Framework for Numerical Weather Predictions for Smart Military Installations

• Main Authors: Bastian, Hyeyon Y., Hoch, Brendon, Obiako, Ifezue V., Buchanan, Randy K., Richards, John, Rinaudo, Christina
• Format: Conference Proceeding
• Language: English
• Subjects: Atmospheric modeling; Computational modeling; Fort Moore; Military computing; Numerical Weather Predictions; Predictive models; Smart Installations; Soft sensors; Uncertainty; Weather forecasting; Weather Research and Forecasting (WRF)
• ISSN: 2472-9647
• DOI: 10.1109/SysCon61195.2024.10553433

United States (US) military installations throughout the world face a variety of extreme weather conditions. From snow and ice to heat and thunderstorms, severe weather impacts readiness, training, and day-to-day operations all year for all armed forces. Each military installation has a plethora of data sources for decision making purposes; ranging from weather forecast output, school closures in the area, energy usage for buildings and facilities on the installation, road conditions, to traffic patterns. The Engineering Research and Development Center's Smart Installations project seeks to unify these disparate data sources on these installations to provide a common operating picture for the decision-makers in a single platform called the Virtual Toolbox for Installation Mission Effectiveness (VTIME). VTIME incorporates real-time weather data and products and additional installation data into dashboards. While many meteorological forecast data sources exist, like the Global Air-Land Weather Exploitation Model (GALWEM) and the National Weather Service National Digitized Forecast Database (NDFD), the fidelity of these forecasts are much lower than the art of the possible. Small-scale weather modeling reduces uncertainty in weather-based decisions. In this study, a numerical weather prediction (NWP) model known as the Weather Research and Forecasting (WRF) model was utilized at a 1 km horizontal resolution to demonstrate the value of providing higher fidelity forecasts. WRF is an open-source NWP model that is portable and highly customizable. This paper provides the preliminary framework for utilizing the WRF model to generate higher fidelity forecasts for military installations using the US Department of Defense's High-Performance Computing environment (DoD HPC); focusing specifically on the Fort Moore, GA use case.