![]() ![]() So far, two-dimensional reconstructions of the sea level of the Baltic Sea were limited to a simple interpolation study ( Olivieri and Spada, 2016). The GIA effect is relatively well described by the regional uplift models, such as the most recent NKG2016LU ( Vestøl et al., 2019), and can thus be removed to obtain absolute sea level (ASL) change ( Richter K. The role of neotectonic and seismic movements is negligible in the area (e.g., Steffen and Wu, 2011). Observed RSL trends are dominated by the GIA, global sea level change and regional to local scale components ( Johansson et al., 2004). The Baltic Sea level varies on time scales from minutes and hours (e.g., waves and storm surges) to days, months and years, through preconditioning for storm surges, seasonal variability and variability related to e.g., North Atlantic Oscillation (the NAO Hünicke et al., 2015). Recent development in Global Isostatic Adjustment (GIA) modeling (e.g., Spada, 2017 Simon et al., 2018 Vestøl et al., 2019), use of satellite altimetry (e.g., Nerem et al., 2018) and sea surface reconstructions ( Meier et al., 2004 Madsen et al., 2015) have contributed to overcoming the above-mentioned problems. Finally, tide gauges are mostly coastal-bound and unevenly spaced, and thus, not entirely representative for the whole sea area (e.g., Woodworth, 2006). Their removal, on the other hand, requires the use of a truly fixed (geocentric) reference network. Nevertheless, a problem in quantification of general sea level trends is that traditional, tide gauge-based estimation of relative sea level (RSL) change is dependent on local, spatially varying land surface movements ( Santamaría-Gómez et al., 2017). ![]() Sea level measurement history in the Baltic Sea extends back to the 1770s, when tide gauge in Stockholm became operational ( Ekman, 1996). This is particularly true for the semi-enclosed seas like the Baltic Sea ( Hünicke et al., 2015 Suursaar and Kall, 2018). As the sea surface topography may dynamically vary in time and space in intricate patterns, the impact of climate change and of sea level change also occur differently in various areas on Earth ( Milne et al., 2009). Considering the relative shortness of the satellite era, natural variability made trend estimation sensitive to the selected data period, but the linear trends derived from the reconstruction (3.4 ± 0.7 mm/yr for 1993–2014) fitted with those of the CCI (4.0 ± 1.4 mm/yr for 1993–2015) and with global mean estimates within the limits of uncertainty.Ĭonsidering ongoing climate change, adequate quantification of the global pattern of sea level change is of crucial importance to helping societies cope with its adverse impact on the future ( IPCC, 2013). The area averaged absolute sea level change for the Baltic Sea was 1.3 ± 0.3 mm/yr for the 20th century, which was slightly below the global mean for the same period. This pattern was confirmed by independent observations and the values were provided along the entire coastline of the Baltic Sea. The reconstructed RSL change, which is important for coastal communities, was found to be dominated by isostatic land movements. However, areas with seasonal sea ice and areas of high natural variability need special treatment. The CCI matched reconstructed sea level variability with correlation above 90% and root-mean-square (RMS) difference below 6 cm in the southern and open part of the Baltic Proper. The validation allowed us to determine how close to the coast the CCI can be considered reliable. An assessment of the quality of an open ocean altimetry product (ESA Sea Level CCI ECV, hereafter “the CCI”) in this regional sea was performed by validating the variability against the reconstruction as an independent source of sea level information. The statistical reconstruction of sea level was based on multiple linear regression and took land deformation information into account. The reconstructed monthly sea level had an average correlation of 96% and root mean square error of 3.8 cm with 56 tide gauges independent of the statistical model. ![]() The reconstruction included both absolute and relative sea level (RSL) in 11 km resolution over the period 1900–2014. 2Estonian Marine Institute, University of Tartu, Tallinn, EstoniaĢD sea level trend and variability fields of the Baltic Sea were reconstructed based on statistical modeling of monthly tide gauge observations, and model reanalysis as a reference.1Danish Meteorological Institute, Copenhagen, Denmark.Høyer 1, Ülo Suursaar 2, Jun She 1 and Per Knudsen 3 ![]()
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