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Sea level rise (SLR) will increase adaptation needs along low-lying coasts worldwide. Despite centuries of experience with coastal risk, knowledge about the effectiveness and feasibility of societal adaptation on the scale required in a warmer world remains limited. This paper contrasts end-century SLR risks under two warming and two adaptation scenarios, for four coastal settlement archetypes (Urban Atoll Islands, Arctic Communities, Large Tropical Agricultural Deltas, Resource-Rich Cities). We show that adaptation will be substantially beneficial to the continued habitability of most low-lying settlements over this century, at least until the RCP8.5 median SLR level is reached. However, diverse locations worldwide will experience adaptation limits over the course of this century, indicating situations where even ambitious adaptation cannot sufficiently offset a failure to effectively mitigate greenhouse-gas emissions.

Change in Land Water Storage (LWS) is one of the main components driving sea-level rise over the twenty-first century. LWS alteration results from both human activities and climate change. Up to now, all components to sea-level change are usually quantified upon a certain climate change scenario except land water changes. Here, we propose to improve this by analyzing the contribution of LWS to regional sea-level change by considering five Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models forced by three different Representative Concentration Pathway (RCP) greenhouse gas emission scenarios. For this analysis, we used LWS output of the global hydrological and water resources model, PCR-GLOBWB 2, in order to project regional sea-level patterns. Projections of ensemble means indicate a range of LWS-driven sea-level rise with larger differences in projections among climate models than between scenarios. Our results suggest that LWS change will contribute around 10% to the projected global mean sea-level rise by the end of twenty-first century. Contribution of LWS to regional sea-level rise is projected to be considerably larger than the global mean over several regions, up to 60% higher than global average of LWS-driven sea-level rise, including the Pacific islands, the south coast of Africa and the west coast of Australia.

The accurate quantification of uncertainties in regional sea-level projections is essential for guiding policy makers. As climate models do not currently simulate total sea level, these uncertainties must be quantified through summation of uncertainties in individual sea-level components. This summation depends on the correlation between the components, which has previously been prescribed or derived from each individual component's dependence on global mean surface temperature. In this study, we quantify, for the first time, regional correlations between sea-level components based on regional climate change projections. We compute regional sea-level projections consistent with climate projections from an ensemble of 14 Earth System Models. From the multi-model spread, we estimate the uncertainty in the regional climate's response to greenhouse forcing. To quantify the total uncertainty, we add the uncertainty in the response of sea-level components to this regional climate change. This approach reveals how regional climate processes impose correlations between sea-level components, affecting the total uncertainty. One example is an anti-correlation between North Atlantic sterodynamic change and Antarctic dynamic mass loss, suggesting a teleconnection established by the large-scale ocean circulation. We find that prescribed correlations, applied in the fifth assessment report of the Intergovernmental Panel on Climate Change, lead to a global overestimation in the uncertainty in regional sea-level projections on the order of 20%. Regionally, this overestimation exceeds 100%. We conclude that accurate uncertainty estimates of regional sea-level change must be based on projections of regional climate change and cannot be derived from global indicators such as global mean surface temperature. publishedVersion