Influences of Instability on Random Errors in Uncrewed Aircraft System Measurements in the Convective Boundary Layer

Uncrewed aircraft systems (UAS) have rapidly expanded as a tool for the atmospheric research community, specifically as a platform for in-situ measurements of the atmospheric boundary layer (ABL). Within this growing sector, it is important to consider how these measurements represent the surrounding ABL, which is in turn dependent on factors such as ABL stability and height above the ground. Specifically, within the convective boundary layer (CBL), turbulent eddies are larger than those within the stable boundary layer due to buoyant mixing. The larger these motions become, the more the averaging time for observations must increase to properly capture their impacts on their surroundings, which ensures a more accurate method for data collection.

To understand how instability impacts the ability of UAS observations to characterize the CBL, a random error analysis was applied to a series of seven large eddy simulations spanning weakly to highly convective conditions. For each simulation, we used the relaxed filtering method (RFM) to estimate relative random errors for wind speed, wind direction, potential temperature, and specific humidity. Using these results, random errors for emulated UAS profiles were estimated to understand the representativeness of these measurements and it was discovered that in general, errors in all of the considered variables increase with increasing instability. Additionally, errors tend to peak near the surface for wind speed and direction and within the entrainment zone atop the CBL for scalars. The research study will conclude with a discussion on the optimal vertical ascent rates and averaging times within the CBL in order to lessen the impacts of random errors.