This project will develop and evaluate a novel class of low-cost millimeter-wave (mmWave) radar sensors to generate high-resolution, volumetric observations of atmospheric variables in the boundary layer. Timely, location-specific weather forecasting is mission-critical for Department of War installations, yet validating high-resolution meteorological models requires equally precise ground-truth measurements that are difficult to obtain with conventional instruments, particularly across complex or remote terrain. Current weather radars cost $150,000 to $1 million, consume significant power, and are not well-suited for near-surface observations. By adapting low-cost automotive mmWave radar sensors (originally developed for the automotive industry) to measure precipitation, wind, temperature, and humidity profiles, this work will enable distributed, scalable sensor networks with unprecedented spatial resolution (centimeters to meters) and temporal resolution (10 minutes). Testing at the Jornada Experimental Range in New Mexico will validate sensor performance against the Army Research Laboratory's Meteorological Sensor Array and integrate observations into high-resolution Weather Research and Forecasting models.

The project will develop prototype mmWave radar units using commercial low-cost sensors operating in the 60-64 gigahertz band, selected for their range accuracy (0.1 millimeter), spatial resolution (3.75 centimeters), and integrated signal processing capabilities. Prototypes will be deployed at the Jornada Experimental Range alongside existing meteorological sensors to collect validation datasets. Signal processing algorithms will be refined to generate volumetric precipitation, wind, temperature, and humidity data compatible with NEXRAD Level 2 radar data formats. High-resolution Weather Research and Forecasting models will integrate mmWave observations to evaluate sensor performance, characterize system capabilities and limitations, and improve atmospheric boundary layer process representation. The approach leverages previous research on mmWave applications for snowpack monitoring and extends those methods to atmospheric boundary layer characterization.

This research supports installation operations by providing access to high-resolution atmospheric observations needed for accurate, location-specific weather forecasting. Boundary layer processes in complex terrain are currently under-observed due to the cost and logistical challenges of conventional instrumentation. By demonstrating low-cost, low-power, scalable mmWave radar networks, this capability will enhance atmospheric model accuracy in areas with limited instrumentation, supporting mission planning, land management, resilience planning, and on-the-ground readiness decisions. The distributed sensor approach is particularly valuable for installations in complex terrain or remote locations where conventional weather radars are impractical. Results will provide installation managers with actionable information for improved decision-making on training operations, equipment performance, and natural resource management strategies dependent on atmospheric conditions. (Anticipated Project Completion - 2026)