Date of Award


Degree Type


Degree Name

Master of Science - Mathematical Sciences


Mathematics and Statistics

First Advisor

Lynn Greenleaf, Ph.D.

Second Advisor

Jeremy Becnel, Ph.D.

Third Advisor

Christopher Ivancic, Ph.D.

Fourth Advisor

Jacob Turner, Ph.D.,


Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to approximate.

The model under consideration in this paper is the Weather Research and Forecast model (WRF). This model takes input from data files as initial conditions, often from other models, and runs a simulation based on its own set of equations and conditions.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.



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