The sea level is changing around the world due to a combination of complex processes, such as changes in ocean density and circulation, the melt of ice sheets and glaciers, terrestrial water storage and vertical land motion. Projections of how much and how fast sea level will change are crucial information for adaptation planning. At the basis of most sea-level projections are global climate models, which can be used to simulate how different components of the Earth’s system, such as the ocean and the atmosphere, evolve as the greenhouse gas concentration in the atmosphere increases. However, differences between global climate models introduce uncertainties in sea-level projections. Additionally, due to their typically low grid resolution, such models poorly capture sea-level change in coastal regions in which small-scale bathymetric features and oceanic processes are important. Another uncertainty is natural sea-level variability, which can obscure long-term sea-level change in model simulations and observational records. In this thesis, the sea-level projections of two generations of global climate models (CMIP5 & CMIP6) are compared to understand how the increased climate sensitivity in CMIP6 affects sea-level projections. Additionally, regional ocean models are used to refine the simulations of two global climate models on the Northwestern European Shelf (dynamical downscaling) and to better understand the drivers of interannual sea-level variability in this region. Finally, global climate model simulations of future changes in the seasonal sea-level cycle on the Northwestern European Shelf are analyzed and explained using sensitivity tests performed with a regional climate model. Based on this research, this thesis concludes that embedding regional ocean models in sea-level science will help to improve the simulations of global climate models, to better understand the mechanisms behind sea-level change and variability and to provide stakeholders with the local sea-level information they need.
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