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Abstract
The advent of mobile observation platforms made possible by advances in small Unmanned Aircraft Systems (sUAS) technology has revolutionized the landscape of Observational Meteorology. sUAS are proven to be safe, reliable, economical, and easy-to-deploy atmospheric sensing platforms. Unmanned aircraft can sample on flexible flight trajectories, have increased observation range, and are increasingly equipped with miniaturized high-resolution sensing instruments, making them instrumental for targeted observations of atmospheric turbulence. The principal objectives of the investigations described in this dissertation were twofold. First, to improve the accuracy and reliability of current turbulence sensing capabilities of the University of Colorado DataHawk UAS. We explore the current landscape of observational turbulence and develop novel strategies to advance fixed-wing UAS turbulence measurement capabilities. Second, to obtain insightful turbulence data products to further our understanding of complex, small-scale turbulence processes. Challenges in turbulence data processing, analysis strategies, and interpretation of UAS sensed data are discussed. Turbulence measurements made using DataHawk UAS during the Instabilities, Dynamics, and Energetics accompanying Atmospheric Layering (IDEAL) observational campaign are the basis for all investigations presented in this document.
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