Being one of the major consequences of anthropogenic climate change, sea level rise forms a threat for many coastal areas and their inhabitants. Because all processes that cause sea-level changes have a spatially-varying fingerprint, local sea-level changes deviate substantially from the global mean. As a consequence, there is no single location on the earth that is subject to the global-mean sea-level change. To understand and forecast future changes in both global and regional sea level, a thorough understanding of its major underlying processes and their regional fingerprints is necessary.
Nowadays, remote sensing from satellite altimetry provides an accurate estimate of changes in sea level on global and regional scales (Leuliette et al., 2004; Nerem et al., 2010; Ablain et al., 2017). The emergence of satellite gravimetry, in the form of the GRACE mission (Tapley et al., 2004), and the global coverage of in-situ subsurface temperature and salinity observations by the Argo programme (Roemmich et al., 2009; Roemmich and Gilson, 2009) has resulted in an extensive increase of our understanding of sea-level changes over the past decade, and the reliability of the estimates of the individual processes behind sea-level changes has reached the level where we can almost fully explain the observed sea-level changes from these contributors (Rietbroek et al., 2016; Leuliette and Miller, 2009; Dieng et al., 2015; Leuliette, 2015; Kleinherenbrink et al., 2016).
However, before this period the spatially-varying signals have been sampled only sparsely by in-situ observations, mainly by means of tide gauges, which limits our current understanding of sea-level changes on global and regional scales. This thesis aims to find an answer to the question whether the sum of the underlying processes that cause sea-level changes can explain the observations, not only on a global scale, which has been assessed a multitude of times (Moore et al., 2011; Church et al., 2011; Gregory et al., 2013; Jevrejeva et al., 2016b), but also on scales of individual ocean basins and coastal regions. The assessment of this so-called sea-level budget has been done for two regional cases, and for the global ocean and individual basins. Furthermore, the effect of ocean bottom deformation on the difference between relative and geocentric observations has been quantified. Finally, we have applied an alternative approach to time-series analysis, in which the various contributors of sealevel variability are co-estimated with a time-varying trend using a Kalman filter and smoother approach, on tide gauge observations.