Modeling surface wind waves and their effects on air-sea fluxes in Chesapeake Bay

In this study, surface wind waves and their effects on air-sea fluxes of momentum, sensible and latent heat were investigated using both field measurements of wave and atmospheric boundary layer data and numerical wave and meteorology models in Chesapeake Bay. The wave models SWAN and GLERL were tested against three wave data sets, and both performed well. GLERL was used for subsequent wind wave forecasts because of its computational speed.; A tower experiment yielded high quality simultaneous data on surface waves and air-sea fluxes. The data showed that the air-sea drag coefficient (Cd) depends on both wind speed and wave age. For low winds, Cd increases as wind decreases. For higher winds, Cd increases as wind speed increases and it decreases as wave age increases. The data show a 20--30% smaller Cd than most other investigators have found. These results led to modification of both models. SWAN predictions fit the measured data better with a lower Cd. After the GLERL model was modified to include a wave age and wave height dependent surface roughness, z0, young waves were predicted to grow much faster. Cd, a byproduct of GLERL, was significantly lower and agreed with the data better after GLERL was properly tuned.; The GLERL model was coupled with a meso-scale meteorology model, RAMS. Significant differences appeared several hours after the coupled simulations were begun. At the tower location under low wind conditions, the coupled model run tended to predict a higher wind than the uncoupled model run. For higher winds, the coupled model run sometimes predicted a higher wind and sometimes predicted a lower wind. Wind fields over the entire domain were affected by model coupling, as well as predicted sensible and latent heat fluxes. The wave conditions predicted by the coupled run were also different from the uncoupled run.; The present study has established a solid foundation for continued work developing a fully coupled modeling system to improve surface wind and air-sea fluxes predictions as they are affected by the presence of waves, and to improve wave predictions as they are affected by the accuracy of surface wind.