAO or SCAND, storm surge distributions exhibit changes in the mean and standard deviation, peak wave period distributions shift between bimodal and near-unimodal shapes, and wind waves and swell show different dominant directions. Using weather types, these response patterns can be traced back to synoptic circulation conditions characterized by different prevailing winds, spatial patterns of storm activity, and local atmospheric pressure. NAO and SCAND modify the occurrence probabilities of these synoptic conditions, thereby providing a probabilistic link between large-scale climate modes and local sea states. This research demonstrates the potential of weather types to offer new perspectives on the impact of climate modes on local sea states.