Higher probability of compound flooding from precipitation and storm surge in Europe under anthropogenic climate change

In low-lying coastal areas, the co-occurrence of high sea level and precipitation resulting in large runoff may cause compound flooding (CF). When the two hazards interact, the resulting impact can be worse than when they occur individually. Both storm surges and heavy precipitation, as well as their interplay, are likely to change in response to global warming. Despite the CF relevance, a comprehensive hazard assessment beyond individual locations is missing, and no studies have examined CF in the future. Analyzing co-occurring high sea level and heavy precipitation in Europe, we show that the Mediterranean coasts are experiencing the highest CF probability in the present. However, future climate projections show emerging high CF probability along parts of the northern European coast. In several European regions, CF should be considered as a potential hazard aggravating the risk caused by mean sea level rise in the future

The transformed-stationary approach: A generic and simplified methodology for non-stationary extreme value analysis

Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MATLAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/ (Mentaschi et al., 2016)

Extreme sea levels at different global warming levels

The Paris agreement focused global climate mitigation policy on limiting global warming to 1.5 or 2 °C above pre-industrial levels. Consequently, projections of hazards and risk are increasingly framed in terms of global warming levels rather than emission scenarios. Here, we use a multimethod approach to describe changes in extreme sea levels driven by changes in mean sea level associated with a wide range of global warming levels, from 1.5 to 5 °C, and for a large number of locations, providing uniform coverage over most of the world’s coastlines. We estimate that by 2100 ~50% of the 7,000+ locations considered will experience the present-day 100-yr extreme-sea-level event at least once a year, even under 1.5 °C of warming, and often well before the end of the century. The tropics appear more sensitive than the Northern high latitudes, where some locations do not see this frequency change even for the highest global warming levels

African heritage sites threatened as sea-level rise accelerates

The African coast contains heritage sites of ‘Outstanding Universal Value’ that face increasing risk from anthropogenic climate change. Here, we generated a database of 213 natural and 71 cultural African heritage sites to assess exposure to coastal flooding and erosion under moderate (RCP 4.5) and high (RCP 8.5) greenhouse gas emission scenarios. Currently, 56 sites (20%) are at risk from a 1-in-100-year coastal extreme event, including the iconic ruins of Tipasa (Algeria) and the North Sinai Archaeological Sites Zone (Egypt). By 2050, the number of exposed sites is projected to more than triple, reaching almost 200 sites under high emissions. Emissions mitigation from RCP 8.5 to RCP 4.5 reduces the number of very highly exposed sites by 25%. These findings highlight the urgent need for increased climate change adaptation for heritage sites in Africa, including governance and management approaches, site-specific vulnerability assessments, exposure monitoring, and protection strategies

How grazing management can maximize erosion resistance of salt marshes

Combining natural saltmarsh habitats with conventional barriers can provide a sustainable and cost-effective alternative for fully engineered flood protection, provided that a minimal salt marsh width can be guaranteed for a long period. Hence, it is essential to understand both the key factors and management options driving the lateral erodibility/stability of salt marshes.We aimed to determine how salt marsh management (i.e. grazing by large vs. small grazers vs. artificial mowing), marsh elevation and marsh age affect soil stability (i.e. soil collapse) and intrinsic lateral erodibility of salt marshes (i.e. particle-by-particle detachment). Soil cores were collected in high and low marshes (above and below 0.5 m MHWL, respectively) of different ages. At these locations, we compared cores from grazed areas to cores inside grazer exclosures, with and without artificial mowing. All cores were exposed to waves in flumes to test their stability and lateral erodibility.All soil cores were characterized by a stable fine-grained layer deposited on top of readily erodible sand. The thickness of the fine-grained layer was a key parameter in reducing salt marsh instability (cliff collapse). This layer thickness increased with marsh age and at lower elevations, but decreased with cattle grazing due to compaction.The erosion resistance of the fine-grained layer increased with (a) large grazers that compacted the soil by trampling, (b) mowing that excluded soil-bioturbating species, and (c) grazing by small grazers that promoted vegetation types with higher root density.Synthesis and applications. Overall, marshes with thinner cohesive and/or fine-grained top layers are more sensitive to lateral erosion than marshes with deep cohesive soils, independently of the management. Grazing and artificial mowing can reduce the erodibility of fine-grained soils, making salt marshes more resilient to lateral erosion. However, compaction by large grazers simultaneously leads to thinner fine-grained layers and lower elevation, potentially leading to more inundation under sea-level rise. Hence, to effectively manage salt marshes to enhance their contribution to coastal protection, we recommend (a) moderate/rotational livestock grazing, avoiding high intensity grazing in sediment-poor systems sensitive to sea-level rise and (b) investigating measures to preserve small grazers.</p

Sandy coastlines under threat of erosion

Sandy beaches occupy more than one-third of the global coastline(1) and have high socioeconomic value related to recreation, tourism and ecosystem services(2). Beaches are the interface between land and ocean, providing coastal protection from marine storms and cyclones(3). However the presence of sandy beaches cannot be taken for granted, as they are under constant change, driven by meteorological(4,5), geological(6) and anthropogenic factors(1,7). A substantial proportion of the world's sandy coastline is already eroding(1,7), a situation that could be exacerbated by climate change(8,9). Here, we show that ambient trends in shoreline dynamics, combined with coastal recession driven by sea level rise, could result in the near extinction of almost half of the world's sandy beaches by the end of the century. Moderate GHG emission mitigation could prevent 40% of shoreline retreat. Projected shoreline dynamics are dominated by sea level rise for the majority of sandy beaches, but in certain regions the erosive trend is counteracted by accretive ambient shoreline changes; for example, in the Amazon, East and Southeast Asia and the north tropical Pacific. A substantial proportion of the threatened sandy shorelines are in densely populated areas, underlining the need for the design and implementation of effective adaptive measures. Erosion is a major problem facing sandy beaches that will probably worsen with climate change and sea-level rise. Half the world's beaches, many of which are in densely populated areas, could disappear by the end of the century under current trends; mitigation could lessen retreat by 40%.info:eu-repo/semantics/publishedVersio

Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis

One of the main consequences of mean sea level rise (SLR) on human settlements is an increase in flood risk due to an increase in the intensity and frequency of extreme sea levels (ESL). While substantial research efforts are directed towards quantifying projections and uncertainties of future global and regional SLR, corresponding uncertainties in contemporary ESL have not been assessed and projections are limited. Here we quantify, for the first time at global scale, the uncertainties in present-day ESL estimates, which have by default been ignored in broad-scale sea-level rise impact assessments to date. ESL uncertainties exceed those from global SLR projections and, assuming that we meet the Paris agreement goals, the projected SLR itself by the end of the century in many regions. Both uncertainties in SLR projections and ESL estimates need to be understood and combined to fully assess potential impacts and adaptation needs

More meteorological events that drive compound coastal flooding are projected under climate change

Compound flooding arises from storms causing concurrent extreme precipitation and meteorological tides, that is the superposition of storm surge and waves. This flooding can severely affect densely populated low-lying coastal areas. Here, combining output from climate and ocean models, we analyse the concurrence probability of the meteorological conditions driving compound flooding. We show that, under a high emissions scenario, the concurrence probability would increase globally by more than 25% by 2100 compared to present. In latitudes above 40o north, compound flooding could become more than 2.5 times as frequent, in contrast to parts of the subtropics where it would weaken. Changes in extreme precipitation and meteorological tides account for most (77% and 20%, respectively) of the projected change in concurrence probability. The evolution of the dependence between precipitation and meteorological tide dominates the uncertainty in the projections. Our results indicate that not accounting for these effects in adaptation planning could leave coastal communities insufficiently protected against flooding

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk

This study provides a literature-based comparative assessment of uncertainties and biases in global to world-regional scale assessments of current and future coastal flood risks, considering mean and extreme sea-level hazards, the propagation of these into the floodplain, people and coastal assets exposed, and their vulnerability. Globally, by far the largest bias is introduced by not considering human adaptation, which can lead to an overestimation of coastal flood risk in 2100 by up to factor 1300. But even when considering adaptation, uncertainties in how coastal societies will adapt to sea-level rise dominate with a factor of up to 27 all other uncertainties. Other large uncertainties that have been quantified globally are associated with socio-economic development (factors 2.3–5.8), digital elevation data (factors 1.2–3.8), ice sheet models (factor 1.6–3.8) and greenhouse gas emissions (factors 1.6–2.1). Local uncertainties that stand out but have not been quantified globally, relate to depth-damage functions, defense failure mechanisms, surge and wave heights in areas affected by tropical cyclones (in particular for large return periods), as well as nearshore interactions between mean sea-levels, storm surges, tides and waves. Advancing the state-of-the-art requires analyzing and reporting more comprehensively on underlying uncertainties, including those in data, methods and adaptation scenarios. Epistemic uncertainties in digital elevation, coastal protection levels and depth-damage functions would be best reduced through open community-based efforts, in which many scholars work together in collecting and validating these data