Influence of long-term regional and large-scale atmospheric circulation on the Baltic sea level

2002 ◽  
Vol 54 (1) ◽  
pp. 76-88 ◽  
Author(s):  
HELEN C. ANDERSSON
2020 ◽  
Author(s):  
Piia Post ◽  
Andreas Lehmann

<p>A detailed assessment of climate variability of the Baltic Sea area for the period 1958-2008 (Lehmann et al. 2011) revealed that changes in the warming trend since the mid-1980s, were associated with changes in the large-scale atmospheric circulation over the North Atlantic. The analysis of winter sea level pressure (SLP) data highlighted considerable changes in intensification and location of storm tracks, in parallel with the eastward shift of the North Atlantic Oscillation (NAO) centres of action. Additionally, a seasonal shift of strong wind events from autumn to winter and early spring exists for the Baltic area. Lehmann et al. (2002) showed that different atmospheric circulation regimes force different circulation patterns in the Baltic Sea. Furthermore, as atmospheric circulation, to a large extent, controls patterns of water circulation and biophysical aspects relevant for biological production, such as the vertical distribution of temperature and salinity, alterations in weather regimes may severely impact the trophic structure and functioning of marine food webs (Hinrichsen et al. 2007). To understand the processes linking changes in the marine environment and climate variability, it is essential to investigate all components of the climate system which of course include also the large-scale atmospheric circulation. Now, since extended time series data (1948-2018) for additional 20 years are available, it is interesting to investigate recent changes/shifts of the large-scale atmospheric conditions and their impact on the wind climate over the Baltic Sea area.</p>


2021 ◽  
Vol 288 (1949) ◽  
Author(s):  
Johan Östergren ◽  
Stefan Palm ◽  
John Gilbey ◽  
Göran Spong ◽  
Johan Dannewitz ◽  
...  

Intra-species genetic homogenization arising from anthropogenic impacts is a major threat to biodiversity. However, few taxa have sufficient historical material to systematically quantify long-term genetic changes. Using archival DNA collected over approximately 100 years, we assessed spatio-temporal genetic change in Atlantic salmon populations across the Baltic Sea, an area heavily impacted by hydropower exploitation and associated with large-scale mitigation stocking. Analysis was carried out by screening 82 SNPs in 1680 individuals from 13 Swedish rivers. We found an overall decrease in genetic divergence and diminished isolation by distance among populations, strongly indicating genetic homogenization over the past century. We further observed an increase in genetic diversity within populations consistent with increased gene flow. The temporal genetic change was lower in larger wild populations than in smaller wild and hatchery-reared ones, indicating that larger populations have been able to support a high number of native spawners in relation to immigrants. Our results demonstrate that stocking practices of salmon in the Baltic Sea have led to the homogenization of populations over the last century, potentially compromising their ability to adapt to environmental change. Stocking of reared fish is common worldwide, and our study is a cautionary example of the potentially long-term negative effects of such activities.


2017 ◽  
Vol 8 (4) ◽  
pp. 1031-1046 ◽  
Author(s):  
Sitar Karabil ◽  
Eduardo Zorita ◽  
Birgit Hünicke

Abstract. Coastal sea-level trends in the Baltic Sea display decadal-scale variations around a long-term centennial trend. In this study, we analyse the spatial and temporal characteristics of the decadal trend variations and investigate the links between coastal sea-level trends and atmospheric forcing on a decadal timescale. For this analysis, we use monthly means of sea-level and climatic data sets. The sea-level data set is composed of long tide gauge records and gridded sea surface height (SSH) reconstructions. Climatic data sets are composed of sea-level pressure, air temperature, precipitation, evaporation, and climatic variability indices. The analysis indicates that atmospheric forcing is a driving factor of decadal sea-level trends. However, its effect is geographically heterogeneous. This impact is large in the northern and eastern regions of the Baltic Sea. In the southern Baltic Sea area, the impacts of atmospheric circulation on decadal sea-level trends are smaller. To identify the influence of the large-scale factors other than the effect of atmospheric circulation in the same season on Baltic Sea sea-level trends, we filter out the direct signature of atmospheric circulation for each season separately on the Baltic Sea level through a multivariate linear regression model and analyse the residuals of this regression model. These residuals hint at a common underlying factor that coherently drives the decadal sea-level trends in the whole Baltic Sea. We found that this underlying effect is partly a consequence of decadal precipitation trends in the Baltic Sea basin in the previous season. The investigation of the relation between the AMO index and sea-level trends implies that this detected underlying factor is not connected to oceanic forcing driven from the North Atlantic region.


2020 ◽  
Author(s):  
Svenja Bierstedt ◽  
Eduardo Zorita ◽  
Birgit Hünicke

<p>The coastlines of the Baltic Sea and Indonesia are both relatively complex, so that the estimation of extreme sea levels caused by the atmospheric forcing becomes complex with conventional methods. Here, we explore whether Machine Learning methods can provide a model surrogate to compute more rapidly daily extremes in sea level from large-scale atmosphere-ocean fields. We investigate the connections between the atmospheric and ocean drivers of local extreme sea level in South East Asia and along the Baltic Sea based on statistical analysis by Random Forest Models, driven by large-scale meteorological predictors and daily extreme sea level measured by tide-gauge records over the last few decades.</p><p>First results show that in some Indonesian areas extremes are driven by large-scale climate fields; in other areas they are incoherently driven by local processes. An area where random forest predicted extremes show good correspondence to observed extremes is found to be the Malaysian coastline. For the Indonesian coasts, the Random Forest Algorithm was unable to predict extreme sea levels in line with observations. Along the Baltic Sea, in contrast, the Random Forest model is able to produce reasonable estimations of extreme sea levels based on the large-scale atmospheric fields. An analysis of the interrelations of extreme sea levels in the South Asia regions suggests that either the data quality may be compromised in some regions or that other forcing factors, distinct from the large-scale atmospheric fields, may also be involved.</p>


1973 ◽  
Vol 4 (1) ◽  
pp. 41-53 ◽  
Author(s):  
EUGENIE LISITZIN

An attempt is made to compute the sea level variations in the Gulf of Bothnia, which is isolated by islands and thresholds from the Baltic Sea proper. Observations from tide gauges during the 30-year period 1931–1960 were used. The effect of land uplift was taken into consideration. The maximum annual deviation in water volume from the long-term mean corresponded to 20.74 km3..


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