Global coastal wave storminess.

Coastal wave storms pose a massive threat to over 10% of the world's population now inhabiting the low elevation coastal zone and to the trillions of $ worth of coastal zone infrastructure and developments therein. Using a ~ 40-year wave hindcast, we here present a world-first assessment of wind-wave storminess along the global coastline. Coastal regions are ranked in terms of the main storm characteristics, showing Northwestern Europe and Southwestern South America to suffer, on average, the most intense storms and the Yellow Sea coast and the South-African and Namibian coasts to be impacted by the most frequent storms. These characteristics are then combined to derive a holistic classification of the global coastlines in terms of their wave environment, showing, for example, that the open coasts of northwestern Europe are impacted by more than 10 storms per year with mean significant wave heights over 6 m. Finally, a novel metric to classify the degree of coastal wave storminess is presented, showing a general latitudinal storminess gradient. Iceland, Ireland, Scotland, Chile and Australia show the highest degree of storminess, whereas Indonesia, Papua-New Guinea, Malaysia, Cambodia and Myanmar show the lowest.

An assessment of whether long-term global changes in waves and storm surges have impacted global coastlines.

A common inference in research studies of observed and projected changes in global ocean wave height and storm surge, is that such changes are potentially important for long-term coastal management. Despite numerous studies of the impacts of anthropogenic climate change on trends in global wind and waves, a clear link to impacts on sandy coastlines, at global scale, is yet to be demonstrated. This study presents a first-pass assessment of the potential link between historical trends in global wave and storm surge values and recession/progradation rates of sandy coastlines since the 1980s. Global datasets of waves, surge and shoreline change rate are used for this purpose. Over the past 30 + years, we show that there have been clear changes in waves and storm surge at global scale. The data, however, does not show an unequivocal linkage between trends in wave and storm surge climate and sandy shoreline recession/progradation. We conclude that these long-term changes in oceanographic parameters may still be too small to have a measurable impact on shoreline recession/progradation and that primary drivers such as ambient imbalances in the coastal sediment budget may be masking any such linkages.

Influence of El Niño on the variability of global shoreline position.

Coastal zones are fragile and complex dynamical systems that are increasingly under threat from the combined effects of anthropogenic pressure and climate change. Using global satellite derived shoreline positions from 1993 to 2019 and a variety of reanalysis products, here we show that shorelines are under the influence of three main drivers: sea-level, ocean waves and river discharge. While sea level directly affects coastal mobility, waves affect both erosion/accretion and total water levels, and rivers affect coastal sediment budgets and salinity-induced water levels. By deriving a conceptual global model that accounts for the influence of dominant modes of climate variability on these drivers, we show that interannual shoreline changes are largely driven by different ENSO regimes and their complex inter-basin teleconnections. Our results provide a new framework for understanding and predicting climate-induced coastal hazards.

Assessing coastline recession for adaptation planning: sea level rise versus storm erosion.

The Sixth Assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) states with high confidence that most sandy coasts around the world will experience an increase in coastal erosion over the twenty-first century. An increase in long term coastal erosion (coastline recession) along sandy coasts can translate into massive socio-economic impacts, unless appropriate adaptation measures are implemented in the next few decades. To adequately inform adaptation measures, it is necessary to have a good understanding of the relative importance of the physical processes driving coastline recession, as well as of linkages between consideration (or not) of certain processes and the level of risk tolerance; understandings that are hitherto lacking. Here, we apply the multi-scale Probabilistic Coastline Recession (PCR) model to two end-member sandy coastal types (swell dominated and storm dominated), to investigate where and when coastline recession projections are dominated by the differential contributions from Sea Level Rise (SLR) and storm erosion. Results show that SLR substantially increases the projected end-century recession at both types of coasts and that projected changes in the wave climate have only a marginal impact. An analysis of the Process Dominance Ratio (PDR), introduced here, shows that the dominance of storm erosion over SLR (and vice versa) on total recession by 2100 depends on both the type of the beach and the risk tolerance levels. For moderately risk-averse decisions (i.e. decisions accounting only for high exceedance probability recessions and hence do not account for very high amounts of potential recession-for example, the placement of temporary summer beach cabins), additional erosion due to SLR can be considered as the dominant driver of end-century recession at both types of beaches. However, for more risk-averse decisions that would typically account for higher potential recession (i.e. lower exceedance probability recessions), such as the placement of coastal infrastructure, multi-storey apartment buildings etc., storm erosion becomes the dominant process. The results of this study provide new insights on which physical processes need to be considered when and where in terms of numerical modelling efforts needed for supporting different management decisions, potentially enabling more streamlined and comprehensive assessments of the efficacy of coastal adaptation measures.

The Climatic Impact-Driver Framework for Assessment of Risk-Relevant Climate Information.

The climate science and applications communities need a broad and demand-driven concept to assess physical climate conditions that are relevant for impacts on human and natural systems. Here, we augment the description of the "climatic impact-driver" (CID) approach adopted in the Working Group I (WGI) contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. CIDs are broadly defined as "physical climate system conditions (e.g., means, events, and extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions." We give background information on the IPCC Report process that led to the development of the 7 CID types (heat and cold, wet and dry, wind, snow and ice, coastal, open ocean, and other) and 33 distinct CID categories, each of which may be evaluated using a variety of CID indices. This inventory of CIDs was co-developed with WGII to provide a useful collaboration point between physical climate scientists and impacts/risk experts to assess the specific climatic phenomena driving sectoral responses and identify relevant CID indices within each sector. The CID Framework ensures that a comprehensive set of climatic conditions informs adaptation planning and risk management and may also help prioritize improvements in modeling sectoral dynamics that depend on climatic conditions. CIDs contribute to climate services by increasing coherence and neutrality when identifying and communicating relevant findings from physical climate research to risk assessment and planning activities.

Probabilistic projections of the stability of small tidal inlets at century time scale using a reduced complexity approach.

Climate change is widely expected to affect the thousands of small tidal inlets (STIs) dotting the global coastline. To properly inform effective adaptation strategies for the coastal areas in the vicinity of these inlets, it is necessary to know the temporal evolution of inlet stability over climate change time scales (50-100 years). As available numerical models are unable to perform continuous morphodynamic simulations at such time scales, here we develop and pilot a fast, probabilistic, reduced complexity model (RAPSTA - RAPid assessment tool of inlet STAbility) that can also quantify forcing uncertainties. RAPSTA accounts for the key physical processes governing STI stability and for climate change driven variations in system forcing. The model is very fast, providing a 100 year projection in less than 3 seconds. RAPSTA is demonstrated here at 3 STIs, representing the 3 main Types of STIs; Permanently open, locationally stable inlet (Type 1); Permanently open, alongshore migrating inlet (Type 2); Seasonally/Intermittently open, locationally stable inlet (Type 3). Model applications under a high greenhouse gas emissions scenario (RCP 8.5), accounting for forcing uncertainties, show that while the Type 1 STI will not change type over the twenty-first century, the Type 2 inlet may change into a more unstable Type 3 system around mid-century, and the Type 3 STI may change into a less unstable Type 2 system in about 20 years from now, further changing into a stable Type 1 STI around mid-century. These projections underscore the need for future adaptation strategies to remain flexible.

Twenty-first-century projections of shoreline change along inlet-interrupted coastlines.

Sandy coastlines adjacent to tidal inlets are highly dynamic and widespread landforms, where large changes are expected due to climatic and anthropogenic influences. To adequately assess these important changes, both oceanic (e.g., sea-level rise) and terrestrial (e.g., fluvial sediment supply) processes that govern the local sediment budget must be considered. Here, we present novel projections of shoreline change adjacent to 41 tidal inlets around the world, using a probabilistic, reduced complexity, system-based model that considers catchment-estuary-coastal systems in a holistic way. Under the RCP 8.5 scenario, retreat dominates (90% of cases) over the twenty-first century, with projections exceeding 100 m of retreat in two-thirds of cases. However, the remaining systems are projected to accrete under the same scenario, reflecting fluvial influence. This diverse range of response compared to earlier methods implies that erosion hazards at inlet-interrupted coasts have been inadequately characterised to date. The methods used here need to be applied widely to support evidence-based coastal adaptation.

A global analysis of extreme coastal water levels with implications for potential coastal overtopping.

Climate change and anthropogenic pressures are widely expected to exacerbate coastal hazards such as episodic coastal flooding. This study presents global-scale potential coastal overtopping estimates, which account for not only the effects of sea level rise and storm surge, but also for wave runup at exposed open coasts. Here we find that the globally aggregated annual overtopping hours have increased by almost 50% over the last two decades. A first-pass future assessment indicates that globally aggregated annual overtopping hours will accelerate faster than the global mean sea-level rise itself, with a clearly discernible increase occurring around mid-century regardless of climate scenario. Under RCP 8.5, the globally aggregated annual overtopping hours by the end of the 21st-century is projected to be up to 50 times larger compared to present-day. As sea level continues to rise, more regions around the world are projected to become exposed to coastal overtopping.

Projections of global-scale extreme sea levels and resulting episodic coastal flooding over the 21st Century.

Global models of tide, storm surge, and wave setup are used to obtain projections of episodic coastal flooding over the coming century. The models are extensively validated against tide gauge data and the impact of uncertainties and assumptions on projections estimated in detail. Global "hotspots" where there is projected to be a significant change in episodic flooding by the end of the century are identified and found to be mostly concentrated in north western Europe and Asia. Results show that for the case of, no coastal protection or adaptation, and a mean RCP8.5 scenario, there will be an increase of 48% of the world's land area, 52% of the global population and 46% of global assets at risk of flooding by 2100. A total of 68% of the global coastal area flooded will be caused by tide and storm events with 32% due to projected regional sea level rise.

Uncertainties in projections of sandy beach erosion due to sea level rise: an analysis at the European scale.

Sea level rise (SLR) will cause shoreline retreat of sandy coasts in the absence of sand supply mechanisms. These coasts have high touristic and ecological value and provide protection of valuable infrastructures and buildings to storm impacts. So far, large-scale assessments of shoreline retreat use specific datasets or assumptions for the geophysical representation of the coastal system, without any quantification of the effect that these choices might have on the assessment. Here we quantify SLR driven potential shoreline retreat and consequent coastal land loss in Europe during the twenty-first century using different combinations of geophysical datasets for (a) the location and spatial extent of sandy beaches and (b) their nearshore slopes. Using data-based spatially-varying nearshore slope data, a European averaged SLR driven median shoreline retreat of 97 m (54 m) is projected under RCP 8.5 (4.5) by year 2100, relative to the baseline year 2010. This retreat would translate to 2,500 km2 (1,400 km2) of coastal land loss (in the absence of ambient shoreline changes). A variance-based global sensitivity analysis indicates that the uncertainty associated with the choice of geophysical datasets can contribute up to 45% (26%) of the variance in coastal land loss projections for Europe by 2050 (2100). This contribution can be as high as that associated with future mitigation scenarios and SLR projections.

Projected 21st century changes in extreme wind-wave events.

We describe an innovative approach to estimate global changes in extreme wave conditions by 2100, as a result of projected climate change. We generate a synthetic dataset from an ensemble of wave models forced by independent climate simulation winds, enhancing statistical confidence associated with projected changes in extreme wave conditions. Under two IPCC representative greenhouse gas emission scenarios (RCP4.5 and RCP8.5), we find that the magnitude of a 1 in 100-year significant wave height (H s ) event increases by 5 to 15% over the Southern Ocean by the end of the 21st century, compared to the 1979-2005 period. The North Atlantic shows a decrease at low to mid latitudes (≈5 to 15%) and an increase at high latitudes (≈10%). The extreme significant wave height in the North Pacific increases at high latitudes by 5 to 10%. The ensemble approach used here allows statistical confidence in projected changes of extremes.

An assessment of measured and computed depth of closure around Japan.

The development of effective coastal adaptation strategies and protection schemes is a major challenge for coastal zone managers and engineers, not only because the coastal zone is the most populated and developed land zone in the world, but also due to projected climate change impacts. A priori knowledge of the so called depth of closure (DoC) is, more often than not, a pre-requisite to understand and model coastal morphological response to wave forcing, which in turn enables the design of appropriate coastal adaption/protection measures. In the absence of long term measurements of coastal profile data, the DoC is often computed using Hallermeier's formulations or derivatives thereof, for applications around the world. However, there are two major unresolved issues associated with computing the DoC in this way: the accuracy of the wave data required for reliable DoC computations, and the generic applicability of the coefficients used in DoC equations. This study exploits the availability of DoCs derived from multiple measurements of coastal profiles and wave data along the Japanese coast together with wave reanalysis products to evaluate the validity of DoC calculation approaches. Results show that the accuracy of computed DoC values determined using wave reanalysis data is limited, particularly when the spatial resolution of the wave reanalysis data is lower. Furthermore, coefficients of DoC equations proposed in previous and present studies appear to be location specific and points toward the need for a concerted worldwide meta-analysis that compares observed and derived DoC in order to derive a globally applicable formulation for DoC computations.

On the need for a new generation of coastal change models for the 21st century.

The combination of climate change impacts, declining fluvial sediment supply, and heavy human utilization of the coastal zone, arguably the most populated and developed land zone in the world, will very likely lead to massive socio-economic and environmental losses in the coming decades. Effective coastal planning/management strategies that can help circumvent such losses require reliable local scale (<~10 km) projections of coastal change resulting from the integrated effect of climate change driven variations in mean sea level, storm surge, waves, and riverflows. Presently available numerical models are unable to adequately fulfill this need. A new generation of multi-scale, probabilistic coastal change models is urgently needed to comprehensively assess and optimise coastal risk at local scale, enabling risk informed, climate proof adaptation measures that strike a good balance between risk and reward.

Disentangling the relative impacts of climate change and human activities on fluvial sediment supply to the coast by the world's large rivers: Pearl River Basin, China.

The world's large rivers are under stress and experiencing unprecedented changes in hydrology, ecosystems, and fluvial sediment loads. Many of these rivers terminate at the great deltas of the world (home to 500 million people), which depend on fluvial sediments for their very existence. While fluvial sediment loads of large rivers have already been greatly modified by human activities, climate change is expected to further exacerbate the situation. But how does the effect of climate change on fluvial sediment loads compare with that of human impacts? Here, we address this question by combining historical observations and 21st century projections for one of the world's largest 25 rivers containing two mega dams; Pearl River, China. Our analysis shows that variations in fluvial sediment supply to the coast from the Pearl river over a ~150 year study period are dominated by human activities. Projected climate change driven 21st century increases in riverflow will only compensate for about 1% of the human induced deficit in sediment load, leading to the coastal zone being starved of about 6000 Mt of sediment over the remainder of this century. A similar dominance of human impacts on fluvial sediment supply is likely at other heavily engineered rivers.

Author Correction: Quantifying uncertainties of sandy shoreline change projections as sea level rises.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Quantifying uncertainties of sandy shoreline change projections as sea level rises.

Sandy shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy shoreline change projections inherit the uncertainties of future mean sea-level changes, of vertical ground motions, and of other natural and anthropogenic processes affecting shoreline change variability and trends. Furthermore, the erosive impact of sea-level rise itself can be quantified using two fundamentally different models. Here, we show that this latter source of uncertainty, which has been little quantified so far, can account for 20 to 40% of the variance of shoreline projections by 2100 and beyond. This is demonstrated for four contrasting sandy beaches that are relatively unaffected by human interventions in southwestern France, where a variance-based global sensitivity analysis of shoreline projection uncertainties can be performed owing to previous observations of beach profile and shoreline changes. This means that sustained coastal observations and efforts to develop sea-level rise impact models are needed to understand and eventually reduce uncertainties of shoreline change projections, in order to ultimately support coastal land-use planning and adaptation.

Author Correction: The State of the World's Beaches.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

The State of the World's Beaches.

Coastal zones constitute one of the most heavily populated and developed land zones in the world. Despite the utility and economic benefits that coasts provide, there is no reliable global-scale assessment of historical shoreline change trends. Here, via the use of freely available optical satellite images captured since 1984, in conjunction with sophisticated image interrogation and analysis methods, we present a global-scale assessment of the occurrence of sandy beaches and rates of shoreline change therein. Applying pixel-based supervised classification, we found that 31% of the world's ice-free shoreline are sandy. The application of an automated shoreline detection method to the sandy shorelines thus identified resulted in a global dataset of shoreline change rates for the 33 year period 1984-2016. Analysis of the satellite derived shoreline data indicates that 24% of the world's sandy beaches are eroding at rates exceeding 0.5 m/yr, while 28% are accreting and 48% are stable. The majority of the sandy shorelines in marine protected areas are eroding, raising cause for serious concern.

ASSESSING CLIMATE CHANGE IMPACTS ON THE STABILITY OF SMALL TIDAL INLETS: Part 2- DATA RICH ENVIRONMENTS.

Climate change (CC) is likely to affect the thousands of bar-built or barrier estuaries (here referred to as Small tidal inlets - STIs) around the world. Any such CC impacts on the stability of STIs, which governs the dynamics of STIs as well as that of the inlet-adjacent coastline, can result in significant socio-economic consequences due to the heavy human utilisation of these systems and their surrounds. This article demonstrates the application of a process based snap-shot modelling approach, using the coastal morphodynamic model Delft3D, to 3 case study sites representing the 3 main STI types; Permanently open, locationally stable inlets (Type 1), Permanently open, alongshore migrating inlets (Type 2) and Seasonally/Intermittently open, locationally stable inlets (Type 3). The 3 case study sites (Negombo lagoon - Type 1, Kalutara lagoon - Type 2, and Maha Oya river - Type 3) are all located along the southwest coast of Sri Lanka. After successful hydrodynamic and morphodynamic model validation at the 3 case study sites, CC impact assessment are undertaken for a high end greenhouse gas emission scenario. Future CC modified wave and riverflow conditions are derived from a regional scale application of spectral wave models (WaveWatch III and SWAN) and catchment scale applications of a hydrologic model (CLSM) respectively, both of which are forced with IPCC Global Climate Model output dynamically downscaled to ~ 50 km resolution over the study area with the stretched grid Conformal Cubic Atmospheric Model CCAM. Results show that while all 3 case study STIs will experience significant CC driven variations in their level of stability, none of them will change Type by the year 2100. Specifically, the level of stability of the Type 1 inlet will decrease from 'Good' to 'Fair to poor' by 2100, while the level of (locational) stability of the Type 2 inlet will also decrease with a doubling of the annual migration distance. Conversely, the stability of the Type 3 inlet will increase, with the time till inlet closure increasing by ~75%. The main contributor to the overall CC effect on the stability of all 3 STIs is CC driven variations in wave conditions and resulting changes in longshore sediment transport, not Sea level rise as commonly believed.