While the understanding and modelling of sea level rise (SLR) due to ocean density and mass changes have greatly improved over the past few decades, relative SLR contributions due to vertical land motions (VLMs) remain a major source of uncertainty. It is critical to downscale global and regional sea-level rise to local relative sea-level change as this is what causes coastal impacts and adaptation needs. In particular, land subsidence can strongly exacerbate coastal flood risk, saltwater intrusion, erosion and loss of wetlands and damage to infrastructure. Here, we present the first analysis of pan-European coastal subsidence based on the European Ground Motion Service (EGMS) Ortho product. First, we perform a comparison between EGMS Ortho (Level 3) vertical velocity estimates and GNSS stations vertical velocity. This comparison reveals that the geodetic reference frame used to calibrate EGMS affects the vertical land velocity estimates and needs to be accounted for carefully, especially for the vertical land motions – including sub-millimetric/year velocities – that could affect local SLR estimates. After adjusting the EGMS calibrated product to the International Terrestrial Reference Frame (ITRF2014), we performed an assessment of VLM in European coastal flood plains. Our results show that half of the European area located in coastal flood plain is, on average, experiencing subsidence at a rate stronger than -1 mm/yr. More importantly, we find that urban area and population experience almost a -1 mm/yr subsidence on average (if we discard the uplifting regions due to Glacial Isostatic Adjustment) and for coastal airports and for harbours, the average land motion drops is even larger with -1.5 mm/yr subsidence rate. Finally, while our analysis allows identifying already well-known coastal subsidence hot-spots (e.g. Northern Italian coastal plain, Netherlands), we demonstrate with few examples that EGMS analysis also paves the way toward the identification of subsiding local scale coastal zones that have been ignored so far and for which flooding risk may become a major concern.

The PROTECT project [1] includes a probabilistic integrated assessment of global population exposure to coastal flood hazard under climate-induced sea-level rise (SLR) over the next three centuries (to 2300). The assessment synthesises present-day datasets on population distribution [2], low lying coastal elevations [3] and extreme tides [4] with probabilistic projection datasets of population [5] and sea level [6] to 2300. For the scenarios considered (SSP1-2.6 & SSP2-4.5) and at a global scale, the median human exposure to coastal flood hazards grows substantially but then peaks in the early 2200s and subsequently slowly declines by 2300, despite continued rise in sea level. Previous assessments have primarily focussed on shorter timeframes [2], typically to 2100, while it is widely acknowledged that even if temperatures are stabilised, sea levels are almost certain to continue to rise for many centuries [7][8][9]. Stakeholder workshops carried out with practitioners under the umbrella of PROTECT [10] and literature reviews [11][12] highlight the importance of extending sea-level rise information beyond 2100, to support strategic coastal adaptation and management, land-use planning, and critical infrastructure design. Recent advancements in long term socio-economic modelling [13][5] now provide projections of global population and GDP at country level to 2300. These have already been applied to long-term risk assessments for other climate sectors [13][5][14]. For this assessment, the global coastline was split into ~29,000 segments, each assigned an extreme tide curve (from the COAST-RP dataset [4]) and a hypsometric curve, generated from a global terrain model [3] and present-day population distribution [2]. The hypsometric curves aggregate the total land-area and population at each elevation, including consideration of hydraulic connectivity to the coastline. This gives the land area and population that would be exposed at a given coastal flood level (up to 20mAMSL) for each coastal segment. When sea-level scenarios [6] (SSP1-2.6 & SSP2-4.5) and socio-economic data [5] are combined, the human exposure and land area exposure to coastal flood hazard under a chosen extreme tide return period (or the annual average based on the event-exposure curve) is calculated. This approach facilitates efficient computations, sampling across probabilistic data, and providing robust statistics at a high spatial resolution compared to traditional methods. The outputs at each coastal segment can be aggregated to sub-national, national, or the global scale. In this analysis, it is found that the median exposure of people to coastal flood hazards increases fivefold to a peak in the early 2200s and subsequently slowly declines to 2300 in both SSPs, despite the continued rise in sea level. For the 80th percentile population exposure grows even more (10- to 11-fold) but then stabilises rather than declines. These results reflect the interplay of sea level and demography with fall in global population in the latter half of the assessment period and are contrary to conventional wisdom. This analysis shows that in addition to sea-level rise, it is important to consider demographic trends when considering coastal futures. Figure 1. Probabilistic annual average global population exposure to coastal flood hazard References exceed the word limit so not included

Sea-level rise (SLR) through the twenty-first century and beyond is inevitable, threatening coastal areas and their inhabitants unless there is appropriate adaptation. We investigate coastal flooding to 2100 under the full range of IPCC AR6 (2021) SLR scenarios, assuming plausible adaptation. The adaptation selects the most economically robust adaptation option: protection or retreat. People living in unprotected coastal areas that are frequently inundated (below 1-in-1-year flood level) are assumed to migrate, and the land is considered lost. Globally, across the range of SLR and related socioeconomic scenarios, we estimate between 4 million and 72 million people could migrate over the twenty-first century, with a net land loss ranging from 2,800 to 490,000 km2. India and Vietnam consistently show the highest absolute migration, while Small Island Developing States are the most affected when considering relative migration and land loss. Protection is the most robust adaptation option under all scenarios for 2.8% of the global coastline, but this safeguards 78% of the global population and 91% of assets in coastal areas. Climate stabilisation (SSP1–1.9 and SSP1–2.6) does not avoid all coastal impacts and costs as sea levels still rise albeit more slowly. The impacts and costs are also sensitive to the socioeconomic scenario: SSP3–7.0 experiences higher migration than SSP5–8.5 despite lower SLR, reflecting a larger population and lower GDP. Our findings can inform national and intergovernmental agencies and organisations on the magnitude of SLR impacts and costs and guide assessments of adaptation policies and strategies.

Climate risk modelling provides valuable quantitative data on potential risks at different spatiotemporal scales, but it is essential that these models are evaluated appropriately. In some cases, it may be useful to merge quantitative datasets with qualitative data and local knowledge, to better inform and evaluate climate risk assessments. This interdisciplinary study maps climatic risks relating to health and agriculture that are facing rural Northern Ireland. A large range of quantitative national climate risk modelling results from the OpenCLIM project are scrutinised using local qualitative insights identified during workshops and interviews with farmers and rural care providers. In some cases, the qualitative local knowledge supported the quantitative modelling results, such as (1) highlighting that heat risk can be an issue for health in rural areas as well as urban centres, and (2) precipitation is changing, with increased variability posing challenges to agriculture. In other cases, the local knowledge challenged the national quantitative results. For example, models suggested that (1) potential heat stress impacts will be low, and (2) grass growing conditions will be more favourable, with higher yields as a result of future climatic conditions. In both cases, local knowledge challenged these conclusions, with discomfort and workplace heat stress reported by care staff and recent experience of variable weather having significant impacts on grass growth on farms across the country. Hence, merging even a small amount of qualitative local knowledge with quantitative national modelling projects results in a more holistic understanding of the local climate risk.

ABSTRACTMost national assessments of climate change‐related risks to agriculture focus on the productivity of existing crops. However, one adaptation option is to switch to alternative crops better suited to changing local climates. Spatially explicit projections of relative climatic suitability across a wide range of crops can identify which ones might be viable alternatives. Parametrising process‐based models for multiple crops is complex, so there is value in using simpler approaches to ‘horizon scan’ to identify high‐level issues and target further research. We present a horizon scan approach based on EcoCrop data, producing mapped changes in suitability under +2°C and +4°C warming scenarios (above pre‐industrial), for over 160 crops across the United Kingdom. For the United Kingdom, climate change is likely to bring opportunities to diversify cropping systems. Many current and potential new crops show widespread increases in suitability under a +2°C warming scenario. However, under a +4°C scenario, several current crops (e.g. onions, strawberries, oats, wheat) begin to show declines in suitability in the region of the United Kingdom where most arable crops are currently grown. Whilst some new crops with increasing suitability may offer viable alternatives (e.g. soy, chickpea, grapes), the greatest average increases in suitability across crops occur outside the UK's current areas of greatest agricultural production. Realising these opportunities would thus be likely to require substantial changes to current farming systems and supply chains. By highlighting these opportunities and challenges, our approach provides potentially valuable information to farmers and national assessments.

Strengthening the adaptive capacity of the UK, via national plans and local-scale interventions, requires easy access to climate risk information and adaptation scenarios. Stakeholder engagement can ensure the right balance between top-down prescriptive modelling, and bottom-up, solution-focussed and lived experience approaches. National-scale, spatially-explicit, integrated climate risk frameworks can help inform the needs of localised climate risk assessments, but there are barriers to local actors accessing the information.

China’s major cities show considerable subsidence from human activities

Coastal erosion and flooding are projected to increase during the 21 st century due to sea-level rise (SLR). To prevent adverse impacts of unmanaged coastal development, national organizations can apply a land protection policy, which consists of acquiring coastal land to avoid further development. Yet, these reserved areas remain exposed to flooding and erosion enhanced by SLR. Here, we quantify the exposure of the coastal land heritage portfolio of the French Conservatoire du littoral (Cdl). We find that 30% (~40%) of the Cdl lands owned (projected to be owned) are located below the contemporary highest tide level. Nearly 10% additional surface exposure is projected by 2100 under the high greenhouse gas emissions scenario (SSP5-8.5) and 2150 for the moderate scenario (SSP2-4.5). The increase in exposure is largest along the West Mediterranean coast of France. We also find that Cdl land exposure increases more rapidly for SLR in the range of 0–1 m than for SLR in the range 2–4 m. Thus, near-future uncertainty on SLR has the largest impact on Cdl land exposure evolution and related land acquisition planning. Concerning erosion, we find that nearly 1% of Cdl land could be lost in 2100 if observed historical trends continue. Adding the SLR effect could lead to more than 3% land loss. Our study confirms previous findings that Cdl needs to consider land losses due to SLR in its land acquisition strategy and start acquiring land farther from the coast.

AbstractBeside 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.

This chapter provides an overview of sea-level rise (SLR) risks and adaptation in estuaries, with a focus on coastal flooding as one of the key coastal risks in estuaries, together with its interaction with wetlands and the emerging ideas around Nature-based solutions (NbS) and estuarine and habitat restoration. Climate change–induced SLR threatens estuaries with a range of interconnected and cascading coastal hazards and risks, including enhanced coastal flooding due to higher extreme sea-levels with consequent damages to people, their livelihoods, physical assets and resources, as well as changes or losses of intertidal wetlands with adverse implications for biodiversity, ecosystem services and associated human livelihoods. In many estuaries, mean and extreme sea-levels, as well as coastal wetlands, have, however, also been significantly modified by local human activities, as estuaries have been a focus of human habitation for millennia, reflecting agriculture and trade and, since the industrial revolution, industry. Adapting to SLR thus requires the adoption of a systemic perspective that not only focuses on climate change drivers, but also on past and ongoing human modifications of estuaries. In principle, a wealth of different measures to respond exists, with all of these having strengths and weaknesses and thus having complementary roles to play in an integrated adaptation strategy. On a basic level, adaptation responses include: (1) protection of the shoreline; (2) advancement (or shortening) of the line of defense through land reclamation or storm surge barriers; (3) retreat from the shoreline; or (4) accommodation of the effects of SLR. Adaptation can thereby be delivered by combinations of hard engineering structures (e.g., dikes, seawalls, bulkheads, breakwaters, and storm surge barriers) and Nature-based solutions, which include nourishment of degraded sediment systems, as well as restoring, creating, and maintaining naturally dissipative intertidal ecosystems, such as salt marshes to mitigate erosion and flooding. Importantly, there is no one-size-fits-all measure, but choosing a particular combination of measures needs to carefully consider the estuarine natural and social context, including uncertainties. This means recognizing that, while estuaries have many common factors, in detail they are all distinct, in their geological context and history of human intervention. Furthermore, there is the need to consider multiple policy objectives and multiple interests of diverse stakeholders. For example, the need to protect both human and natural capital in estuaries can often give rise to conflicts, such that significant trade-offs will be required to ensure human safety whilst also sustaining healthy ecosystems. These kinds of challenges can be addressed by using multiple-criteria frameworks and embedding these into inclusive participatory processes. Finally, uncertainties can be addressed by implementing low-regret measures and keeping future options open by either delaying decisions that do not necessarily need to be made today or building flexible measures that can later be adapted as one learns more about how much SLR to expect. Furthermore, decisions that need to be made today can be improved by factoring in uncertain SLR through employing robust and adaptive decision-making frameworks.

The state of progress towards climate adaptation is currently unclear. Here we apply a structured expert judgement to assess multiple dimensions shaping adaptation (equally weighted): risk knowledge, planning, action, capacities, evidence on risk reduction, long-term pathway strategies. We apply this approach to 61 local coastal case studies clustered into four urban and rural archetypes to develop a locally informed perspective on the state of global coastal adaptation. We show with medium confidence that today’s global coastal adaptation is halfway to the full adaptation potential. Urban archetypes generally score higher than rural ones (with a wide spread of local situations), adaptation efforts are unbalanced across the assessment dimensions and strategizing for long-term pathways remains limited. The results provide a multi-dimensional and locally grounded assessment of global coastal adaptation and lay new foundations for international climate negotiations by showing that there is room to refine global adaptation targets and identify priorities transcending development levels.

In the UK, coastal flooding and erosion are two of the primary climate-related hazards to communities, businesses, and infrastructure. To better address the ramifications of those hazards, now and into the future, the UK needs to transform its scattered, frag-mented coastal data resources into a systematic, integrated portal for quality-assured, pub-licly accessible open data. Such a portal would support analyses of coastal risk and resilience by hosting, in addition to data layers for coastal flooding and erosion, a diverse array of spatial datasets for building footprints, infrastructure networks, land use, popula-tion, and various socio-economic measures and indicators derived from survey and census data. The portal would facilitate novel combinations of spatial data layers to yield scientifi-cally, societally, and economically beneficial insights into UK coastal systems.

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.

<p>Sea level rise is a major result of climate change that threatens coastal communities and has the potential to incur significant economic damage. Projecting sea level rise as temperatures rise is therefore crucial for policy and decision-making.</p><p>The two modelling methods currently used to project future sea level change are process-based and semi-empirical. Process-based models rely on combining outputs from coupled atmosphere/ocean models for each component of sea level rise. Semi-empirical models calculate sea level as an integrated response to either warming or radiative forcing, using parameters constrained from past observations.</p><p>Historically, there is disagreement in sea-level projections between different modelling methods. One source of the discrepancies is uncertainty in land ice response to warming; although nonlinearities exist within processes affecting this response, most existing semi-empirical models treat the relationship between warming and ice-melt as linear.</p><p>Non-linear ice melt processes may have not yet affected the observational record (such as tipping points as future warming crosses some threshold) or may have already occurred (such as non-linear effects that apply across all levels of warming, or for which the threshold has already been passed). Here, we examine the effect on semi-empirical projections of sea level rise of nonlinearities in ice melt that have already affected the observed sea level record, by adding a nonlinear term to the relationship between warming and the rate of sea level rise within a large ensemble of historically constrained efficient earth systems model simulations.</p><p>Projections reach a median sea level rise of 1.3m by 2300 following SSP245, and 2.6m by 2300 following SSP585. Results suggest that nonlinear interactions can be sub-linear, super-linear or 0, with a mainly symmetrical distribution. This includes high-impact, low-probability super-linear interactions that lead to significantly larger high-end sea level rise projections than when nonlinear interactions are not included. It is key to note that nonlinear interactions that have not yet occurred but that may occur in the future, are not considered – these will lead to an increased projection of sea level rise.</p>

Abstract Climate change and economic growth are having a profound influence on the integrity of socio-economics and ecology of coastal Bangladesh. In the extreme, there are widespread expectations of inundation and coastal abandonment. However, results from our integrated assessment model (IAM) show that over the next 30 years, development choices might have a stronger influence on livelihoods and economic wellbeing than climate driven environmental change. The IAM simulates the economic development of rural areas by coupling physical models (driven by expectations of climate change) with economic models (informed by a series of policy decisions). This is done using substantial primary, secondary and stakeholder-derived biophysical and socio-economic datasets, together with shocks such as cyclones. The study analyses the future socio-ecological sensitivity to climate change and policy decisions and finds that well managed development is as important as adaptation to mitigate risks, reduce poverty and raise aggregate well-being. This analysis enables decision makers to identify appropriate development pathways that address current social-ecological vulnerability and develop a more resilient future to 2050 and beyond. These policy actions are complementary to climate adaptation and mitigation. Our IAM framework provides a valuable evidence-based tool to support sustainable coastal development and is transferable to other vulnerable delta regions and other coastal lowlands around the world.

Abstract Coastal subsidence can significantly increase rates of relative sea level change over and above climate-related changes, and has been reported to be particularly large in densely populated regions. However, due to the small scale variability of vertical land motion (VLM) and the sparsity of VLM observations, there is currently still low confidence in VLM and the uncertainties this introduces in sea level change estimates. Therefore, we synergize currently available VLM observations (from GNSS, InSAR, tide gauges, and satellite altimetry) to investigate the impact of VLM on relative sea level changes and their uncertainties, as well as the implications for coastal populations. We find that the average contemporary (1995-2019) global relative sea level change experienced by coastal populations (5.14 mm/year) is more than twice as large as the average coastal relative sea level change (2.09 mm/year). This is because rates of subsidence tend to be higher in densely populated areas. A significant part of the coastline (representing 40% of the coastal population) lacks measurements or access to the direct measuring stations which are necessary to constrain VLM rates estimated with InSAR. Missing, or imprecise VLM constraints contribute to the increased population-weighted uncertainties in the relative sea level change trends of ~3 mm/year. Thus, future community efforts are needed to improve the observational database in the disproportionately exposed and densely populated coasts in order to reduce uncertainties in estimates of future relative sea-level rise and their societal implications.

Abstract Including sea-level rise (SLR) projections in coastal adaptation is increasingly recognized as crucial. Here we analyze the first global survey on the use of SLR projections comprising 253 coastal practitioners engaged in adaptation/planning from 49 countries with time frames of 2050 and 2100. While recognition of the threat of SLR is almost universally recognized, only 71% of respondents currently utilize SLR projections. Generally, developing countries have lower levels of utilization. There is no global standard in the use of SLR projections: for locations using a standard structure, 53% are planning for a single projection, while the remainder are using multiple projections, with 13% considering an unlikely high-end scenario. Countries with long histories of adaptation and consistent national support show greater assimilation of SLR projections into adaptation decisions. This research proves insightful for improving sea-level science, and informs important ongoing efforts on the application of the science which are essential to promote effective adaptation.