Regional Wave Climate Research Articles

Morphology and Sediment Dynamics of Blossom Shoals at Icy Cape, Alaska

AbstractCapes and cape‐associated shoals represent sites of convergent sediment transport, and can provide points of relative coastal stability, navigation hazards, and offshore sand resources. Shoal evolution is commonly impacted by the regional wave climate. In the Arctic, changing sea‐ice conditions are leading to (a) longer open‐water seasons when waves can contribute to sediment transport, and (b) an intensified wave climate (related to duration of open water and expanding fetch). At Blossom Shoals offshore of Icy Cape in the Chukchi Sea, these changes have led to a five‐fold increase in the amount of time that sand is mobile at a 31‐m water depth site between the period 1953–1989 and the period 1990–2022. Wave conditions conducive to sand transport are still limited to less than 2% of the year, however—and thus it is not surprising that the overall morphology of the shoals has changed little in 70 years, despite evidence of active sand transport in the form of 1‐m‐scale sand waves on the flanks of the shoals which heal ice keel scours formed during the winter. Suspended‐sediment transport is relatively weak due to limited sources of mud nearby, but can be observed in a net northeastward direction during the winter (driven by the Alaska Coastal Current under the ice) and in a southwestward direction during open‐water wind events. Longer open‐water seasons mean that annual net northeastward transport of fine sediment may weaken, with implications for the residence time of fine‐grained sediments and particle‐associated nutrients in the Chukchi Sea.

GLOBAL WAVE CLIMATE TRENDS: WHAT DO THE SOUTHERN HEMISPHERE WAVE BUOYS TELL US?

Australia’s national wave data network presently consists of around 35 directional wave buoys distributed across the Australian coastline, with 11 of these buoys have been in operation since the mid-seventies. South Africa is home to 4 offshore wave buoys which have operating since the early eighties. New Zealand wave buoy network is relatively younger, with 3 wave buoys in operation since the early 2000s. All of these buoys have been providing invaluable longterm historical wave data which have allowed the offshore and coastal scientific community to better assess extreme wave climates and their impact on the coastline. Additionally, these data records of wave observations are key for model validation and to better understand the effects of climate change on the local and regional wave climate.

PREDICTING SHORELINE EVOLUTION IN A CHANGING WAVE CLIMATE

Reliable predictions of shoreline evolution at a range of time scales both now and by end of the century are required for assessing coastal vulnerability in a changing climate. This is particularly important given the possible changes in regional wave climates and/or ocean water levels due to climate variability. To this end, much work has gone into the development of simple and efficient semi-empirical shoreline models that can be used to predict shoreline evolution over time scales ranging from seasonal to multi-decadal. An alternative is to use time-varying model parameters to improve model predictability at interannual timescales. Kalman filter techniques offer a framework to detect time-varying (or non-stationary) model parameters by adjusting them as shoreline observations become available. Ibaceta et al. (2020) implemented a dual state parameter Ensemble Kalman Filter (EnKF) within the shoreline evolution model ShoreFor (Davidson et al., 2013), and showed that this methodology is suitable to detect parameter changes that best hindcasted observed shoreline evolution. Additionally, they demonstrated that this observed parameter non-stationarity could be linked to the changing characteristics of the underlying wave forcing. The application of this methodology over long-term datasets now enables the parametrization and physical interpretation of the model parameters as a function of the multi-year variability in wave forcing, allowing for enhanced shoreline predictions out of the selected training period.

Coastal boulder movement on a rocky shoreline in northwest Ireland from repeat UAV surveys using Structure from Motion photogrammetry

The degree of boulder mobility in response to coastal storms likely varies spatially and temporally along rocky shorelines, but this is difficult to evaluate from field monitoring of individual boulders alone. Structure from Motion (SfM) photogrammetry can be used to analyse changes in shoreline geomorphology or boulder distributions over time and space from rocky shorelines. This study employs data from repeated Unpiloted Aerial Vehicle (UAV) surveys in 2017, 2018, 2019 and 2022 along a 1-km stretch of a rocky shoreline in northwest Ireland. SfM techniques were used to generate orthomosaics of the bedrock platform surface from which distributions and transport patterns of boulders were examined. Based on the identification of specific boulders that appear in images from successive time slices, 16–32 % of boulders had remained stationary (had either rotated or flipped on the spot, but experienced no change in boulder position), 18–39 % had moved but less than the calculated Root Mean Square Error (RMSE) value of 23 cm, and 29–66 % of boulders had moved greater than the RMSE value, and <29 m distance in one case. In addition, a significant minority of boulders also appeared or disappeared (3–23 %) between successive time slices, which may reflect their episodic transport to/from the sea or beyond the region of interest. Overall, the results indicate that boulder movement is highly variable over time and space and does not appear to correspond with episodic wave forcing. This is different to previous studies that have described a simple deterministic relationship between boulder movement and singular wave forcing events such as storms. Repeated UAV surveys provide a consistent methodology for understanding rocky shoreline and boulder dynamics, and can offer insight into shoreline sensitivity to regional wave climate operating under more normal or ‘average’ conditions.

Regional wave climate projections forced by EURO‐CORDEX winds for the Black Sea and Sea of Azov towards the end of the 21st century

AbstractWave phenomena impact high commercial value coastal and offshore activities, infrastructures and transportation. The knowledge of future wave conditions allows for consistent long‐term planning and decision‐making. The present study aims to provide robust, reliable projections of the potential future wave conditions of the Black Sea under the influence of climate change. For this purpose, an eight‐member dynamic wave climate ensemble that accurately represents the Black Sea's present wave climate has been produced, and future projections are assessed and analysed here. The wave climate ensemble was obtained by forcing the Simulating Waves Nearshore spectral wave model with eight regional wind fields from the EURO‐CORDEX. The future simulations of the regional wind fields are based on the RCP8.5 high‐emission scenario. The historical wave climate of the ensemble was evaluated against ERA5 reanalysis data. Projected changes in the mean wind and wave characteristics are examined by comparing historical and future simulations. In addition, the projected trends in the annual means during the future period of the wave simulations for significant wave height (Hs) and wave energy flux are also analysed. The projections for Hs and wind speeds are pronounced with significant decreases down to −10% across the basin, especially in the eastern region of the Black Sea. Changes in the Hs 99% percentiles of up to 16% are projected to occur. The projected changes in the annual mean of the wave energy flux are close to the projected changes in Hs means, while the seasonal changes (between −15% and 12%) are expected to be higher.

Projected 21st Century Wind‐Wave Climate of Bass Strait and South‐East Australia: Comparison of EC‐Earth3 and ACCESS‐CM2 Climate Model Forcing

AbstractThis study analyses the past and future wave climate of Bass Strait and south‐east Australia by comparing two high‐resolution regional wave climate models (RWCMs), respectively forced by the surface wind speed of EC‐Earth3 and ACCESS‐CM2 global circulation models (GCMs) under two emission scenarios (SSP1‐2.6 and SSP5‐8.5). The two RWCMs are verified against long‐term buoy and satellite observations as well as hindcast model data. The comparison with long‐term satellite altimeter observations shows good agreement between the long‐term model climate and the observations. Both RWCMs project a future increase in swell, approaching the coast of Tasmania and mainland Australia, generated from distant storms in the Southern Ocean. However, different projected wave height spatial distributions are found in the coastal regions, affected by local synoptic weather events and by the coarse resolution of the GCMs winds. We also show that the long‐term wave climate in the domain is impacted by the Southern Annular Mode. As low‐pressure systems are projected to move southward, especially in the SSP5‐8.5 scenario, the swells approaching south‐east Australia are projected to be longer and more energetic in the future. The combination of more energetic swell systems and a counterclockwise rotation in peak wave direction, projected by both RWCMs, may influence the coastal equilibrium, impacting critical coastal locations.

Improving multi-decadal coastal shoreline change predictions by including model parameter non-stationarity

Our ability to predict sandy shoreline evolution resulting from future changes in regional wave climates is critical for the sustainable management of coastlines worldwide. To this end, the present generation of simple and efficient semi-empirical shoreline change models have shown good skill at predicting shoreline changes from seasons up to several years at a number of diverse sites around the world. However, a key limitation of these existing approaches is that they rely on time-invariant model parameters, and assume that beaches will evolve within constrained envelopes of variability based on past observations. This raises an interesting challenge because the expected future variability in key meteocean and hydrodynamic drivers of shoreline change are likely to violate this ‘stationary’ approach to longer-term shoreline change prediction. Using a newly available, multi-decadal (28-year) dataset of satellite-derived shorelines at the Gold Coast, Australia, this contribution presents the first attempt to improve multi-decadal shoreline change predictions by allowing the magnitude of the shoreline model parameters to vary in time. A data assimilation technique (Ensemble Kalman Filter, EnKF) embedded within the well-established ShoreFor shoreline change model is first applied to a 14-year training period of approximately fortnightly shoreline observations, to explore temporal variability in model parameters. Then, the magnitudes of these observed non-stationary parameters are modelled as a function of selected wave climate covariates, representing the underlying seasonal to interannual variability in wave forcing. These modelled time-varying parameters are then incorporated into the shoreline change model and tested over the complete 28-year dataset. This new inclusion of non-stationary model parameters that are directly modelled as a function of the underlying wave forcing and corresponding time scales of beach response, is shown to outperform the multi-decadal predictions obtained by applying the conventional stationary approach (RMSEnon-stationary = 11.1 m; RMSEstationary = 254.3 m). Based on these results, it is proposed that a non-stationary approach to shoreline change modelling can reduce the uncertainty associated with the misspecification of physical processes driving shoreline change and should be considered for future shoreline change predictions.

Systematization of short-term forecasts of regional wave heights using a machine learning technique and long-term wave hindcast

Machine-learning techniques have been applied to wave forecasting to address the implementational and computational challenges of conventional numerical wave models. Most previous studies emphasized the accuracy of approaches based on in situ wave measurements, but such approaches are site-specific and lack the spatial and temporal fidelity required by regional wave climate forecasts. This study presents a novel systematization of forecasting regional wave heights at sufficient spatial resolution and coverage, using long-term wave hindcasts generated by numerical wave models as a training dataset for a long short-term memory (LSTM). This systematization not only ensures the accuracy of the model's forecasts but demonstrates the applicability of long-term wave hindcasts as input data. It involves thoroughly investigating the dependence of model accuracy on multi-task LSTM structures (training variables, input data record periods, and forecast lead times), and on regional wave climates (different wave sites and sea states). The resulting model performance is spatially heterogeneous in global wave forecasts, underlining the need for validation of wave forecasting models to global wave climates. This study reveals that machine-learning techniques that leverage validated long-term wave hindcasts can successfully forecast regional wave climates. As access to high-resolution regional wave hindcast data improves, accuracy will also increase.

Wave power trends along the U.S. coastline: in situ measurements and model hindcast estimates

Observational data are successfully assessed to investigate wave power (wave energy flux per unit of wave-crest) trends within four coastal regions around the US, a parameter that is deemed vital to those responsible for coastal protection and community resilience. This study tests for shifting observational inter-annual wave power trends using a newly developed, unique, United States Army Corps of Engineers Quality Controlled Consistent Measurement Archive, and offers a viable methodology to remove documented observational time series data discontinuations. This study is one of the first to show spatially and temporally comparative observational and model wave power results, providing new information on the accuracy of model wave power estimates, while showcasing in situ wave power trends at 29 sites around the U.S. coastline. Overall, the majority of the eastern Pacific Ocean and Hawaii wave power trends are downward, with mixed slope wave power trends apparent within the Atlantic Ocean and the Gulf of Mexico. Observational and model results are similar with respect to timing, but not magnitude, of wave power peaks in long-term inter-annual trends, with the moored buoy data presenting smaller wave power ranges for two (eastern Pacific Ocean and Hawaii) of the four regions. Additionally, the detection of a noticeable variability in the wave power trend direction within each region suggests that site-specific wave power trends should not be generalised to represent a large region. This work demonstrates that observational data are essential in local and regional wave climate studies to accurately estimate wave power for coastal planners and engineers.

Foredune height variations along the western coast of Taiwan Strait

AbstractKnowledge of the morphological characteristics of coastal foredunes, particularly crest height, is of crucial importance in evaluating coastal vulnerability to marine disasters. However, the factors driving variation in foredune height and the corresponding mechanisms remain poorly understood, especially for regional, large‐scale landscapes. In this contribution, an extensive foredune–beach topographic survey and comprehensive data collection, including regional wind regime, wave and tide climate, were conducted along the ~400 km‐long western coast of Taiwan Strait. The results show that the factor with the most significant effect on the spatial variation in foredune height is wave power, followed by aeolian drift potential (shore‐normal component), while beach width and grain size appear to have only marginal impacts for our study sites. Under a relatively high‐energy wave climate, significant volumes of sandy sediments can be delivered to the beach–dune system, and the beach state tends to be more dissipative, thus contributing to a higher/larger foredune. In particular, the in‐phase synchronization of sediment supply (contributed by wave processes) and transport potential (controlled by wind processes) can lead to the greatest potential for foredune growth. Finally, the source (river) to sink (coastal foredune) dispersal of sediments along this ~400 km‐long strait coastal regime is summarized.

Rapid-response observations on barrier islands along Cape Fear, North Carolina, during Hurricane Isaias

Hurricane Isaias struck the Cape Fear Region of North Carolina around 23:00 EDT on 3 August 2020, making landfall at Ocean Isle Beach as a Category 1 storm with peak wind speeds of 80 mph. An array of nearshore Sofar Spotter wave buoys captured the wave field at two beaches off the coasts of Bald Head Island (south-facing and east-facing beaches) and Masonboro Island. Local variations in significant wave height and peak wave direction were observed along the Lower Cape Fear Region, due to large shoal features impacting the regional wave climate. A cross-shore transect of five pressure sensors was installed at the north end of Masonboro Island 2.5 days prior to landfall to measure storm surge, wave runup, and variation of gravity/ infragravity wave energy across the barrier island. The three fast-sampling wave gauges along the backshore became buried before Hurricane Isaias peak storm surge, and the two gauges on and behind the dune were never inundated. A low-cost (&lt; $250) Storm Surge Observation Camera (SSOC) prototype captured storm surge and coastal erosion at Kure Beach, in conjunction with pre- and post-storm RTK GPS beach profile surveys. Kure Beach experienced more than 1.0 m of vertical erosion of the berm, while Masonboro Island experienced around 0.1 m of accretion across the backshore, despite nearly identical wave and wind forcing conditions at the two beaches separated by ~20 km. Pre-storm berm height and width (higher and wider at Kure Beach), as well as foreshore slope (steeper, 1:9, at Kure Beach), are likely factors influencing significant erosion at Kure Beach, while slight accretion was observed at Masonboro Island.

Analysis of the New Zealand’s Taranaki regional wave climate using high-resolution modelling

Understanding the regional wave climate is essential for engineering applications. The last two decades have not been included in assessments of the wave climate of New Zealand’s Taranaki region, where the country exploits offshore oil and gas. To make up for this lack of assessment, we carried out a high-resolution long-term (1979–2018) wave hindcast and examined several aspects of the climate in the region. The hindcast data validation against buoy and satellite data showed good agreement and suitability for wave climate analysis. Seasonal wave distributions reveal a bi-modal pattern, composed of (1) more energetic and long period (13–15 s) westerly–southwesterly swells; and (2) shorter-period (∼8 s) southwesterly wind-seas. These signatures result from the region’s high exposure to swells generated by persistent strong winds blowing over long fetches in the Southern Ocean, and to local storm-associated wind-seas, respectively. The largest waves are found offshore, with mean Hs value reaching 2.83 m, 90th percentile 4.3 m, 99th percentile 6.1 m, and maximum 10.8 m. Storm wave monthly climatologies show that storm peaks are largest in the austral autumn, especially in May, while the number of events is the largest in July. Trends in Hs statistics reveal an increase over the past 40 years, with higher rates at higher percentiles. Storm peaks have also increased, by up to 8 cm/decade, whereas the number of storm events has decreased. In agreement with previous work, we found relationships between Hs and climate patterns. Waves get larger in Taranaki waters during El Nino events, as a result of stronger southwesterly winds, and during negative Antarctic Oscillation phases, as westerly winds displace northward.

LONG-TERM PREDICTION OF LONGSHORE SEDIMENT TRANSPORT IN THE CONTEXT OF CLIMATE CHANGE

Due to climate change impacts on atmospheric circulation, global and regional wave climate in many coastal regions around the world might change. Any changes in wave parameters could result in significant changes in wave energy flux, the patterns of coastal sediment transport, and coastal evolution. Although some studies have tried to address the potential impacts of climate change on longshore sediment transport (LST) patterns, they did not sufficiently consider the uncertainties arising from different sources in the projections. In this study, the uncertainty associated with the choice of model used for the estimation of LST is examined. The models were applied to a short stretch of coastline located in Northern Gold Coast, Australia, where a huge volume of sediment is transported along the coast annually. The ensemble of results shows that the future mean annual and monthly LST rate might decrease by about 11 percent, compared to the baseline period. The results also show that uncertainty associated with LST estimation is significant. Hence, it is proposed that this uncertainty, in addition to that from other sources, should be considered to quantify the contribution of each source in total uncertainty. In this way, a probabilistic-based framework can be developed to provide more meaningful output applicable to long-term coastal planningRecorded Presentation from the vICCE (YouTube Link): https://youtu.be/3CGU9RcGYjE

TRANSITIONAL IMPACTS OF ENSO ON WAVE CLIMATE IN COASTAL REGIONS

Amongst all the factors involved in coastal risk assessment, climate variability is key, due to its potential for modifying the coast, particularly through increased seasonal risk of erosion-flooding on the coast (Toimil et al. 2020; Wahl and Plant 2015). The principal driver of interannual variability of the wave climate around the world is El Nio-Southern Oscillation (ENSO). Many researches have focused on the analysis of this phenomenon globally ( Stopa and Cheung 2014), its impacts on regional wave climate (Barnard et al. 2015, 2017; Oderiz et al. 2020; Reguero, Mendez, and Losada 2013) and their local coastal effects ( Mortlock and Goodwin 2016). This interest in ENSO impacts in wave climate is motivated by its capacity to cause coastal erosion (Barnard et al. 2015). Particularly, the temporal and spatial transition of ENSO is nowadays a current issue (Ha et al. 2012). On the worlds coasts, the ENSO impacts delay is not yet fully understood, nor integrated into engineering practices.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/DZbOYztPYW0

Climate-induced variability in South Atlantic wave direction over the past three millennia

Through alteration of wave-generating atmospheric systems, global climate changes play a fundamental role in regional wave climate. However, long-term wave-climate cycles and their associated forcing mechanisms remain poorly constrained, in part due to a relative dearth of highly resolved archives. Here we use the morphology of former shorelines preserved in beach-foredune ridges (BFR) within a protected embayment to reconstruct changes in predominant wave directions in the Subtropical South Atlantic during the last ~ 3000 years. These analyses reveal multi-centennial cycles of oscillation in predominant wave direction in accordance with stronger (weaker) South Atlantic mid- to high-latitudes mean sea-level pressure gradient and zonal westerly winds, favouring wave generation zones in higher (lower) latitudes and consequent southerly (easterly) wave components. We identify the Southern Annular Mode as the primary climate driver responsible for these changes. Long-term variations in interhemispheric surface temperature anomalies coexist with oscillations in wave direction, which indicates the influence of temperature-driven atmospheric teleconnections on wave-generation cycles. These results provide a novel geomorphic proxy for paleoenvironmental reconstructions and present new insights into the role of global multi-decadal to multi-centennial climate variability in controlling coastal-ocean wave climate.

Assessing Reef Island Sensitivity Based on LiDAR-Derived Morphometric Indicators

Reef islands are some of the most highly sensitive landforms to the impacts of future environmental change. Previous assessments of island morphodynamics primarily relied on historical aerial and satellite imagery. These approaches limit analysis to two-dimensional parameters, with no ability to assess long-term changes to island volume or elevation. Here, we use high-resolution airborne LiDAR data to assess three-dimensional reef island features for 22 islands along the north-western coast of Australia. Our primary objective was to utilize two regional LiDAR datasets to identify characteristics indicative of island sensitivity and future vulnerability. Results show reef platform area to be an accurate predictor of island area and volume suggesting larger island volumes may reflect (1) increased carbonate production and supply from the reef platform and/or (2) enhanced shoreline protection by larger reef platforms. Locations of foredune scarping (an erosional signature) and island orientations were aligned to the regional wind and wave climate. Reef island characteristics (island area, volume, elevation, scarping, and platform area) were used to rank islands according to sensitivity, using a new Island Sensitivity Characteristics Index (ISCi) where low ISCi indicates stable islands (large areas and volumes, high elevations, and fewer scarped areas) and high ISCi indicates unstable islands (small areas and volumes, low elevations, and more scarped areas). Comparison of two LiDAR surveys from 2016 and 2018 validates the use of 3D morphometrics as important (direct) measurements of island landform change, and can complement the use of 2D parameters (e.g., area) moving forward. Results demonstrate that ongoing use of airborne LiDAR and other 3D technology for monitoring coral reef islands at regional scales will enable more accurate quantification of their sensitivity to future impacts of global environmental change.

High-resolution hindcasts for U.S. wave energy resource characterization

The marine and hydrokinetic (MHK) industry is at an early stage of development and has the potential to play a significant role in diversifying the U.S. energy portfolio and reducing the U.S. carbon footprint. Wave energy is the largest among all the U.S. MHK energy resources, which include wave energy, ocean current, tidal-instream, ocean thermal energy conversion, and river-instream. Wave resource characterization is an essential step for regional wave energy assessments, Wave Energy Converter (WEC) project development, site selection and WEC design. The present paper provides an overview of a joint modelling effort by the Pacific Northwest National Laboratory and Sandia National Laboratories on high-resolution wave hindcasts to support the U.S. Department of Energy’s Water Power Technologies Office’s program of wave resource characterization, assessment and classifications in all US coastal regions. Topics covered include the modelling approach, model input requirements, model validation strategies, high performance computing resource requirements, model outputs and data management strategies. Examples of model setup and validation for different regions are provided along with application to development of classification systems, and analysis of regional wave climates. Lessons learned and technical challenges of the long-term, high-resolution regional wave hindcast are discussed.

Projections of Extreme Ocean Waves in the Arctic and Potential Implications for Coastal Inundation and Erosion

AbstractThe Arctic Ocean wave climate is undergoing a dramatic change due to the sea ice retreat. This study presents simulations of the Arctic regional wave climate corresponding to the surface winds and sea ice concentrations as simulated by five CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models for the historical (1975–2005) and RCP8.5 scenario future (2081–2100) periods. The annual maximum significant wave height is projected to increase up to 6 m offshore and up to two to three times greater than the corresponding 1979–2005 value along some coastlines, as waves become more exposed to the fall storms there. The connection between the Atlantic Ocean and the Arctic wave climates is projected to strengthen due to increase of swell influence. Changes in the wave direction also seem to indicate a weakening of the Beaufort High illustrated by a counterclockwise rotation of the mean wave direction for extreme conditions in the Western Arctic. The projected changes in wave conditions lead to a general increase of the wave‐driven erosion and inundation potential along the Arctic coastlines. Potentially, hazardous extreme wave events are projected to become significantly more frequent and more intense. For example, in the Beaufort coastlines a once‐in‐20‐year event under the historical (1979–2005) climate is projected to occur, on average, once every 2–5 years during 2081–2100. This is a pressing issue, as it affects many Arctic coastal communities, as well as existing and emerging Arctic infrastructure and activities, with some of them having already suffered severe wave‐induced damage in the past years.

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

Two-dimensional modelling of wave dynamics and wave forces on fringing coral reefs

Two-dimensional numerical modelling of swell wave dynamics on idealized fringing reefs is performed using SWAN, covering a wide range of bathymetries, climate forcing conditions and water depths over the reefs. The results illustrate the impact of reef geometry and bathymetry, coral species and sea level rise on key hydrodynamic parameters on the reef and on forces on corals. The modelling demonstrates that one-dimensional models underestimate the wave action on the reef flat. Wide short reefs and narrow long reefs have similar wave heights at the centre of the reef flat. For a given reef length, the wave height first decreases with increasing reef width, then increases to a local maximum when reef width is approximately equal to the reef length, and then decreases for further increases in width. This pattern is a result of combined dissipation and refraction processes, which combine to lead to different zones of cross-reef wave transformation. Provided that a reef retains its hydrodynamic functions in breaking and refracting the waves, sea level rise enhances the wave heights and wave orbital velocities on the reef flat. If vertical coral growth does not keep pace with sea level rise, loss of the hydrodynamic functions of the reef may occur on deeper reefs, and result in a reduction of near bed velocities with sea level rise. Hydrodynamic forces on corals vary by coral species and SLR changes the magnitude of the forces on different species in different ways, which may lead to less favourable conditions for certain coral species. For long period swell, the intermediate size corals are drag-dominated and behave similarly to branching corals, whereas for short period swell their behavior is similar to that of the inertia-dominated massive corals. For intermediate corals different responses to SLR may therefore be expected for different overall regional wave climates. Over time, this process may contribute to changes in the structural complexity of reefs. The influence of sea level rise on the forces on corals on the reef flat is different under swell and cyclonic wind conditions since wind influences wave period in the latter case.