Storm Frequency in the Northern Baltic Sea Region and its Association to the North Atlantic Oscillation

• Main Author: Arra, Venni
• Format: Bachelor Thesis
• Language: English
• Published: Stockholms universitet, Institutionen för naturgeografi 2018
• Subjects: Climate; Wind; Storm Frequency; Baltic Sea; NAO; Natural Sciences; Naturvetenskap; Physical Geography; Naturgeografi; Climate Research; Klimatforskning; Meteorology and Atmospheric Sciences; Meteorologi och atmosfärforskning; North Atlantic; North Atlantic oscillation
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-165907

Storms can be both destructive and valuable at the same time. They expose coastal areas to various risks but can also enhance the supply of wind energy and provide marine ecosystems with oxygen rich water. As the North Atlantic Oscillation (NAO) is known to have a significant impact on the wind climate in Europe, investigating its interconnection to storm frequency and intensity under global warming circumstances in the Northern Baltic Sea region was of interest in this study. Wind speed data series of annual storm counts were obtained from five meteorological stations along with PC-based NAO values over the period 1960-2017. The data series were analysed in Microsoft Excel and modelled using a Poisson regression or negative binomial regression model in SPSS Statistics. The results display an unsystematic spatial pattern both in the association to the NAO as well as in the overall storm frequency. However, storm (≥ 21 m s-1) frequency has generally been decreasing, whereas the proportion of severe storms (≥ 24 m s-1) has slightly been increasing, suggesting a tendency toward stronger but fewer storms. Even though only certain data series display statistically significant findings (p ≤ .05), a majority of the winter storms and severe winter storms display a positive association, indicating that a higher NAOI is related to a greater number of winter storms. The spatial and temporal variability in the obtained results can partially be explained by storm tracks and prevalent wind directions. Nevertheless, inhomogeneities do presumably affect the wind speed observations through internal and external influences and changes related to the meteorological stations. Future research should, therefore, also consider integrating other storm related parameters, such as direct air pressure measurements, wave heights and storm surges, as well as implement different data homogenization methods and techniques.