Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 $\pm 2.6{}^{\circ }$ C and 0.22 $\pm 0.59$ m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS.

The CopterSonde is an unmanned aircraft system (UAS) developed in house by a team of engineers and meteorologists at the University of Oklahoma. The CopterSonde is an ambitious attempt by the Center for Autonomous Sensing and Sampling to address the challenge of filling the observational gap present in the lower atmosphere among the currently used meteorological instruments such as towers and radiosondes. The CopterSonde is a unique and highly flexible platform for in situ atmospheric boundary layer measurements with high spatial and temporal resolution, suitable for meteorological applications and research. Custom autopilot algorithms and hardware features were developed as solutions to problems identified throughout several field experiments carried out since 2017. In these field experiments, the CopterSonde has been proven capable of safely operating at wind speeds up to 22 m s⁻¹, flying at 3050 m above mean sea level, and operating in extreme temperatures: nearly −20 ^∘C in Finland and 40 ^∘C in Oklahoma, United States. Leveraging the open-source ArduPilot autopilot code has allowed for seamless integration of custom functions and protocols for the acquisition, storage, and distribution of atmospheric data alongside the flight control data. This led to the development of features such as the “wind vane mode” algorithm, which commands the CopterSonde to always face into the wind. It also inspired the design of an asymmetric airframe for the CopterSonde, which is shown to provide more suitable locations for weather sensor placement, in addition to allowing for improvements in the overall aerodynamic characteristics of the CopterSonde. Moreover, it has also allowed the team to design and create a modular shell where the sensor package is attached and which can run independently of the CopterSonde's main body. The CopterSonde is on the trend towards becoming a smart UAS tool with a wide possibility of creating new adaptive and optimized atmospheric sampling strategies.

The deployment of small unmanned aircraft systems (UAS) to collect routine in situ vertical profiles of the thermodynamic and kinematic state of the atmosphere in conjunction with other weather observations could significantly improve weather forecasting skill and resolution. High-resolution vertical measurements of pressure, temperature, humidity, wind speed and wind direction are critical to the understanding of atmospheric boundary layer processes integral to air–surface (land, ocean and sea ice) exchanges of energy, momentum, and moisture; how these are affected by climate variability; and how they impact weather forecasts and air quality simulations. We explore the potential value of collecting coordinated atmospheric profiles at fixed surface observing sites at designated times using instrumented UAS. We refer to such a network of autonomous weather UAS designed for atmospheric profiling and capable of operating in most weather conditions as a 3D Mesonet. We outline some of the fundamental and high-impact science questions and sampling needs driving the development of the 3D Mesonet and offer an overview of the general concept of operations. Preliminary measurements from profiling UAS are presented and we discuss how measurements from an operational network could be realized to better characterize the atmospheric boundary layer, improve weather forecasts, and help to identify threats of severe weather.

Bathymetric surveying to gather information about depths and underwater terrain is increasingly important to the sciences of hydrology and geomorphology. Submerged terrain change detection, water level, and reservoir storage monitoring demand extensive bathymetric data. Despite often being scarce or unavailable, this information is fundamental to hydrodynamic modeling for imposing boundary conditions and building computational domains. In this manuscript, a novel, low-cost, rapid, and accurate method is developed to measure submerged topography, as an alternative to conventional approaches that require significant economic investments and human power. The method integrates two types of Unmanned Aerial Systems (UAS) sampling techniques. The first couples a small UAS (sUAS) to an echosounder attached to a miniaturized boat for surveying submerged topography in deeper water within the range of accuracy. The second uses Structure from Motion (SfM) photogrammetry to cover shallower water areas no detected by the echosounder where the bed is visible from the sUAS. The refraction of light passing through air–water interface is considered for improving the bathymetric results. A zonal adaptive sampling algorithm is developed and applied to the echosounder data to densify measurements where the standard deviation of clustered points is high. This method is tested at a small reservoir in the U.S. southern plains. Ground Control Points (GCPs) and checkpoints surveyed with a total station are used for properly georeferencing of the SfM photogrammetry and assessment of the UAS imagery accuracy. An independent validation procedure providing a number of skill and error metrics is conducted using ground-truth data collected with a leveling rod at co-located reservoir points. Assessment of the results shows a strong correlation between the echosounder, SfM measurements and the field observations. The final product is a hybrid bathymetric survey resulting from the merging of SfM photogrammetry and echosoundings within an adaptive sampling framework.

Obtaining thermodynamic measurements using rotary-wing unmanned aircraft systems (rwUAS) requires several considerations for mitigating biases from the aircraft and its environment. In this study, we focus on how the method of temperature sensor integration can impact the quality of its measurements. To minimize non-environmental heat sources and prevent any contamination coming from the rwUAS body, two configurations with different sensor placements are proposed for comparison. The first configuration consists of a custom quadcopter with temperature and humidity sensors placed below the propellers for aspiration. The second configuration incorporates the same quadcopter design with sensors instead shielded inside of an L-duct and aspirated by a ducted fan. Additionally, an autopilot algorithm was developed for these platforms to face them into the wind during flight for kinematic wind estimations. This study will utilize in situ rwUAS observations validated against tower-mounted reference instruments to examine how measurements are influenced both by the different configurations as well as the ambient environment. Results indicate that both methods of integration are valid but the below-propeller configuration is more susceptible to errors from solar radiation and heat from the body of the rwUAS.