Wildfires are devastating natural disasters that cause massive physical, ecological, and economic damage. In Southern California, wildfires are strongly impacted by Santa Ana wind events. Current research funded by NIST, the National Institute of Standards and Technology, is focused on studying the behavior of winds within the Rancho Bernardo Trails community in San Diego County, which was the victim of the Witch and Guejito wildfires in 2007. The goal of the research project is to understand the effects that Santa Ana winds have upon the spread of wildfires as the fires transition from a wildland environment to an urban environment across what is called the wildland-urban interface. Within the Trails community in Rancho Bernardo and the neighboring San Dieguito River Valley, there exist 18 different locations monitoring wind speed, wind direction, temperature, and humidity using various methods. In conjunction with experimental field data, the project utilizes a CFD model developed by NIST called Fire Dynamics Simulator (FDS) in order to simulate wind flow and fire spread under specified conditions. A statistical analysis was done on experimental data from both a Santa Ana event on February 8, 2016 and typical wind behavior on February 1, 2016. The goal of this analysis was to study how the local terrain within the Rancho Bernardo Trails community and the surrounding area affected wind flow during a Santa Ana event. Correlation between different Trails sites were calculated to quantify this affect, and time graphs and boundary layer profiles were created to visualize the data collected. FDS has three methods by which wind flow can be implemented within the domain. Before fire can be modeled accurately within FDS, it must first be determined which wind flow method is best suited for the purposes of this project. Testing was done within a simplified domain to study how various boundary conditions and imposed synthetic turbulence affect the wind flow using each method. It was determined that the Coriolis Force method is the most promising method to use for complex simulations, but still requires some validation testing.