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Alongshore and temporal variability in wave runup and inner surfzone wave conditions are investigated on an intermediate beach using lidar-derived elevation transect timeseries. The lidar scanners were deployed at two alongshore locations separated by ε330 m at the U.S. Army Engineer Research and Development Center Field Research Facility in Duck, NC and collected 30 min (41 min) linescan time series at 7.1 Hz (5 Hz) each hour over an 11-day period before, during, and after Hurricane Matthew in October 2016. Runup and water surface- elevation time series at the estimated 0.5-m depth contour were used to determine the extreme runup 𝜔2% , the mean runup and inner surfzone water surface elevation, and the significant runup and inner-surf wave heights across sea-swell, infragravity, and all frequency bands. Offshore wave conditions were determined from an array of pressure gauges located in ε8-m water depth. Results show that the significant wave height in the sea- swell frequency band 𝜀𝜗𝜗 was intermittently depth-limited in the inner surf zone, with the ratio of significant sea-swell wave height in the inner surf zone to that in about 8-m depth (𝜀𝜗𝜗,𝜛𝜗𝜚 /𝜀𝜗𝜗,8 m ) ranging from 0.42 to 1.31 during low-energy conditions and from 0.19 to 0.39 during high-energy conditions. Significant temporal variability in runup parameters was observed over the 11-day period, with 𝜔2% ranging from 1.07 to 3.07 m at the southern lidar location and from 1.45 to 3.36 m at the northern lidar location. Alongshore differences in 𝜔2% ranged from 0.00 to 0.90 m, with both 𝜔2% and the significant swash height 𝜔𝜍𝜑𝛻 typically larger at the northern lidar location. Alongshore variability in most inner surfzone and runup parameters was largest during low-energy offshore wave conditions when the inner surf zone was unsaturated, although this trend was weakest in 𝜔2%. The mean runup elevation 𝜔𝜕ℵℶℷ above the still water level was only weakly correlated with the wave-driven super-elevation of the water surface in the inner surf zone (𝜚𝜕ℵℶℷ , R2 = 0.23), suggesting that wave-breaking-induced setup is only one factor contributing to 𝜔𝜕ℵℶℷ . Although the significant sea-swell swash height 𝜔𝜗𝜗 and alongshore differences in 𝜔𝜗𝜗 were correlated with foreshore beach slope ℸ⊳ ⊲0ℵ𝜍1⊲0ℵ (R2 = 0.59 and R2 = 0.70, respectively), 𝜔2% , 𝜔𝜕ℵℶℷ , and alongshore variations thereof were uncorrelated with ℸ⊳ ⊲0ℵ𝜍1⊲0ℵ. 𝜔2% and 𝜔𝜕ℵℶℷ were correlated with the significant wave height in the inner surf zone 𝜀𝜍𝜑𝛻,𝜛𝜗𝜚 (R2 = 0.61 and R2 = 0.72, respectively), which is strongly influenced by wave dissipation patterns across the surf zone. These results suggest that while ℸ⊳ ⊲0ℵ𝜍1⊲0ℵ affects the magnitude of swash oscillations about the mean, it has a smaller role in the total elevation reached by runup on intermediate beaches. Furthermore, the results illustrate the importance of surfzone bathymetry and the resulting temporal and alongshore variations of inner surfzone wave heights to the extreme and mean runup. 

The likelihood of rip currents as a function of water depth (tidal level), incident wave height, period, direction, and spectral spreading in both frequency and direction is investigated with a Boussinesq numerical model (FUNWAVE) for alongshore uniform, moderately variable, and strongly variable bathymetry, providing two- dimensional probability distributions of rip-current occurrence along the coast. The simulations suggest that over strongly irregular alongshore bathymetry rip-current likelihood increases with longer wave periods and narrower directional spectra. In contrast, over more uniform alongshore bathymetry, rip current likelihood in- creases with shorter wave periods and broader directional spectra. The simulations suggest that as bathymetric variability increases, the effects of different incident wave fields decreases. 

Abstract A physics‐informed deep conditional generative model driven with remotely sensed surface currents is shown to estimate surfzone water depths (bathymetry). The model encodes measured flow data as latent Gaussian parameters and decodes these distributions to estimate water depths over the domain, progressively refining its predictions via a loss‐minimization strategy. The model performance is evaluated on in‐distribution and out‐of‐distribution data sets collected in Duck, North Carolina, demonstrating promising site‐specific results, especially given the limited training data set used here (6 bathymetries with a total of 8 flow realizations). However, broader applicability requires transfer learning across a wider range of bathymetric observations. 

Data and code used in Surfzone Water Depth Estimation from Surface Flows Using a Data-Driven and Physics-Informed Deep Conditional Generative Model, 

Abstract Currents transport sediment, larvae, pollutants, and people across and along the surfzone, creating a dynamic interface between the coastal ocean and shore. Previous field studies of nearshore flows primarily have relied on relatively low spatial resolution deployments of in situ sensors, but the development of remote sensing techniques using optical imagery and naturally occurring foam as a flow tracer has allowed for high spatial resolution observations (on the order of a few meters) across the surfzone. Here, algorithms optical current meter (OCM) and particle image velocimetry (PIV) are extended from previous surfzone applications and used to estimate both cross-shore and alongshore 2-, 10-, and 60-min mean surface currents in the nearshore using imagery from both oblique and nadir viewing angles. Results are compared with in situ current meters throughout the surfzone for a wide range of incident wave heights, directions, and directional spreads. Differences between remotely sensed flows and in situ current meters are smallest for nadir viewing angles, where georectification is simplified. Comparisons of 10-min mean flow estimates from a nadir viewing angle with in situ estimates of alongshore and cross-shore currents had correlationsr²= 0.94 and 0.51 with root-mean-square differences (RMSDs) = 0.07 and 0.16 m s⁻¹for PIV andr²= 0.88 and 0.44 with RMSDs = 0.08 and 0.22 m s⁻¹for OCM. Differences between remotely sensed and in situ cross-shore current estimates are at least partially owing to the difference between onshore-directed mass flux on the surface and offshore-directed undertow in the mid–water column. 

Abstract The dissipation of wave energy is important to nearshore circulation and beach profile evolution. Here, radar measurements of wave dissipation at the water surface across the surfzone are used to estimate water velocities and sediment transport in the lower water column to drive an energetics model for morphological change. The radar‐driven model accurately simulates both the 25‐m onshore and the 50‐m offshore migration of a sand bar observed on an Atlantic Ocean beach with a single set of calibration coefficients. Similar to previous studies, wave asymmetry dominated during mild wave conditions when the bar migrated shoreward, and undertow dominated during energetic conditions when the bar migrated seaward. Model results were improved by accounting for both wave bottom boundary layer effects near the sand bar (especially during onshore migration) and the vertical extent of sediment suspension in the undertow transport (especially during offshore migration). 

This dataset contains radar-derived surfzone surface roller energy flux and dissipation data used in: Grossmann, F., Streßer, M., Raubenheimer, B. & Elgar, S. (2025). Radar estimates of surfzone dissipation drive a morphological evolution model, Manuscript submitted for publication. The study investigates the morphological evolution of a sandbar between consecutive bathymetric surveys in environmental conditions that cause onshore (denoted ON1 and ON2) and offshore (denoted OFF) bar migration. The coherent marine radar (CMR) deployment at the U.S. Army Corps of Engineers Research and Development Center's Field Research Facility (FRF) in Duck, North Carolina, USA, was initiated as part of the During Nearshore Event Experiment (DUNEX). A detailed description of the deployment setup is available in: Streßer, M., Collins, C. O. I., Lund, B., Humbertson, J., Horstmann, J., Carrasco, R., Spore, N., & Brodie, K. (2024). Coherent Marine X-Band Radar Deployment during DUNEX (Techreport No. ERDC/CHL TR-24-16). US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory. https://doi.org/10.21079/11681/49218 The data was processed using the methodology described in: Streßer, M., Horstmann, J., & Baschek, B. (2022). Surface Wave and Roller Dissipation Observed With Shore-Based Doppler Marine Radar. Journal of Geophysical Research: Oceans, 127(8), e2022JC018437. https://doi.org/10.1029/2022JC018437 Specifically, the roller energy was computed using equation 14, flux of roller energy using equation 15, and the dissipation of roller energy using equation 17 of Streßer et al. (2022). The radar roller dissipation scaling factor was set to Br = 0.013. The roller slope parameter was set to βs = 0.1. All quantities are computed from 7-min long coherent radar records with a static antenna pointing to 60° from North (nautical convention, i.e. counter-clockwise from North). The radar was located at Latitude/Longitude = 36.1822972/−75.7511785. The antenna was located at an elevation of approx. 15 m (relative to NorthAmerican Vertical Datum of 1988).   As in Streßer et al. (2022), roller energy and dissipation were smoothed using a 5-point moving average filter (in space) to mitigate measurement noise. The unsmoothed raw values are also included in the data set.   Variables in CMR data structure: t: UTC time in Matlab datetime format r: range, i.e. distance from radar antenna [m] xFRF: cross-shore coordinate of FRF local reference system [m] yFRF: alongshore coordinate of FRF local reference system [m] Er: roller energy [J m^(-2)] Fr: flux of roller energy [W m^(-2)] Dr: roller dissipation [W m^(-2)] Er_raw, Fr_raw, and Dr_raw are raw quantities before spatial smoothing.The data is stored in Matlab® v7.3 format. 

Abstract In the surfzone, breaking‐wave generated eddies and vortices transport material along the coast and offshore to the continental shelf, providing a pathway from land to the ocean. Here, surfzone vorticity is investigated with unique field observations obtained during a wide range of wave and bathymetric conditions on an Atlantic Ocean beach. Small spatial‐scale [O(10 m)] vorticity estimated with a 5 m diameter ring of 14 current meters deployed in ∼2 m water depth increased as the directional spread of the wave field increased. Large spatial‐scale [O(100 m)] vorticity calculated from remote sensing estimates of currents across the surfzone along 200 m of the shoreline increased as alongshore bathymetric variability (channels, bars, bumps, holes) increased. For all bathymetric conditions, large‐scale vorticity in the inner surfzone was more energetic than in the outer surfzone. 

Wave-orbital velocities are estimated with particle image velocimetry (PIV) applied to rapid sequences of images of the surfzone surface obtained with a low-cost camera mounted on an amphibious tripod. Time series and spectra of the remotely sensed cross-shore wave-orbital velocities are converted to the depth of colocated acoustic Doppler velocimeters (ADVs), using linear finite depth theory. These converted velocities are similar to the velocities measured in situ (mean nRMSE for time series =16% and for spectra =10%). Small discrepancies between depth-attenuated surface and in situ currents may be owing to errors in the surface velocity measurements, uncertainties in the water depth, the vertical elevation of the ADVs, and the neglect of nonlinear effects when using linear finite depth theory. These results show the potential to obtain spatially dense estimates of wave velocities