Microscale Forecasting for Drone Flight Planning to Develop a Microclimate Model

Interest in microscale weather research is increasing as cities and populations continue to expand and grow. Energy conservation and sustainability are also becoming more predominant research areas since they represent important factors in urban heat islands, small geographical features, and anthropogenic activity. Advancements in Unmanned Aerial Vehicles (UAVs), commonly known as drones, have enabled more precise data collection in areas that were previously considered data sparse. Multiple UAVs can collect data over a very small area quickly and efficiently. The abstract will explain the use of UAVs for microscale weather forecasting to develop a microclimate model. The UAVs and researchers are part of the Autonomous Vehicle Systems (AVS) Laboratory at the University of the Incarnate Word (UIW); a multidisciplinary Lab with research interests in robotics, UAVs, weather modeling, and artificial intelligence.

Measuring weather conditions at the microscale is important for design, engineering, and forecast modeling. The UIW campus presents a unique microclimate due to the mixture of wooded and urban landscapes, with a river and springs flowing through the center. The campus, located in the central portion of the greater San Antonio, Texas metropolitan area, and is on the edge of the Olmos Basin, which also has significant elevation changes that can be seen even across the Incarnate Word campus. Data collection is essential in identifying a microclimate within a large city with varying vegetation and Urban Heat Island.

This study will collect data from three observation sites on campus and add UAV data. These observations will be compared to observations taken at the San Antonio International Airport (KSAT) and two rural sites outside of the San Antonio metropolitan area. Two of the observation sites on campus record data every thirty minutes and are located on opposite ends of the campus with varying elevations. The UAV data is collected 2-3 times per week and will be supplemented by a National Weather Service cooperative observation station at the Headwaters Sanctuary located on the UIW campus. Maps of the area will include station plots and contours to show the difference in weather conditions between the observation sites.

A short-range microclimate numerical model will be developed using the MATLAB Programming Language and then compared to twenty-four-hour NAM forecasts to determine the accuracy of the developed model. Twenty-four-hour forecasts derived from this model will be compared to the data collected for the research for validation. Developing a microscale forecast model will be extremely beneficial for drone flight planning, as accurate forecasts of basic meteorological parameters are needed for safe and effective flying. Microclimate analysis will allow numerical models to give more accurate output of weather parameters on a microscale. With further analysis the microclimate of the UIW campus can be determined.