Abstract
In coastal and semi-enclosed seas, the mean local sea level can significantly influence the magnitude of flooding in inundation areas. Using the cyclostationary empirical orthogonal function (CSEOF) method, we examine the spatial patterns and temporal variations of annual sea level cycle in the Baltic Sea based on satellite altimetry data, tide gauge data, and regional model reanalysis during 1993 and 2014. All datasets demonstrate coherent spatial and temporal annual sea level variability, although the model reanalysis shows a smaller interannual variation of annual sea level amplitude than other datasets. A large annual sea level cycle is observed in the Baltic Sea, except in the Danish straits from December to February. Compared with altimetry data, tide gauge data exhibit a stronger annual sea level cycle in the Baltic Sea (e.g., along the coasts and in the Gulf of Finland and the Gulf of Bothnia), particularly in the winter. Moreover, the maps of the maximum and minimum annual sea level amplitude imply that all datasets underestimate the maximum annual sea level amplitude. Analysis of the atmospheric forcing factors (e.g., sea level pressure, North Atlantic Oscillation (NAO), winds and air temperature), which may contribute to the interannual variation of the annual sea level cycle shows that both the zonal wind and winter NAO (e.g., from December to March) are highly correlated with the annual cycle variations in the tide gauge data in 1900–2012. In the altimetry era (1993–2014), all the atmospheric forcing factors are linked to the annual sea level cycle variations, particularly in 1996, 2010 and 2012, when a significant increase and drop of annual sea level amplitude are observed from all datasets, respectively.
Highlights
The understanding of coastal sea level variability is critical for human activities, economy, and safety in the low-lying regions
We aim to investigate the temporal variations and spatial patterns of the annual sea level cycle on the basis of satellite altimetry data, tide gauge data, and model reanalysis using the cyclostationary empirical orthogonal function (CSEOF) method to further clarify their physical origins in the Baltic Sea
Several stations located at the entrance of the Baltic Sea (e.g., Danish Straits) show maximum sea level in autumn, which may relate to local ocean dynamic conditions [26]
Summary
The understanding of coastal sea level variability is critical for human activities, economy, and safety in the low-lying regions. Stramska et al [11] found a well-pronounced seasonal cycle in the 18-year average sea level (1993–2010) at a specific location (55.44◦N, 18.33◦E) in the open Baltic Sea based on altimetry data. They found the average amplitude of annual sea level anomaly (SLA) to be approximately 18 cm and asymmetric in shape. Etcheverry et al [12] computed the annual signal from tide gauges and compared it with information derived from gridded satellite altimetry data Their results show that the root mean square differences (RMSds) between the datasets are up to 4 cm in the southern Baltic Sea and in regions occasionally covered by sea ice (e.g., the Gulf of Bothnia), and less than 1 cm in other regions
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