期刊名称：Tellus A: Dynamic Meteorology and Oceanography
电子版ISSN：1600-0870
出版年度：2016
卷号：68
期号：1
DOI：10.3402/tellusa.v68.30540
摘要：Abstract The seasonal cycle accounts for about 40% of the total sea level variability in the Baltic Sea. In a climate change context, changes are expected to occur, not only in mean levels but also in the seasonal characteristics of sea level. The present study addresses the quantification of changes in the seasonal cycle of sea level from a set of century-long tide gauge records in the Baltic Sea. In order to obtain robust estimates of the changes in amplitude and phase of the seasonal cycle, we apply different methods, including continuous wavelet filtering, multi-resolution decomposition based on the maximal overlap discrete wavelet transform, auto-regressive-based decomposition, singular spectrum analysis and empirical mode decomposition. The results show that all methods generally trace a similar long-term variability of the annual cycle amplitudes, and we focus on discrete wavelet analysis as the natural counterpart of classical moving Fourier analysis. In contrast to previous studies suggesting the existence of long-term changes in the seasonal cycle, in particular an increase of the annual amplitude, we find alternating periods of high and low amplitudes without any clear indication of systematic long-term trends. The derived seasonal patterns are spatially coherent, discriminating the stations in the Baltic entrance from the remaining stations in the Baltic basin, for which zonal wind accounts for typically more than 40% of the variations in amplitude.
