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.
This article aimed to provide an overview of relative and absolute sea level rise in the Baltic Sea based on different studies, where researchers have used data from tide gauges, satellite altimetry, sea level rise, and land uplift models. These results provide an opportunity to get an overview of the sea level rise in the Baltic Sea. However, to better understand the impact of sea level rise on the coastal area of the Baltic Sea, and especially in Estonia, two post-glacial land uplift models, the latest land uplift model NKG2016LU of the Nordic Commission of Geodesy (NKG) and Estonian land uplift model EST2020VEL, were used. These models enabled to eliminate post-glacial land uplift from absolute sea level rise. To determine the relative sea level rise in the coastal area of the Baltic Sea, the rates from land uplift models were compared to ESA’s BalticSEAL absolute sea level rise model. It was found that the relative sea level rise between 1995–2019 was −5 to 4.5 mm/yr (based on NKG2016LU) in the Baltic Sea. In addition, the southern area is more affected by relative sea level rise than the northern part. During the research, it was also found that the IPCC AR5 sea level projections predict a maximum relative sea level rise in the Baltic Sea by the year 2100 of between 0.3 to 0.7 m. As coastal areas in the southern part of the Baltic Sea are predominantly flat, the sea level may reach the real estate properties by the end of the 21st century. In the coastal area of Estonia, the relative sea level rise in the period 1995–2019 was −1.1 to 3.1 mm/yr (based on NKG2016LU) and −0.3 to 3.4 mm/yr (based on EST2020VEL), the difference between the land uplift models is −0.9 to 0.1 mm/y. In Estonia, the west and southwest area are most threatened by sea level rise, where the coast is quite flat. One of the largest cities in Estonia, Pärnu, is also located there. Using the ESA’s sea level and EST2020VEL land uplift models, it was found that the relative sea level rise will be 0.28 m by the year 2100. Based on the large spatial resolution IPCC AR5 sea level projections, the relative sea level rise will be on the same scale: 0.2–0.4 m.
The aim of this study was to estimate the noise properties, velocities, and their uncertainties from a time-series of selected (~9 years long) Estonian continuously operating Global Navigation Satellite System (GNSS) stations. Two software packages based on different processing methods, Gipsy–Oasis and Bernese, were used for daily coordinate calculations. Different methods and software (Tsview, Hector, and MIDAS) were used for coordinate time-series analysis. Outliers were removed using three different strategies. Six different stochastic noise models were used for trend estimation altogether with the analysis of the noise properties of the residual time-series with Hector. Obtained velocities were compared with different land uplift and glacial isostatic adjustment models (e.g., ICE-6G (VM5a), NKG2016LU, etc.). All compared solutions showed similar fit to the compared models. It was confirmed that the best fit to the time-series residuals were with the flicker noise plus white noise model (for the North and East component) and generalized Gauss–Markov model (for Up). Velocities from MIDAS, Tsview, and Hector solutions within the same time-series (Gipsy–Oasis or Bernese) agreed well but velocity uncertainties differed up to four times. The smallest uncertainties were obtained from Tsview; the MIDAS solution produced the most conservative values. Although the East and Up component velocities between Gipsy and Bernese solutions agreed well, the North component velocities were systematically shifted.
This study investigates the applicability of hydrodynamic leveling by means of contemporary pressure gauges for achieving geodetic accuracy in height determination. The main problems associated with pressure gauges are rigorous connection to a national leveling network and data processing, for example, determination of time-dependent drift and data filtering principles. The equipment and methodology were tested in a test area in the Baltic Sea. It can be concluded that the year-long sea level series may provide ±2.0 cm accuracy for hydrodynamic leveling within the water stretches up to 65 km. This is confirmed by alternative height determination methods and additional field experiments.