Date of Award
12-2025
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
School
Ocean Science and Engineering
Committee Chair
Dr.Diana Bernstein
Committee Chair School
Ocean Science and Engineering
Committee Member 2
Dr. Jerry Wiggert
Committee Member 2 School
Ocean Science and Engineering
Committee Member 3
Dr. Denis Wiesenburg
Committee Member 3 School
Ocean Science and Engineering
Committee Member 4
Dr. Kemal Cambazoglu
Committee Member 4 School
Ocean Science and Engineering
Committee Member 5
Dr. Brian Dzwonkowski
Abstract
High waves in the Gulf of Mexico, caused by tropical cyclones and winter storms, pose significant threats to coastal communities and marine activities. Wave prediction depends on precise wind field estimates, but current atmospheric model outputs often show considerable bias during severe weather events. This dissertation aims to develop and apply wind-wave modeling frameworks to obtain more accurate results and improve coastal hazard predictions in the Gulf of Mexico.
The research uses three interconnected studies with numerical modeling approaches. First, available wind data were evaluated, and wave sensitivity analysis was performed using the unstructured SWAN model with five distinct wind data sources from ECMWF and NCEP global and regional models, validated against National Data Buoy Center observations. Second, the high-resolution Weather Research and Forecasting (WRF) model was optimized through systematic testing of different domain configurations and various physics parameterization schemes during Hurricane Michael (2018). Third, a multi-physics ensemble simulation framework was adopted by integrating the WRF model results with SWAN wave simulations to simulate hurricane-induced waves. Key results show that FNL and NAM wind datasets offer better correlation with observations, while ECMWF Real-Time products combined with Janssen schemes give the best wave estimates, with minimal error and maximal correlation. The selected nested domain setup at 0.1° resolution cut the RMSE by up to 10% and reduced bias by over 60% compared to other available datasets. The best WRF physics setup includes Lin and WSM6 microphysics with the YSU planetary boundary layer scheme, and performed consistently across coastal stations, with fair agreement at the nearshore stations with higher complexity and more importance. The ensemble simulation framework, using eleven WRF simulations with varied wind inputs for SWAN, proved more reliable through simple averaging and an ensemble wind-related product. Overall, these findings help recommend a framework for high-precision coastal wind-wave prediction during extreme tropical cyclone events. By optimizing wind field generation and wave modeling, this research may offer an essential tool for wind-wave prediction, reliable for coastal management, marine planning, and engineering resilience. The ensemble simulation approach has great potential for operational use for hazard warning systems, supporting better risk reduction and public safety in the Gulf of Mexico coastal areas, especially for the Mississippi Bight.
ORCID ID
0000-0002-3448-2103
Copyright
Azadeh Razavi Arab, 2025
Recommended Citation
Razavi Arab, Azadeh, "Enhanced Wind and Wave Modeling of Tropical Cyclone Events in the Gulf of Mexico" (2025). Dissertations. 2405.
https://aquila.usm.edu/dissertations/2405
Included in
Civil and Environmental Engineering Commons, Climate Commons, Meteorology Commons, Oceanography Commons, Other Oceanography and Atmospheric Sciences and Meteorology Commons