Emily Foshee

Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Atmospheric Science

Committee Chair

Udaysankar Nair

Committee Member

Larry D. Carey

Committee Member

John R. Mecikalski

Committee Member

Arastoo Biazar

Committee Member

Pawan Gupta


Wind forecasting, Weather forecasting, Tehuantepec, Gulf of (Mexico)


Mountain Gap Winds (MGW) are low-level jets forced by gaps along elongated complex terrain that act as flow barriers. A prominent occurrence of MGW, forced by the Chivela pass in southern Mexico, is found over the Gulf of Tehuantepec in the eastern Pacific where it impacts air, marine transport, fisheries, and tropical cyclogenesis. Though this MGW was subject of numerous studies, crucial aspects yet to be addressed include improving the forecasting of this phenomenon and understanding the impact of MGW on the evolution of tropical cyclones in the East Pacific. Computationally inexpensive linear regression model (LRM) and Recurrent Neural Network (RNN) can be used to improve MGW forecasts from coarse resolution numerical models. Weather Research and Forecast (WRF) model forecasts can be improved by adequately resolving flow through the mountain gap and by using dynamic ocean-atmosphere coupling. Performance of LRM and RNN are comparable to such WRF forecasts. WRF simulations show the presence of MGW in the eastern Pacific can intensify tropical cyclones and enhance rainfall. Unique contributions of this study include: 1) new methods for MGW forecasting, 2) a better understanding of MGW dynamics contributing to improvements in numerical prediction, and 3) first numerical modeling investigation of MGW impacts on tropical cyclones.



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