Accession Number:

ADA551426

Title:

Data Enhanced Modeling of Sea and Swell on the Continental Shelf

Descriptive Note:

Annual rept.

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF OCEANOGRAPHY

Report Date:

1998-01-01

Pagination or Media Count:

4.0

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 e.g., remotely sensed or in situ and measurement locations e.g., at the offshore model boundary or in the nearshore that provide the most useful constraints on model predictions will be identified. Our approach for improving the SWAN wave propagation scheme first-order, upwind is to explore a variety of higher order schemes that have been developed or proposed by others in related research fields. The primary shortcoming of the first-order scheme has been the excessive directional diffusion of wave energy as it progresses through the numerical domain. Therefore, one of the principal standards for judging the higher order schemes is their stability in this regard. The most promising higher order scheme will be implemented in the SWAN model. Our approach to adding data assimilation capabilities to the SWAN model is to identify the types of wave measurements available on or near the continental shelf, relate these measurements to the SWAN models spectral output with as few additional assumptions as possible, and assimilate this information using methods that are computationally feasible for use in future operational products. An operational shallow water swell prediction model for the California coast, initialized with deep water forecast spectra from the FNMOC global WAM model, will be used as a baseline for assessing the benefits of different data assimilation strategies.

Subject Categories:

  • Physical and Dynamic Oceanography
  • Fluid Mechanics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE