In recent years, increased attention has turned to studying the atmospheric boundary layer (ABL) as new observing systems have been developed. Traditionally, the ABL has been drastically under-sampled by conventional observing systems (e.g., radiosonde and meteorological towers). Filling this so-called ``ABL data gap" using new, high-resolution observing systems has the potential to assist with the development of next-generation parameterization schemes for scales ranging from large-eddy simulation to climate scales, improve forecaster situational awareness during high-impact weather, and provide detailed information for assimilation into numerical weather prediction. Specifically, commercial availability of ground-based remote sensors and the recent widespread availability of small uncrewed aerial systems (UAS) has opened up a world of opportunity to observe and study the complex processes that occur in the ABL which have previously not been routinely observed.

However, it is important to evaluate the utility of each system by directly comparing them with one another in a variety of environments. In the following studies, thermodynamic and kinematic data from a suite of remote sensors contained in the Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS) and state-of-the-art weather-sensing UAS (WxUAS) are compared to one another. CLAMPS contains an Atmospheric Emitted Radiance Interferometer (AERI) and a microwave radiometer (MWR) for thermodynamic profiling and a scanning Doppler wind lidar (DL) for kinematic profiling. The WxUAS used is the CopterSonde, which has been developed specifically to provide accurate kinematic and thermodynamic measurements. Data from two campaigns, one which took place in the San Luis Valley in Colorado and the other at the Kessler Atmospheric and Ecological Field Station in central Oklahoma, are used for the comparison.

From these intercomparisons, multiple instrument deficiencies are examined. Compared to both the DL and high-resolution radiosondes, the CopterSonde tended to underestimate the wind speed using an empirically derived function that relates the tilt of the UAS to the wind speed. Utilizing the DL retrieved wind profiles, a new function is proposed and validated. Additionally, issues are identified with thermodynamic retrievals performed in locations where appropriate prior information is unavailable. A modified thermodynamic retrieval, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) algorithm, is used to combine multiple observation types to attempt to improve the retrievals. Additionally, data collected from the Verification of the Origins of Rotation in Tornadoes Experiment Southeast (VORTEX-SE) are used to examine sensitivities in TROPoe.

Throughout the analyses, synergies are present between the remote sensing and UAS. These synergies are discussed in the context of next generation profiling networks to fill the ABL data gap and suggestions are made for how a next generation network could function with remote-sensing and WxUAS.