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Abstract Beside climate‐change‐induced sea‐level rise (SLR), land subsidence can strongly amplify coastal risk in flood‐prone areas. Mapping and quantifying contemporary vertical land motion (VLM) at continental scales has long been a challenge due to the absence of gridded observational products covering these large domains. Here, we fill this gap by using the new European Ground Motion Service (EGMS) to assess the current state of coastal VLM in Europe. First, we compare the InSAR‐based EGMS Ortho (Level 3) with nearby global navigation satellite systems (GNSS) vertical velocity estimates and show that the geodetic reference frame used to calibrate EGMS strongly influences coastal vertical land velocity estimates at the millimeter per year level and this needs to be considered with caution. After adjusting the EGMS vertical velocity estimates to a more updated and accurate International Terrestrial Reference Frame (ITRF2014), we performed an assessment of VLM in European low elevation coastal flood plains (CFPs). We find that nearly half of the European CFP area is, on average, subsiding at a rate faster than 1 mm/yr. More importantly, we find that urban areas and populations located in the CFP experience a near −1 mm/yr VLM on average (excluding the uplifting Fennoscandia region). For harbors, the average VLM is even larger and increases to −1.5 mm/yr on average. This demonstrates the widespread importance of continental‐scale assessments based on InSAR and GNSS to better identify areas at higher risk from relative SLR due to coastal subsidence.

Abstract As sea levels are rising, the number of chronic flooding events at high tide is increasing across the world coastlines. Yet, many events reported so far either lack observational evidence of flooding, or relate to coastal areas where ground subsidence or oceanic processes often enhance climate change-induced sea-level rise (SLR). Here we present observational and modelling evidence of high-tide flooding events that are unlikely to occur without SLR in French Guiana, where sea-level rise rates are close to the global average and where there is no significant ground subsidence. In particular, on 16 October 2020, a well-documented flooding event happened in Cayenne under calm weather conditions. Our probabilistic assessment of daily maximum water levels superimposed on SLR shows that this event can be modelled and is a consequence of SLR. As sea levels will continue to rise, we show that the number, severity and extent of such high-tide flooding events will increase across several urban areas of French Guiana, with an evolution depending on the topography. As concerns are growing regarding the economic impacts and adaptation challenges of high-tide chronic events across the world, our study provides new evidence that this early impact of SLR is emerging now.

Abstract On behalf of the journal, AGU, and the scientific community, we, the editors of Earth's Future, are delighted to publish the names of the 817 peer reviewers who provided 1,242 reviews for our journal in 2023 (italicized names have contributed three or more reviews). Your diligent efforts to provide timely comments on our submissions have significantly improved the manuscripts and elevated the scientific rigor of future research. As a unique transdisciplinary journal, Earth's Future delves into the state of the planet and its inhabitants, sustainable and resilient societies, the science of the Anthropocene, and predictions of our shared future through research articles, reviews, and commentaries. In the face of observed and anticipated global environmental and climatic changes, the need for high‐quality scientific theories, assessments, and projections about the future of our planet has never been more pressing. To safeguard research integrity in this crucial area, we rely on our reviewers' expertise and selfless cooperation. We extend our heartfelt thanks to each of the individuals listed below for their contributions to our journal and the broader scientific discourse. Your dedication is immensely appreciated.

Elevating parts or the entirety of the structure of buildings in exposed coastal areas can be an effective way of managing the growing risks associated with climate change and sea level rise. While these accommodation measures are well known, there is little to no research on their role in coastal adaptation policy in Europe or on accommodation taking place at all. A systematic review of grey literature was carried out in metropolitan France, the UK and Ireland to assess the current state of structural accommodation. The analysis shows that although measures such as the raising of floor levels of new developments are common practice as part of property-level resilience and flood risk management on the coasts of the three studied countries, accommodation remains driven by local spatial planning and poorly integrated in overarching adaptation policies. Accommodation is found to be unevenly distributed along the assessed coasts and in many locations is happening in protected or sheltered locations to manage residual risk. Comparisons with the experience from the US – where elevated buildings have been an established strategy for over 50 years – suggest that accommodation could be enhanced by providing guidelines that better account for coastal processes such as the impacts of waves, as well as by promoting financial incentives through subsidies or insurance schemes. National coastal adaptation policies are rapidly evolving in Europe and could benefit from a better understanding of the advantages and limitations of accommodation by elevating buildings.

Abstract We produce projections of global mean sea‐level rise to 2500 for low and medium emissions scenarios (Shared Socioeconomic Pathways SSP1‐2.6 and SSP2‐4.5) relative to 2020, based on extending and combining model ensemble data from current literature. We find that emissions have a large effect on sea‐level rise on these long timescales, with [5, 95]% intervals of [0.3, 4.3]m and [1.0, 7.6]m under SSP1‐2.6 and SSP2‐4.5 respectively, and a difference in the 95% quantile of 1.6 m at 2300 and 3.3 m at 2500 for the two scenarios. The largest and most uncertain component is the Antarctic ice sheet, projected to contribute 5%–95% intervals of [−0.1, 2.3]m by 2500 under SSP1‐2.6 and [0.0, 3.8]m under SSP2‐4.5. We discuss how the simple statistical extensions used here could be replaced with more physically based methods for more robust predictions. We show that, despite their uncertainties, current multi‐centennial projections combined into multi‐study projections as presented here can be used to avoid future “lock‐ins” in terms of risk and adaptation needs to sea‐level rise.

This perspective paper reports the results of a collaborative survey of French research institutes concerned with environmental issues, which examined the potential for a market uptake of climate services for adaptation in France. The study is based on a review of existing reports on the market of climate services, and on interviews of 68 climate service providers and users in public and private organizations. Although the study does not allow to provide quantified estimations regarding the present and future size of the market, its results offer new perspectives with implications extending far beyond the sole case of France: first, while the market is still in its infancy, significant opportunities exist in sectors such as flooding risks, and, to a slightly lesser extent, hydro and nuclear energy and viticulture. In addition, the study identifies critical conditions for the uptake in climate services: (1) a coordinated delivery of data, information, expertise and training by public research institutes concerned with climate change and its impacts; (2) the inclusion of adaptation in the regulation and in public and private tenders. Finally, (3) uncertainties in climate projections appear as a major barrier to the uptake of climate services. However, ambitious greenhouse gas emission reduction as planned by the COP-21 Paris Agreement contribute to reducing this uncertainties by allowing users to select a subset of climate change projections, avoiding those for which adaptation is most problematic.

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.

Sea-level rise (SLR) will be one of the major climate change-induced risks of the 21st century for coastal areas. The large uncertainties of ice sheet melting processes bring in a range of unlikely – but not impossible – high-end sea-level scenarios (HESs). Here, we provide global to regional HESs exploring the tails of the distribution estimates of the different components of sea level. We base our scenarios on high-end physical-based model projections for glaciers, ocean sterodynamic effects, glacial isostatic adjustment and contributions from land-water, and we rely on a recent expert elicitation assessment for Greenland and Antarctic ice-sheets. We consider two future emissions scenarios and three time horizons that are critical for risk-averse stakeholders (2050, 2100, and 2200). We present our results from global to regional scales and highlight HESs spatial divergence and their departure from global HESs through twelve coastal city and island examples. For HESs-A, the global mean-sea level (GMSL) is projected to reach 1.06(1.91) in the low(high) emission scenario by 2100. For HESs-B, GMSL may be higher than 1.69(3.22) m by 2100. As far as 2050, while in most regions SLR may be of the same order of magnitude as GMSL, at local scale where ice-sheets existed during the Last Glacial Maximum, SLR can be far lower than GMSL, as in the Gulf of Finland. Beyond 2050, as sea-level continue to rise under the HESs, in most regions increasing rates of minimum(maximum) HESs are projected at high(low-to-mid) latitudes, close to (far from) ice-sheets, resulting in regional HESs substantially lower(higher) than GMSL. In regions where HESs may be extremely high, some cities in South East Asia such as Manila are even more immediately affected by coastal subsidence, which causes relative sea-level changes that exceed our HESs by one order of magnitude in some sectors.

Long-term (>decades) coastal recession due to sea-level rise (SLR) has been estimated using the Bruun Rule for nearly six decades. Equilibrium-based shoreline models have been shown to skillfully predict short-term wave-driven shoreline change on time scales of hours to decades. Both the Bruun Rule and equilibrium shoreline models rely on the equilibrium beach theory, which states that the beach profile shape equilibrates with its local wave and sea-level conditions. Integrating these two models into a unified framework can improve our understanding and predictive skill of future shoreline behavior. However, given that both models account for wave action, but over different time scales, a critical re-examination of the SLR-driven recession process is needed. We present a novel physical interpretation of the beach response to sea-level rise, identifying two main contributing processes: passive flooding and increased wave-driven erosion efficiency. Using this new concept, we analyze the integration of SLR-driven recession into equilibrium shoreline models and, with an idealized test case, show that the physical mechanisms underpinning the Bruun Rule are explicitly described within our integrated model. Finally, we discuss the possible advantages of integrating SLR-driven recession models within equilibrium-based models with dynamic feedbacks and the broader implications for coupling with hybrid shoreline models.

Abstract Cost-effective coastal flood adaptation requires a realistic valuation of losses, costs and benefits considering the uncertainty of future flood projections and limited resources for adaptation. Here we present an approach to quantify the flood protection benefits of beaches accounting for the dynamic interaction of storm erosion, long-term shoreline evolution and flooding. We apply the method in Narrabeen-Collaroy (Australia) considering uncertainty in different shared socioeconomic pathways, sea-level rise projections, and beach conditions. By 2100, results show that failing to consider erosion can underestimate flood damage by a factor of 2 and maintaining present-day beach width can avoid 785 million AUD worth assets from flood damage. By 2050, the flood protection and recreational benefits of holding the current mean shoreline could be more than 150 times the cost of nourishment. Our results give insight on the benefits of beaches for adaptation and can help accelerate financial instruments for restoration.

While the prioritisation of scarce resources for climate adaptation is becoming a priority for low and middle income countries, the climate service literature addressing adaptation prioritisation decisions is scarce. This paper contributes to filling this gap by presenting a co-creation process carried out in the Maldives among representatives of government, civil society and researchers. Together, we identified the need to improve a ranking method currently used by the Maldivian government to prioritise islands for investments in erosion prevention. As a solution we developed a layered index. The first layer of this index captures the objective dimension of the problem through an erosion hazard subindex, using the three variables wave energy, reef health and reef flat minimum width. The second layer captures the normative dimension through a multi-criteria analysis using the erosion hazard subindex as one criterion next to other stakeholder selected criteria such as critical infrastructure, economic activity, per capita income and the potential to house additional people that resettle from riskier places as sea-level rise progresses. Results of this new ranking method show that socioeconomic criteria were considered more important by the stakeholders than the biophysical criterion of erosion hazard. Among the top-ranked islands are many regional centres but also less populous islands that have a large potential to house additional people. Lessons learnt from the co-creation process highlight the importance of assembling interdisciplinarity teams, fostering mutual learning among project participants, and designing research projects that do not prescribe upfront the exact problems to be addressed and methods to be applied.

Abstract Atoll islands face increasing coastal risks (coastal erosion and marine flooding) due to climate change, especially sea-level rise. To face increasing coastal risks, various adaptation options are considered by atoll countries and territories, including in particular hard protection (preferred option to date), Nature-based Solutions (increasingly used) and island raising (considered a longer-term solution and a potential alternative to international migration, e.g. in the Maldives). Internal relocation within the same atoll island or atoll, which refers to long-term community movement from one threatened island area or island to a safer island area or island, has previously been disregarded by scholars as a potentially relevant climate adaptation strategy. However, in low-lying coastal areas, it offers real potential to address the dual context of increasing climate risks and the shrinking of the solution space. This paper assesses the potential of internal relocation for atolls by applying to Rangiroa Atoll, French Polynesia, Central Pacific, a two-fold assessment framework questioning its physical relevance (are some islands high enough to host settlements in the future?) and its societal feasibility (are the political-institutional and socio-economic conditions in place? Are people willing to relocate?). The findings show that internal relocation is both relevant and feasible on Rangiroa Atoll and should therefore serve as a pillar to develop robust in situ adaptation pathways in this atoll.

Abstract Atoll islands are among the places most vulnerable to climate change due to their low elevation above mean sea level. Even today, some of these islands suffer from severe flooding generated by wind-waves, that will be exacerbated with mean sea-level rise. Wave-induced flooding is a complex physical process that requires computationally-expensive numerical models to be reliably estimated, thus limiting its application to single island case studies. Here we present a new model-based parameterisation for wave setup and a set of numerical simulations for the wave-induced flooding in coral reef islands as a function of their morphology, the Manning friction coefficient, wave characteristics and projected mean sea level that can be used for rapid, broad scale (e.g. entire atoll island nations) flood risk assessments. We apply this new approach to the Maldives to compute the increase in wave hazard due to mean sea-level rise, as well as the change in island elevation or coastal protection required to keep wave-induced flooding constant. While future flooding in the Maldives is projected to increase drastically due to sea-level rise, we show that similar impacts in nearby islands can occur decades apart depending on the exposure to waves and the topobathymetry of each island. Such assessment can be useful to determine on which islands adaptation is most urgently needed.

The latest IPCC report estimates that approximately 1 billion people will be at risk from coastal hazards in the near term due to coastal population increase, sea-level rise and other coastal changes. This will occur in a world that is changing rapidly due to climate change, ecosystem decline, human development and the projected transformations of the economy to meet the objectives of the Paris Agreement. In this context, social sciences provide a pivotal perspective to coastal adaptation, for example, while assessing barriers and opportunities across scales, from local to global. This scoping review explores how social sciences support coastal adaptation. We show that Political Sciences, Economics, Sociology and Geography are already supporting coastal adaptation. Yet, scientific fields such as legal sciences, psychology, history and archaeology as well as anthropology and ethnography are less developed in the context of coastal adaptation to sea-level rise. New research avenues could also integrate education, media and communication research and aim at truly interdisciplinary studies linking different branches of social sciences with coastal science and climate services. This effort could help moving from a coastal adaptation often focused on coastal engineering protection to a broader vision of coastal resilient development, also addressing the challenges of mitigation, sustainable development and coastal ecosystem decline.

Climate services are ideally co-developed by scientists and stakeholders working together to identify decisions and user needs. Yet, while climate services have been developed at regional to local scales, relatively little attention has been paid to the global scale. Global climate services involve decisions that rely on climate information from many locations in different world regions, and are increasingly salient. Increasing interconnections in the global financial system and supply chains expose private companies and financial institutions to climate risk in multiple locations in different world regions. Further, multilateral decisions on greenhouse gas emission reduction targets, disaster risk finance or international migration should make use of global scale climate risk assessments. In order to advance global climate service development, we present a typology of decisions relying on global (i.e., non-local) climate risk information. We illustrate each decision type through examples of current practice from the coastal domain drawn from the literature and stakeholder interviews. We identify 8 types of decisions making use of global climate information. At a top-level, we distinguish between “multilateral climate policy decisions,” and “portfolio decisions involving multiple locations.” Multilateral climate policy decisions regard either “mitigation targets” or “multilateral adaptation” decisions. Portfolio decisions regard either “choice of location” or “choice of financial asset” decisions. Choice of location decisions can be further distinguished as to whether they involve “direct climate risks,” “supply chain risks” or “financial network risks.” Our survey of examples shows that global climate service development is more advanced for portfolio decisions taken by companies with experience in climate risk assessment, i.e., (re-)insurers, whereas many multilateral climate policy decisions are at an earlier stage of decision-making. Our typology thus provides an entry-point for global climate service development by pointing to promising research directions for supporting global (non-local) decisions that account for climate risks.

Non-stationary extreme value analysis is a powerful framework to address the problem of time evolution of extremes and its link to climate variability as measured by different climate indices CI (like North Atlantic Oscillation NAO index). To model extreme sea levels (ESLs), a widely-used tool is the non-stationary Generalized Extreme Value distribution (GEV) where the parameters (location, scale and shape) are allowed to vary as a function of some covariates like the month-of-year or some CIs. A commonly used assumption is that only a few CIs impact the GEV parameters by using a linear model, and most of the time by focusing on two GEV parameters (location or/and the scale parameter). In the present study, these assumptions are revisited by relying on a data-driven spline-based GEV fitting approach combined with a penalization procedure. This allows identifying the type (non- or linear) of the CI influence for any of the three GEV parameters directly from the data, and evaluating the significance of this relation, i.e. without making any a priori assumptions as it is traditionally done. This approach is applied to the monthly maxima of sea levels derived from eight of the longest (quasi century-long) tide gauge dataset (Brest, France; Cuxhaven, Germany; Gedser, Denmark; Halifax, Canada; Honolulu, US; Newlyn, UK; San Francisco, US; Stockholm, Sweden) and by accounting for four major CIs (the North Atlantic Oscillation, the Atlantic Multidecadal Oscillation, the Niño 1 + 2 and the Southern Oscillation indices). From this analysis, we show that: (1) the links between CIs and different parameters of a GEV distribution fitted to ESL data are most of the time linear, but some of them present significant non-linear shapes; (2) multiple CIs should be considered to predict ESLs, and (3) the CI influence of the GEV distribution is not limited to the location parameter. These results are useful to understand current modes of variability of ESLs, and ultimately to improve coastal resilience through more precise extreme water level assessments.

Populated coastal areas worldwide have a legacy of numerous solid waste disposal sites. At the same time, mean sea level is rising and likely to accelerate, increasing flooding and/or erosion. There is therefore concern that landfill sites located at and near the coast pose a growing risk to the environment from the potential release of liquid and solid waste materials. This paper aims to assess our present understanding of this issue as well as research and practice needs by synthesizing the available evidence across a set of developed country cases, comprising England, France, Germany, the Netherlands, and the United States (Florida). Common insights gained here include: (1) a lack of data and limited appreciation of waste release from coastal landfill as a potential problem; (2) recognition of the scale and diversity of coastal landfill waste within a range of generic settings (or situations); and (3) a lack of robust protocols that allow the impact of different categories of waste release to the coast to be assessed in a consistent and evidence-based manner, most particularly for solid waste. Hence, a need for greater understanding of the following issues is identified: (1) the amount, character and impact of waste that could be released from landfill sites; (2) the acceptability and regulation of waste eroding from coastal landfills; (3) present and future erosion rates at landfill sites suggesting the need for more monitoring and relevant predictive tools; (4) the full range of possible management methods for dealing with waste release from landfills and the science to support them; and (5) relevant long-term funding mechanisms to address this issue. The main focus and experience of current management practice has been protection/retention, or removal of landfills, with limited consideration of other feasible solutions and how they might be facilitated. Approaches to assess and address solid waste release to the marine/coastal environment represent a particular gap. Lastly, as solid waste will persist indefinitely and sea levels will rise for many centuries, the long timescale of this issue needs wider appreciation and should be included in coastal and waste policy.

The Maldives, with one of the lowest average land elevations above present-day mean sea level, is among the world regions that will be the most impacted by mean sea-level rise and marine extreme events induced by climate change. Yet, the lack of regional and local information on marine drivers is a major drawback that coastal decision-makers face to anticipate the impacts of climate change along the Maldivian coastlines. In this study we focus on wind-waves, the main driver of extremes causing coastal flooding in the region. We dynamically downscale large-scale fields from global wave models, providing a valuable source of climate information along the coastlines with spatial resolution down to 500 m. This dataset serves to characterise the wave climate around the Maldives, with applications in regional development and land reclamation, and is also an essential input for local flood hazard modelling. We illustrate this with a case study of HA Hoarafushi, an atoll island where local topo-bathymetry is available. This island is exposed to the highest incoming waves in the archipelago and recently saw development of an airport island on its reef via land reclamation. Regional waves are propagated toward the shoreline using a phase-resolving model and coastal inundation is simulated under different mean sea-level rise conditions of up to 1 m above present-day mean sea level. The results are represented as risk maps with different hazard levels gathering inundation depth and speed, providing a clear evidence of the impacts of the sea level rise combined with extreme wave events.

European coastal databases contain information on the evolution of European shorelines in the 1990s and the 1980s. We investigate if a shift toward erosion has been observed between these two periods, as it could be expected as a consequence of contemporary sea-level rise or changing coastal management practices. We select comparable European coastal sites, consider their state transitions as the parameters of a discrete-time Markov chain, and analyze their steady states in order to reveal underlying changes in shoreline evolution trends. The results suggest that European coastal wetlands and small beaches have initiated a shift toward erosion, which attenuates previous optimistic statements. Our results should be interpreted with caution due to the limited number of observations and presumed errors in the database. However, they suggest that the impact of contemporary sea-level rise along European coastlines in the 1990s may be more important than previously thought. Our results suggest that more research is needed to quantify the morphodynamics of muddy coasts and to develop data models able to represent coastal morphodynamic changes adequately.

The original version of this Article contained an error in the Acknowledgements section.

Coastal zones are highly dynamical systems affected by a variety of natural and anthropogenic forcing factors that include sea level rise, extreme events, local oceanic and atmospheric processes, ground subsidence, etc. However, so far, they remain poorly monitored on a global scale. To better understand changes affecting world coastal zones and to provide crucial information to decision-makers involved in adaptation to and mitigation of environmental risks, coastal observations of various types need to be collected and analyzed. In this white paper, we first discuss the main forcing agents acting on coastal regions (e.g., sea level, winds, waves and currents, river runoff, sediment supply and transport, vertical land motions, land use) and the induced coastal response (e.g., shoreline position, estuaries morphology, land topography at the land–sea interface and coastal bathymetry). We identify a number of space-based observational needs that have to be addressed in the near future to understand coastal zone evolution. Among these, improved monitoring of coastal sea level by satellite altimetry techniques is recognized as high priority. Classical altimeter data in the coastal zone are adversely affected by land contamination with degraded range and geophysical corrections. However, recent progress in coastal altimetry data processing and multi-sensor data synergy, offers new perspective to measure sea level change very close to the coast. This issue is discussed in much detail in this paper, including the development of a global coastal sea-level and sea state climate record with mission consistent coastal processing and products dedicated to coastal regimes. Finally, we present a new promising technology based on the use of Signals of Opportunity (SoOp), i.e., communication satellite transmissions that are reutilized as illumination sources in a bistatic radar configuration, for measuring coastal sea level. Since SoOp technology requires only receiver technology to be placed in orbit, small satellite platforms could be used, enabling a constellation to achieve high spatio-temporal resolutions of sea level in coastal zones.

Global scale assessments of coastal flood damage and adaptation costs under 21st century sea-level rise are associated with a wide range of uncertainties, including those in future projections of socioeconomic development (shared socioeconomic pathways (SSP) scenarios), of greenhouse gas concentrations (RCP scenarios), and of sea-level rise at regional scale (RSLR), as well as structural uncertainties related to the modelling of extreme sea levels, data on exposed population and assets, and the costs of flood damages, etc. This raises the following questions: which sources of uncertainty need to be considered in such assessments and what is the relative importance of each source of uncertainty in the final results? Using the coastal flood module of the Dynamic Interactive Vulnerability Assessment modelling framework, we extensively explore the impact of scenario, data and model uncertainties in a global manner, i.e., by considering a large number (>2000) of simulation results. The influence of the uncertainties on the two risk metrics of expected annual damage (EAD), and adaptation costs (AC) related to coastal protection is assessed at global scale by combining variance-based sensitivity indices with a regression-based machine learning technique. On this basis, we show that the research priorities in terms of future data/knowledge acquisition to reduce uncertainty on EAD and AC differ depending on the considered time horizon. In the short term (before 2040), EAD uncertainty could be significantly decreased by 25 and 75% if the uncertainty of the translation of physical damage into costs and of the modelling of extreme sea levels could respectively be reduced. For AC, it is RSLR that primarily drives short-term uncertainty (with a contribution ~50%). In the longer term (>2050), uncertainty in EAD could be largely reduced by 75% if the SSP scenario could be unambiguously identified. For AC, it is the RCP selection that helps reducing uncertainty (up to 90% by the end of the century). Altogether, the uncertainty in future human activities (SSP and RCP) are the dominant source of the uncertainty in future coastal flood risk.

Coastal floods are driven by many hydro-meteorological forcing factors, among which are mean sea levels, tides, atmospheric storm surges, and waves. Depending on these conditions, wave overtopping may occur and, in some cases, lead to a significant flood. In the present study, we investigate the effect of the stochastic character of waves on the flood itself using a phase-resolving wave model (SWASH). We focus on the macro-tidal site of Gâvres (France), consider two past flood events (both resulting from wave overtopping), and investigate how the effect of randomness of waves on the flood is changing with the forcing conditions and the time span (minutes to hours). We clearly show that the effect of waves’ stochasticity on the flood itself is far from being negligible and, especially on a short time scale (~15 min), generates an uncertainty comparable to that induced by the sea-level rise scenarios, as long as the still water level remains smaller than the critical level above which overflow occurs. This implies that lower confidence should be assigned to flood projection on sites where wave overtopping is the main process leading to flood.

Sea-level rise magnifies flood hazards, raising the question when adaptation measures need to be taken. Here, we quantify when the recurrence of extreme water level events will double due to projected sea-level rise. Reproducing the most common method based on extreme water levels observed with tide gauges, at least one third of the coastal locations are to expect a doubling of extremes within a decade. However, tide gauges are commonly placed in wave-sheltered harbours where the contribution of waves to water levels is much smaller than at nearby wave-exposed coastlines such as beaches and dikes. In this study, we quantify doubling times at a variety of idealised shorelines based on modelled tides, storm surges and waves. We apply an extreme value analysis that accounts for the joint probability of extreme storm surges and extreme waves. Our results indicate that doubling times at wave-exposed shorelines are longer than those in wave-sheltered harbours, allowing for more time to adapt to magnified flood hazards. The median doubling times of average water levels including parameterised wave set-up are 1.2 to 5 times longer than those of still water levels as observed with tide gauges. For instantaneous water levels including wave run-up, doubling times are an additional 30% to 100% longer. We conclude that tide gauge-based analyses underestimate adaptation times by underestimating the contribution of waves to extreme water levels, and provide a quantitative framework to guide adaptation policy at wave-exposed shorelines.

In the area of sea-level rise, recent research has focused on assessing either likely or high end future sea levels, but less attention has been given to “low-end” sea-level projections, exploring best-case potential sea-level changes and providing the basis for estimating minimum adaptation needs. Here, we provide global and regional probabilistic sea-level projections using conservative projections of glaciers and ice-sheets melting and a selection of models from the Coupled Model Intercomparison Project phase 5 (CMIP5) delivering moderate thermal expansion. Our low-end sea-level projections are higher than previously estimated because they rely on modeling outcomes only, and do not add any expert judgement, aiming essentially at delivering more realistic upper tails. While there are good reasons to believe that our projections are excessively optimistic, they can be used as low-end sea-level projections in order to inform users with low aversion to uncertainty. Our low-end sea-level projection exceeds 0.5 m along most inhabited coasts by 2100 for business as usual greenhouse gas emissions (RCP8.5), which is relevant for adaptation practitioners as long as efficient climate change mitigation policies are not implemented. This means that without efficient climate mitigation, an acceleration of sea-level rise can hardly be avoided during the 21st century.

Changes in mean sea level (MSL) are a major, but not the unique, cause of changes in high-percentile sea levels (HSL), e.g. the annual 99.9th quantile of sea level (among other factors, climate variability may also have huge influence). To unravel the respective influence of each contributor, we propose to use structural time series models considering six major climate indices (CI) (Artic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Southern Oscillation Index, Niño 1 + 2 and Niño 3.4) as well as a reconstruction of MSL. The method is applied to eight century-long tide gauges across the world (Brest (France), Newlyn (UK), Cuxhaven (Germany), Stockholm (Sweden), Gedser (Danemark), Halifax (Canada), San Francisco (US), and Honolulu (US)). The treatment within a Bayesian setting enables to derive an importance indicator, which measures how often the considered driver is included in the model. The application to the eight tide gauges outlines that MSL signal is a strong driver (except for Gedser), but is not unique. In particular, the influence of Artic Oscillation index at Cuxhaven, Stockholm and Halifax, and of Niño Sea Surface Temperature index 1 + 2 at San Francisco appear to be very strong as well. A similar analysis was conducted by restricting the time period of interest to the 1st part of the 20th century. Over this period, we show that the MSL dominance is lower, whereas an ensemble of CI contribute to a large part to HSL time evolution as well. The proposed setting is flexible and could be applied to incorporate any alternative predictive time series such as river discharge, tidal constituents or vertical ground motions where relevant.

For many climate change impacts such as drought and heat waves, global and national frameworks for climate services are providing ever more critical support to adaptation activities. Coastal zones are especially in need of climate services for adaptation, as they are increasingly threatened by sea level rise and its impacts, such as submergence, flooding, shoreline erosion, salinization and wetland change. In this paper, we examine how annual to multi-decadal sea level projections can be used within coastal climate services (CCS). To this end, we review the current state-of-the art of coastal climate services in the US, Australia and France, and identify lessons learned. More broadly, we also review current barriers in the development of CCS, and identify research and development efforts for overcoming barriers and facilitating their continued growth. The latter includes: (1) research in the field of sea level, coastal and adaptation science and (2) cross-cutting research in the area of user interactions, decision making, propagation of uncertainties and overall service architecture design. We suggest that standard approaches are required to translate relative sea level information into the forms required to inform the wide range of relevant decisions across coastal management, including coastal adaptation.

Despite progresses in climate change science, projections of future sea-level rise remain highly uncertain, especially due to large unknowns in the melting processes affecting the ice-sheets in Greenland and Antarctica. Based on climate-models outcomes and the expertise of scientists concerned with these issues, the IPCC provided constraints to the quantiles of sea-level projections. Moreover, additional physical limits to future sea-level rise have been established, although approximately. However, many probability functions can comply with this imprecise knowledge. In this contribution, we provide a framework based on extra-probabilistic theories (namely the possibility theory) to model the uncertainties in sea-level rise projections by 2100 under the RCP 8.5 scenario. The results provide a concise representation of uncertainties in future sea-level rise and of their intrinsically imprecise nature, including a maximum bound of the total uncertainty. Today, coastal impact studies are increasingly moving away from deterministic sea-level projections, which underestimate the expectancy of damages and adaptation needs compared to probabilistic laws. However, we show that the probability functions used so-far have only explored a rather conservative subset of sea-level projections compliant with the IPCC. As a consequence, coastal impact studies relying on these probabilistic sea-level projections are expected to underestimate the possibility of large damages and adaptation needs.

Figures 3 and 4 of the article ‘Bounding probabilistic sea-level projections within the framework of the possibility theory’ display a minimum value for sea level rise of 15 cm by 2100 with respect to the 1986–2005 mean for the RCP 8.5. The value of 15 cm is consistent with sea level rise rates dropping back to velocities observed during the 20th century according to recent studies, but not to the current sea level rise velocity of 3.4 mm yr ^−1 , as incorrectly stated in the article. This error has no impact on the rest of the article, including its arguments and conclusions, but it is potentially confusing for scientists willing to reproduce the left side of figures 3 and 4. We apologise for any inconvenience caused.

With growing concerns regarding future impacts of sea-level in major coastal cities, the most accurate information is required regarding local sea-level changes with respect to the coast. Besides global and regional sea-level changes, local coastal vertical ground motions can substantially contribute to local changes in sea-level. In some cases, such ground motions can also limit the usefulness of tide-gauge records, which are a unique source of information to evaluate global sea-level changes before the altimetry era. Using satellite synthetic aperture radar interferometry, this study aims at characterizing vertical coastal ground motion in Dakar (Senegal), where a unique century-long record in Africa has been rediscovered. Given the limited number of available images, we use a stacking procedure to compute ground motion velocities in the line of sight over 1992–2010. Despite a complex geology and a rapid population growth and development, we show that the city as a whole is unaffected by differential ground motions larger than 1 mm year ^−1 . Only the northern part of the harbor displays subsidence patterns after 2000, probably as a consequence of land reclamation works. However, these ground motions do not affect the historical tide gauge. Our results highlight the value of the historical sea-level records of Dakar, which cover a 100 year time-span in a tropical oceanic region of Africa, where little data are available for past sea-level reconstructions.