On the Design of Unmanned Aerial Weather Measurement Systems for Wintry Precipitation Observations

Abstract

Weakly forced winter weather precipitation events within the atmospheric boundary layer can lead to considerable negative economic impacts. Due to their proximity to the ground and varying range of particle sizes, some of these precipitation phenomena are not well captured by current observation systems (e.g., radiosondes, ground and space-based radars, and automated surface observations). In aerial transportation, undetected low-altitude freezing rain and drizzle can produce almost invisible hazards with potentially catastrophic consequences for aircraft within low altitudes (e.g., the terminal area). However, the lack of direct observations of the low-altitude freezing precipitation environment creates a challenge for forecasters, flight crews, dispatchers, and air traffic controllers. This challenge is further exacerbated by the integration of autonomous aircraft (i.e., sUAS and AAM) into the national airspace system, which will necessitate the availability of this currently missing information at higher spatial and temporal resolutions. To address this need, this dissertation endeavors to develop a novel unmanned aerial weather measurement system (WxUAS) to complement the current observation systems and provide insight into the mechanisms that govern low-altitude wintry precipitation. Such insight is achieved through a multi-modal data fusion algorithm that leverages novel WxUAS-base techniques for in-situ measurements in active precipitation and airborne radar measurements to produce an automated present weather inference aimed at detecting and locating freezing and melting layers, cloud and cloud-transition layers, as well as precipitation type and intensity. Validation for these novel techniques is presented through an intercomparison study with NASA instruments.