Lagrangian circulation on the Southeast US Continental Shelf: Implications for larval dispersal and retention

Lagrangian characterization of continental shelf circulation provides estimates of the retention and transport of particulate and dissolved substances. In this paper, we quantify the retentive characteristics of the Southeast U.S. Continental Shelf by comparing observed and numerical (modeled) drifters released throughout 2000 and 2001. Agreement between the observed and computed drifter trajectories shows that retention on this shelf can be up to two months at any point during the year. These results have important implications for ecological and fisheries applications and indicate that the populations of marine organisms in this region might be relatively closed (i.e., with weak exchange) during some periods of the year

Monthly climatology of the continental shelf waters of the South Atlantic Bight

Monthly circulation of the South Atlantic Bight is diagnosed using a 3-D, shallow water, finite element model forced with monthly wind stress and hydrographic climatology. Temperature and salinity observations from the period 1950-1999 are objectively interpolated onto the model domain, and Comprehensive Ocean-Atmosphere Data Set (COADS) wind velocities from 1975-1999 are used to prescribe the model surface wind stress. The resulting monthly temperature and salinity fields compare favorably to existing shelf climatology. River discharge maxima are evident in the spring temperature and salinity fields, and the rapid heating and cooling of the shelf are captured. The diagnostic circulation is largely wind-driven in the inner and mid-shelf, and the Gulf Stream is apparent in the solutions on the outer shelf. We present the monthly fields, including the temporal and spatial distribution of available hydrographic data, the regional COADS data that provide surface wind stress forcing, the objective analysis, and the model response to these forcings. The hydrographic and velocity fields provide best-prior-estimates of the circulation for data assimilation studies in the region, as well as initial conditions for process-oriented prognostic model studies in the Georgia coastal region

Low frequency water level correction in storm surge models using data assimilation

Research performed to-date on data assimilation (DA) in storm surge modeling has found it to have limited value for predicting rapid surge responses (e.g., those accompanying tropical cyclones). In this paper, we submit that a well-resolved, barotropic hydrodynamic model is typically able to capture the surge event itself, leaving slower processes that determine the large scale, background water level as primary sources of water level error. These “unresolved drivers” reflect physical processes not included in the model's governing equations or forcing terms, such as far field atmospheric forcing, baroclinic processes, major ocean currents, steric variations, or precipitation. We have developed a novel, efficient, optimal interpolation-based DA scheme, using observations from coastal water level gages, that dynamically corrects for the presence of unresolved drivers. The methodology is applied for Hurricane Matthew (2016) and results demonstrate it is highly effective at removing water level residuals, roughly halving overall surge errors for that storm. The method is computationally efficient, well-suited for either hindcast or forecast applications and extensible to more advanced techniques and datasets

The role of hydrodynamics in explaining variability in fish populations

A review of the physical processes present in coastal regions and their effect on pelagic stages of flatfish populations is presented. While quantitative understanding of processes affecting cross-shelf transport and exchange continues to be a fundamental problem shared by physical oceanographers and fisheries scientists studying the early life history of flatfish, advances in hydrodynamic and coupled physical-biological models have made it possible to begin to examine population-level implications of environmental processes. There is now a need to rank these processes in terms of their impact on recruit strength. Existing paradigms provide testable frameworks for explaining the role of physical variability in the observed population patterns, abundance and variability. Identifying explicit links between physical variability and recruitment could result in new approaches to fisheries management strategies

Cold event in the South Atlantic Bight during summer of 2003: Model simulations and implications

A set of model simulations are used to determine the principal forcing mechanisms that resulted in anomalously cold water in the South Atlantic Bight (SAB) in the summer of 2003. Updated mass field and elevation boundary conditions from basin-scale Hybrid Coordinate Ocean Model (HYCOM) simulations are compared to climatological forcing to provide offshore and upstream influences in a one-way nesting sense. Model skill is evaluated by comparing model results with observations of velocity, water level, and surface and bottom temperature. Inclusion of realistic atmospheric forcing, river discharge, and improved model dynamics produced good skill on the inner shelf and midshelf. The intrusion of cold water onto the shelf occurred predominantly along the shelf-break associated with onshore flow in the southern part of the domain north of Cape Canaveral (29° to 31.5°). The atmospheric forcing (anomalously strong and persistent upwelling-favorable winds) was the principal mechanism driving the cold event. Elevated river discharge increased the level of stratification across the inner shelf and midshelf and contributed to additional input of cold water into the shelf. The resulting pool of anomalously cold water constituted more than 50% of the water on the shelf in late July and early August. The excess nutrient flux onto the shelf associated with the upwelling was approximated using published nitrate-temperature proxies, suggesting increased primary production during the summer over most of the SAB shelf

Variability in Coastal Flooding predictions due to forecast errors during Hurricane Arthur

Storm surge prediction models rely on an accurate representation of the wind conditions. In this paper, we examine the sensitivity of surge predictions to forecast uncertainties in the track and strength of a storm (storm strength is quantified by the power dissipation of the associated wind field). This analysis is performed using Hurricane Arthur (2014), a Category 2 hurricane, which made landfall along the North Carolina (NC) coast in early July 2014. Hindcast simulations of a coupled hydrodynamic-wave model are performed on a large unstructured mesh to analyze the surge impact of Arthur along the NC coastline. The effects of Arthur are best represented by a post-storm data assimilated wind product with parametric vortex winds providing a close approximation. Surge predictions driven by forecast advisories issued by the National Hurricane Center (NHC) during Arthur are analyzed. The storm track predictions from the NHC improve over time. However, successive advisories predict an unrealistic increase in the storm's strength. Due to these forecast errors, the global root mean square errors of the predicted wind speeds and water levels increase as the storm approaches landfall. The relative impacts of the track and strength errors on the surge predictions are assessed by replacing forecast storm parameters with the best known post-storm information about Arthur. In a “constant track” analysis, Arthur's post storm determined track is used in place of the track predictions of the different advisories but each advisory retains its size and intensity predictions. In a “constant storm strength” analysis, forecast wind and pressure parameters are replaced by corresponding parameters extracted from the post storm analysis while each advisory retains its forecast storm track. We observe a strong correlation between the forecast errors and the wind speed predictions. However, the correlation between these errors and the forecast water levels is weak signifying a non-linear response of the shallow coastal waters to meteorological forcing

Downscaling of real-time coastal flooding predictions for decision support

During coastal storms, forecasters and researchers use numerical models to predict the magnitude and extent of coastal flooding. These models must represent the large regions that may be affected by a storm, and thus, they can be computationally costly and may not use the highest geospatial resolution. However, predicted flood extents can be downscaled (by increasing resolution) as a post-processing step. Existing downscaling methods use either a static extrapolation of the flooding as a flat surface, or rely on subsequent simulations with nested, full-physics models at higher resolution. This research explores a middle way, in which the downscaling includes simplified physics to improve accuracy. Using results from a state-of-the-art model, we downscale its flood predictions with three methods: (1) static, in which the water surface elevations are extrapolated horizontally until they intersect the ground surface; (2) slopes, in which the gradient of the water surface is used; and (3) head loss, which accounts for energy losses due to land cover characteristics. The downscaling methods are then evaluated for forecasts and hindcasts of Hurricane Florence (2018), which caused widespread flooding in North Carolina. The static and slopes methods tend to over-estimate the flood extents. However, the head loss method generates a downscaled flooding extent that is a close match to the predictions from a higher-resolution, full-physics model. These results are encouraging for the use of these downscaling methods to support decision-making during coastal storms

Barotropic tides in the South Atlantic Bight

The characteristics of the principal barotropic diurnal and semidiurnal tides are examined for the South Atlantic Bight (SAB) of the eastern United States coast. We combine recent observations from pressure gauges and ADCPs on fixed platforms and additional short-term deployments off the Georgia and South Carolina coasts together with National Ocean Service coastal tidal elevation harmonics. These data have shed light on the regional tidal propagation, particularly off the Georgia/South Carolina coast, which is perforated by a dense estuary/tidal inlet complex (ETIC). We have computed tidal solutions for the western North Atlantic Ocean on two model domains. One includes a first-order representation of the ETIC in the SAB, and the other does not include the ETIC. We find that the ETIC is highly dissipative and affects the regional energy balance of the semidiurnal tides. Nearshore, inner, and midshelf model skill at semidiurnal frequencies is sensitive to the inclusion of the ETIC. The numerical solution that includes the ETIC shows significantly improved skill compared to the solution that does not include the ETIC. For the M2 constituent, the largest tidal frequency in the SAB, overall amplitude and phase error is reduced from 0.25 m to 0.03 m and 13.8° to 2.8° for coastal observation stations. Similar improvement is shown for midshelf stations. Diurnal tides are relatively unaffected by the ETIC

Influence of storm timing and forward speed on tides and storm surge during Hurricane Matthew

The amount and extent of coastal flooding caused by hurricanes can be sensitive to the timing or speed of the storm. For storms moving parallel to the coast, the hazards can be stretched over a larger area. Hurricane Matthew was a powerful storm that impacted the southeastern U.S. during October 2016, moving mostly parallel to the coastline from Florida through North Carolina. In this study, three sources for atmospheric forcing are considered for a simulation of Matthew's water levels, which are validated against extensive observations, and then the storm's effects are explored on this long coastline. It is hypothesized that the spatial variability of Matthew's effects on total water levels is partly due to the surge interacting nonlinearly with tides. By changing the time of occurrence of the storm, differences in storm surge are observed in different regions due to the storm coinciding with other periods in the tidal cycles. These differences are found to be as large as 1 m and comparable to the tidal amplitude. A change in forward speed of the storm also should alter its associated flooding due to differences in the duration over which the storm impacts the coastal waters. With respect to the forward speed, the present study contributes to established results by considering the scenario of a shore-parallel hurricane. A faster storm caused an increase in peak water levels along the coast but a decrease in the overall volume of inundation. On the other hand, a slower storm pushed more water into the estuaries and bays and flooded a larger section of the coast. Implications for short-term forecasting and long-term design studies for storms moving parallel to long coastlines are discussed herein

Real-time data assimilative modeling on Georges bank

Real-time oceanic forecasts were constructed at sea on Georges Bank during Spring 1999. Ship- and shore-based computations were combined to deliver daily 3-day forecasts to shipboard scientists for interpreting observations and planning operations. Data assimilated included acoustic Doppler current profiler velocities, drifter trajectories, and taxa-specific plankton observations from a Video Plankton Recorder (VPR) system. Services provided included basic 3-D circulation forecasts, forecast positions of drifters, dye and zoo-plankton, and the advective adjustment of observations to produce synoptic maps. The results indicate that real-time, at-sea data assimilative modeling can provide valuable information services and can be deployed routinely, provided that networking among ships, instruments, and shore continues to improve. This paper summarizes the real-time modeling experience. Results of the larger effort including scientific data interpretation are being reported separately