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Coastal areas are highly diverse, ecologically rich, regions of key socio-economic activity, and are particularly sensitive to sea-level change. Over most of the 20th century, global mean sea level has risen mainly due to warming and subsequent expansion of the upper ocean layers as well as the melting of glaciers and ice caps. Over the last three decades, increased mass loss of the Greenland and Antarctic ice sheets has also started to contribute significantly to contemporary sea-level rise. The future mass loss of the two ice sheets, which combined represent a sea-level rise potential of ∼65 m, constitutes the main source of uncertainty in long-term (centennial to millennial) sea-level rise projections. Improved knowledge of the magnitude and rate of future sea-level change is therefore of utmost importance. Moreover, sea level does not change uniformly across the globe and can differ greatly at both regional and local scales. The most appropriate and feasible sea level mitigation and adaptation measures in coastal regions strongly depend on local land use and associated risk aversion. Here, we advocate that addressing the problem of future sea-level rise and its impacts requires (i) bringing together a transdisciplinary scientific community, from climate and cryospheric scientists to coastal impact specialists, and (ii) interacting closely and iteratively with users and local stakeholders to co-design and co-build coastal climate services, including addressing the high-end risks., Astrodynamics & Space Missions

Sea level rise (SLR) is a long-lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process-based models. However, risk-averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high-end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high-end scenarios. High-end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1-2.6) relative to pre-industrial values our high-end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5-8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long-term benefits of mitigation. However, even a modest 2°C warming may cause multi-meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high-end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high-end SLR., SCOPUS: ar.j, info:eu-repo/semantics/published

Despite widespread efforts to implement climate services, there is almost no literature that systematically analyzes users' needs. This paper addresses this gap by applying a decision analysis perspective to identify what kind of mean sea level rise (SLR) information is needed for local coastal adaptation decisions. We first characterize these decisions, then identify suitable decision analysis approaches and the sea level information required, and finally discuss if and how these information needs can be met given the state of the art of sea level science. We find that four types of information are needed: (i) probabilistic predictions for short-term decisions when users are uncertainty tolerant; (ii) high-end and low-end SLR scenarios chosen for different levels of uncertainty tolerance; (iii) upper bounds of SLR for users with a low uncertainty tolerance; and (iv) learning scenarios derived from estimating what knowledge will plausibly emerge about SLR over time. Probabilistic predictions can only be attained for the near term (i.e., 2030-2050) before SLR significantly diverges between low and high emission scenarios, for locations for which modes of climate variability are well understood and the vertical land movement contribution to local sea levels is small. Meaningful SLR upper bounds cannot be defined unambiguously from a physical perspective. Low- to high-end scenarios for different levels of uncertainty tolerance and learning scenarios can be produced, but this involves both expert and user judgments. The decision analysis procedure elaborated here can be applied to other types of climate information that are required for mitigation and adaptation purposes.

Sea-level rise (SLR) can modify not only total water levels, but also tidal dynamics. Several studies have investigated the effects of SLR on the tides of the western European continental shelf (mainly the M2 component). We further investigate this issue using a modelling-based approach, considering uniform SLR scenarios from −0.25 m to +10 m above present-day sea level. Assuming that coastal defenses are constructed along present-day shorelines, the patterns of change in high tide levels (annual maximum water level) are spatially similar, regardless of the magnitude of sea-level rise (i.e., the sign of the change remains the same, regardless of the SLR scenario) over most of the area (70%). Notable increases in high tide levels occur especially in the northern Irish Sea, the southern part of the North Sea and the German Bight, and decreases occur mainly in the western English Channel. These changes are generally proportional to SLR, as long as SLR remains smaller than 2 m. Depending on the location, they can account for +/−15% of regional SLR. High tide levels and the M2 component exhibit slightly different patterns. Analysis of the 12 largest tidal components highlights the need to take into account at least the M2, S2, N2, M4, MS4 and MN4 components when investigating the effects of SLR on tides. Changes in high tide levels are much less proportional to SLR when flooding is allowed, in particular in the German Bight. However, some areas (e.g., the English Channel) are not very sensitive to this option, meaning that the effects of SLR would be predictable in these areas, even if future coastal defense strategies are ignored. Physically, SLR-induced tidal changes result from the competition between reductions in bed friction damping, changes in resonance properties and increased reflection at the coast, i.e., local and non-local processes. A preliminary estimate of tidal changes by 2100 under a plausible non-uniform SLR scenario (using the RCP4.5 scenario) is provi