Investigation of sea level variability in the Baltic Sea from tide gauge, satellite altimeter data, and model reanalysis

2015 ◽  
Vol 36 (10) ◽  
pp. 2548-2568 ◽  
Author(s):  
Qing Xu ◽  
Yongcun Cheng ◽  
Hans-Peter Plag ◽  
Biao Zhang
2021 ◽  
Author(s):  
Ida Margrethe Ringgaard ◽  
Jacob L. Høyer ◽  
Kristine S. Madsen ◽  
Adili Abulaitijiang ◽  
Ole B. Andersen

<p>The rise and fall of the sea surface in the coastal region is observed closely by two different sources: tide gauges measure the relative sea level anomaly at the coast at high temporal resolution (minutes or hours) and satellite altimeters measure the absolute sea surface height of the open ocean along tracks multiple times a day. However, these daily tracks are scattered across the Baltic Sea with each track being repeated at a lower temporal resolution (days). Due to the inverse relationship between spatial and temporal coverage of the satellite altimetry data, gridded satellite altimetry products often prioritize spatial coverage over temporal resolution, thus filtering out the high sea level variability. In other words, the satellite data, and especially averaged products, often miss the daily sea level variability, such as storm surges, which is most important for all societies in the coastal region. To compensate for the sparse spatial coverage from satellite altimetry, we here present an experimental product developed as part of the ESA project Baltic+SEAL:  on a 3-day scale, the DMI Optimal Interpolation (DMI-OI) method is combined with error statistics from a storm surge model as well as 3-day averages from both tide gauge observations and satellite altimetry tracks to generate a gridded sea level anomaly product for the Baltic Sea for year 2017. The product captures the overall temporal evolution of the sea level changes well for most areas with an average RMSE wrt. tide gauge observations of 17.2 cm and a maximum of 34.2 cm. Thus, the 3-day mean gridded product shows potential as an alternative to monthly altimetry products, although further work is needed.</p>


2020 ◽  
Vol 12 (24) ◽  
pp. 4062
Author(s):  
Aive Liibusk ◽  
Tarmo Kall ◽  
Sander Rikka ◽  
Rivo Uiboupin ◽  
Ülo Suursaar ◽  
...  

Multi-mission satellite altimetry (e.g., ERS, Envisat, TOPEX/Poseidon, Jason) data have enabled a synoptic-scale view of ocean variations in past decades. Since 2016, the Sentinel-3 mission has provided better spatial and temporal sampling compared to its predecessors. The Sentinel-3 Ku/C Radar Altimeter (SRAL) is one of the synthetic aperture radar altimeters (SAR Altimeter) which is more precise for coastal and lake observations. The article studies the performance of the Sentinel-3 Level-2 sea level altimetry products in the coastal areas of the Baltic Sea and on two lakes of Estonia. The Sentinel-3 data were compared with (i) collocated Global Navigation Satellite System (GNSS) ship measurements, (ii) the Estonian geoid model (EST-GEOID2017) together with sea-level anomaly corrections from the tide gauges, and (iii) collocated buoy measurements. The comparisons were carried out along seven Sentinel-3A/B tracks across the Baltic Sea and Estonian lakes in 2019. In addition, the Copernicus Marine Environment Monitoring Service (CMEMS) Level-3 sea-level products and the Nucleus for European Modelling of the Ocean (NEMO) reanalysis outcomes were compared with measurements from Estonia’s 21 tide gauges and the buoy deployed offshore. Our results showed that the uncertainty of the Sentinel-3 Level-2 altimetry product was below decimetre level for the seacoast and the selected lakes of Estonia. Results from CMEMS Level-3 altimetry products showed a correlation of 0.83 (RMSE 0.18 m) and 0.91 (RMSE 0.27 m) when compared against the tide gauge measurements and the NEMO model, respectively. The overall performance of the altimetry products was very good, except in the immediate vicinity of the coastline and for the lakes, where the accuracy was nearly three times lower than for the open sea, but still acceptably good.


2020 ◽  
Vol 12 (22) ◽  
pp. 3747
Author(s):  
Thomas Gruber ◽  
Jonas Ågren ◽  
Detlef Angermann ◽  
Artu Ellmann ◽  
Andreas Engfeldt ◽  
...  

Traditionally, sea level is observed at tide gauge stations, which usually also serve as height reference stations for national leveling networks and therefore define a height system of a country. One of the main deficiencies to use tide gauge data for geodetic sea level research and height systems unification is that only a few stations are connected to the geometric network of a country by operating permanent GNSS receivers next to the tide gauge. As a new observation technique, absolute positioning by SAR using active transponders on ground can fill this gap by systematically observing time series of geometric heights at tide gauge stations. By additionally knowing the tide gauge geoid heights in a global height reference frame, one can finally obtain absolute sea level heights at each tide gauge. With this information the impact of climate change on the sea level can be quantified in an absolute manner and height systems can be connected across the oceans. First results from applying this technique at selected tide gauges at the Baltic coasts are promising but also exhibit some problems related to the new technique. The paper presents the concept of using the new observation type in an integrated sea level observing system and provides some early results for SAR positioning in the Baltic sea area.


1997 ◽  
Vol 15 (11) ◽  
pp. 1478-1488 ◽  
Author(s):  
G. Chen ◽  
R. Ezraty

Abstract. It is becoming well known that aliasing associated with ocean tides could be a major source of systematic error in altimeter sea-level measurements, due to asynoptic sampling and imperfect tide modelling. However, it has been shown that signals of non-tidal origin may also contribute significantly to the observed aliasing. In this paper, numerical simulations are performed to demonstrate the full aliasing potential associated with altimeter observations of seasonal sea-level variability and annual Rossby waves. Our results indicate that ignorance of non-tidal aliasing may lead to the possibility of underestimating the total aliasing and misinterpreting or overlooking existing geophysical phenomena. Therefore, it is argued that an entire aliasing picture should be kept in mind when satellite altimeter data are analysed.


2018 ◽  
Vol 9 (1) ◽  
pp. 69-90 ◽  
Author(s):  
Sitar Karabil ◽  
Eduardo Zorita ◽  
Birgit Hünicke

Abstract. The main purpose of this study is to quantify the contribution of atmospheric factors to recent off-shore sea-level variability in the Baltic Sea and the North Sea on interannual timescales. For this purpose, we statistically analysed sea-level records from tide gauges and satellite altimetry and several climatic data sets covering the last century. Previous studies had concluded that the North Atlantic Oscillation (NAO) is the main pattern of atmospheric variability affecting sea level in the Baltic Sea and the North Sea in wintertime. However, we identify a different atmospheric circulation pattern that is more closely connected to sea-level variability than the NAO. This circulation pattern displays a link to sea level that remains stable through the 20th century, in contrast to the much more variable link between sea level and the NAO. We denote this atmospheric variability mode as the Baltic Sea and North Sea Oscillation (BANOS) index. The sea-level pressure (SLP) BANOS pattern displays an SLP dipole with centres of action located over (5° W, 45° N) and (20° E, 70° N) and this is distinct from the standard NAO SLP pattern in wintertime. In summertime, the discrepancy between the SLP BANOS and NAO patterns becomes clearer, with centres of action of the former located over (30° E, 45° N) and (20° E, 60° N). This index has a stronger connection to off-shore sea-level variability in the study area than the NAO in wintertime for the period 1993–2013, explaining locally up to 90 % of the interannual sea-level variance in winter and up to 79 % in summer. The eastern part of the Gulf of Finland is the area where the BANOS index is most sensitive to sea level in wintertime, whereas the Gulf of Riga is the most sensitive region in summertime. In the North Sea region, the maximum sea-level sensitivity to the BANOS pattern is located in the German Bight for both winter and summer seasons. We investigated, and when possible quantified, the contribution of several physical mechanisms which may explain the link between the sea-level variability and the atmospheric pattern described by the BANOS index. These mechanisms include the inverse barometer effect (IBE), freshwater balance, net energy surface flux and wind-induced water transport. We found that the most important mechanism is the IBE in both wintertime and summertime. Assuming a complete equilibration of seasonal sea level to the SLP gradients over this region, the IBE can explain up to 88 % of the sea-level variability attributed to the BANOS index in wintertime and 34 % in summertime. The net energy flux at the surface is found to be an important factor for the variation of sea level, explaining 35 % of sea-level variance in wintertime and a very small amount in summer. The freshwater flux could only explain 27 % of the variability in summertime and a negligible part in winter. In contrast to the NAO, the direct wind forcing associated with the SLP BANOS pattern does not lead to transport of water from the North Sea into the Baltic Sea in wintertime.


2016 ◽  
Vol 59 (3) ◽  
Author(s):  
Marco Olivieri ◽  
Giorgio Spada

<p>Exploiting the Delaunay interpolation, we present a newly implemented 2-D sea-level reconstruction from coastal sea-level observations to open seas, with the aim of characterizing the spatial variability of the rate of sea-level change. To test the strengths and weaknesses of this method and to determine its usefulness in sea-level interpolation, we consider the case studies of the Baltic Sea and of the Pacific Ocean. In the Baltic Sea, a small basin well sampled by tide gauges, our reconstructions are successfully compared with absolute sea-level observations from altimetry during 1993-2011. The regional variability of absolute sea level observed across the Pacific Ocean, however, cannot be reproduced. We interpret this result as the effect of the uneven and sparse tide gauge data set and of the composite vertical land movements in and around the region. Useful considerations arise that can serve as a basis for developing sophisticated approaches.</p>


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