Flying the Gap: WxUAS as a Key Component of Data Fusion for Seamless Vertical Profiles of the Atmosphere

Accurate and continuous vertical profiles of the atmosphere are essential for high-resolution numerical weather prediction models, particularly in resolving the complex dynamics of the planetary boundary layer (PBL). Despite advances in observational technologies, there remains a significant gap in vertical coverage near the Earth's surface. Atmospheric profilers, such as NOAA's wind profilers and NCAR's MicroPulse Differential Absorption Lidar, typically have minimum height coverage extending several hundred meters above ground level, which leaves critical layers underrepresented in operational high-resolution weather models. Additionally, the coarse vertical resolution of many observational systems limits the detailed characterization of the atmosphere's lowest levels.

In this study, we address these challenges by integrating data from a variety of sources to create seamless vertical profiles. We fuse observations from surface weather stations, ground-based remote sensing, airborne platforms, and space-based instruments, alongside in-situ vertical profiles obtained from GreenSight's WeatherHive WxUAS. By analyzing data collected during the New York State Mesonet solar eclipse event, and the ARM SGP site and NCAR Marshall Field Site during WH2yMSIE, we employ two data fusion techniques—statistical methods and machine learning algorithms—to enhance the resolution and continuity of atmospheric profiles.

Our approach aims to fill the observational gaps in the PBL, providing a more detailed and accurate representation of atmospheric conditions. We will validate the fused profiles against data from meteorological towers and radiosondes to ensure accuracy and reliability. The results of this study will highlight the effectiveness of WxUAS in bridging observational gaps and offer recommendations for improving vertical profile data integration in weather models and atmospheric research.