Navy Nearshore Ocean Prediction Systems

Proc. 5 th AMS Coastal Conf, 2003

2008

An easily operable computational system has been designed to simulate waves and longshore currents. The system is composed of a MATLAB GUI in the foreground, which directs the integration of the SWAN shallow water wave model with a 1D surf model in the background. This newly developed tool first performs a rapid implementation of SWAN in a specific site followed by a comprehensive evaluation of the wave model output. Cross-shore profiles and other surf model input parameters are defined graphically directly from the SWAN output results. Longshore currents are then evaluated immediately in various locations. Besides testing the application of the described system in different environments, a comparison to measurements from a field experiment is also performed. Comparisons were made for longshore current velocities from both 'in situ' measurements as well as currents resulting from quasi-3D nearshore circulation model (SHORECIRC) simulations. The results indicate that the system developed provides reasonable predictions and that the hybrid modeling approach used can be also applied in some areas where the 1D beach paradigm is not valid.

2005

2011

Abstract: The present project is part of a comprehensive effort by the PI, his students, and collaborators at the Naval Research Laboratory to increase the robustness and viability of the Delft3D model suite as an operational forecasting tool, and aid its continued transition to Navy forecasting centers. Prior projects have focused on determining the model s response to characteristics and sample sizes of bathymetric information. The present project focuses on determining the effect of boundary errors on model response, and the development of ...

Journal of Coastal Research, 2010

1998

Abstract: Our long-term goal is to contribute to the accurate prediction of surface gravity wave generation, propagation, and dissipation in coastal regions through the combined use of measurements and models. Our primary objectives are to develop robust wave data assimilation and higher order wave propagation schemes for the Delft Hydraulics shallow water SWAN model. In the process of developing the wave data assimilation methods, the types of wave data (eg, remotely sensed or in situ) and measurement locations (eg, at the ...

Journal of Marine Science and Technology

The objective of the present work is to illustrate the performances of the numerical wave models in ocean and coastal environment. Third generation wave models are considered nowadays the most appropriate for such task. These are full spectral models based on the integration on the wave energy (or alternatively wave action) balance equation. In order to cover more aspects related with the modelling process hindcast, nowcast and forecast schemes are discussed and illustrated along six case studies. The major model used was SWAN (acronym for Simulating Waves Nearshore) which is a very flexible model that can be applied in a wide range of coastal applications being effective from high resolution coastal areas up to quasi oceanic scales. In both hindcasts and forecasts the wave forcing was provided by generation models (WAM and WW3), while in nowcast schemes buoy data were used. Various coastal environments that are rather different from the point of view of the bathymetric features and of the characteristics of the environmental matrix were considered. These are the Portuguese continental nearshore with higher resolution sub domains, Madeira Archipelago, the nearshore of Sardinia Island in the Mediterranean Sea and the Black Sea. A general conclusion of this work would be that, despite some limitations, the wave models provide an effective framework in predicting wave conditions in ocean and coastal environment.

Global wind-wave models such as the National Oceanic and Atmospheric Administration WaveWatch 3 (NWW3) play an important role in monitoring the world's oceans. However, untransformed data at grid points in deep water provide a poor estimate of swell characteristics at nearshore locations, which are often of significant scientific, engineering, and public interest. Explicit wave modeling, such as the Simulating Waves Nearshore (SWAN), is one method for resolving the complex wave transformations affected by bathymetry, winds, and other local factors. However, obtaining accurate bathymetry and determining parameters for such models is often difficult. When target data is available (i.e., from in situ buoys or human observers, empirical alternatives such artificial neural networks (ANNs) and linear regression may be considered for inferring nearshore conditions from offshore model output. Using a sixfold cross-validation scheme, significant wave height H s and period were estimated at one onshore and two nearshore locations. In estimating H s at the shoreline, the validation performance of the best ANN was r = 0.91, as compared to those of linear regression (0.82), SWAN (0.78), and the NWW3 H s baseline (0.54).