Spatial and temporal wave climate variability along the south coast of Sweden during 1959–2021 - Adell, Anna; Almström, Björn; Kroon, Aart; Larson, Magnus; Uvo, Cintia Bertacchi; Hallin, Caroline (Elsevier BV, 2023)
Highlights • 62-year wave climate hindcast derived for the southern Baltic Sea using SWAN. • SWAN was validated using public wave datasets and new nearshore measurements. • Westerly directions dominate most annual wave fields. • Annual wave energy and wave direction are correlated to the winter NAO index. Abstract This study presents 62 years of hindcast wave climate data for the south coast of Sweden from 1959–2021. The 100-km-long coast consists mainly of sandy beaches and eroding bluffs interrupted by headlands and harbours alongshore, making it sensitive to variations in incoming wave direction. A SWAN wave model of the Baltic Sea, extending from the North Sea to the Åland Sea, was calibrated and validated against wave observations from 16 locations distributed within the model domain. Wave data collected from open databases were complemented with new wave buoy observations from two nearshore locations within the study area at 14 and 15 m depth. The simulated significant wave height showed good agreement with the local observations, with an average R2 of 0.83. The multi-decadal hindcast data was used to analyse spatial and temporal wave climate variability. The results show that the directional distribution of incoming waves varies along the coast, with a gradually increasing wave energy exposure from the west towards the east. The wave climate is most energetic from October to March, with the highest wave heights in November, December, and January. In general, waves from westerly directions dominate the annual wave energy, but within the hindcast time series, a few years had larger wave energy from easterly directions. The interannual variability of total wave energy and wave direction is correlated to the North Atlantic Oscillation (NAO) index. In the offshore, the total annual wave energy had a statistically significant positive correlation with the NAO DJFM station-based index, with a Spearman rank correlation coefficient of 0.51. In the nearshore, the correlation was even stronger. Future studies should ...