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Abstract In the marine boundary layer, the exchange of momentum, heat, and moisture occurs between the atmosphere and ocean. Since it is too dangerous for a crewed aircraft to fly close to the ocean surface to directly obtain these measurements, a sUAS (small Uncrewed Aircraft System) is one of the only viable options. On 24 March 2023 a Black Swift Technologies S0 sUAS was deployed from the NOAA P‐3 on a calm clear day off the west coast of Florida. For 23 min at the end of the mission, the sUAS flew 8 straight line legs with an average length of 2.15 km, at roughly 10 m above the ocean surface, with wind speeds between 3.0 and 4.5 m s⁻¹. For the first time over the open ocean using a sUAS, the 4‐Hz wind and thermodynamic data was used to calculate surface momentum flux, sensible heat flux, and latent flux using both direct covariance methods and the bulk aerodynamic formulas. Since all the flux quantities can be found using both direct and indirect methods, we are able to calculate the exchange coefficients of momentum flux (C_D), latent heat flux (C_E), and sensible heat flux (C_H) with results that are generally in good agreement with previous studies over the same wind speed range. This study demonstrates the ability of sUAS to measure air‐sea interactions. Future intention is to use sUAS to obtain similar measurements in high wind events such as hurricanes which could better help understand hurricane intensification and improve model physics. 

Abstract. Above polar ice sheets, atmospheric water vapor exchangeoccurs across the planetary boundary layer (PBL) and is an importantmechanism in a number of processes that affect the surface mass balance ofthe ice sheets. Yet, this exchange is not well understood and hassubstantial implications for modeling and remote sensing of the polarhydrologic cycle. Efforts to characterize the exchange face substantiallogistical challenges including the remoteness of ice sheet field camps,extreme weather conditions, low humidity and temperature that limit theeffectiveness of instruments, and dangers associated with flying mannedaircraft at low altitudes. Here, we present an unmanned aerial vehicle (UAV)sampling platform for operation in extreme polar environments that iscapable of sampling atmospheric water vapor for subsequent measurement ofwater isotopes. This system was deployed to the East Greenland Ice-coreProject (EastGRIP) camp in northeast Greenland during summer 2019. Foursampling flight missions were completed. With a suite of atmosphericmeasurements aboard the UAV (temperature, humidity, pressure, GPS) wedetermine the height of the PBL using online algorithms, allowing forstrategic decision-making by the pilot to sample water isotopes above andbelow the PBL. Water isotope data were measured by a Picarro L2130-iinstrument using flasks of atmospheric air collected within the nose cone ofthe UAV. The internal repeatability for δD and δ18O was2.8 ‰ and 0.45 ‰, respectively,which we also compared to independent EastGRIP tower-isotope data. Based onthese results, we demonstrate the efficacy of this new UAV-isotope platformand present improvements to be utilized in future polar field campaigns. Thesystem is also designed to be readily adaptable to other fields of study,such as measurement of carbon cycle gases or remote sensing of groundconditions. 

ABSTRACT Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research Using Remotely-Piloted Aircraft (ISARRA) has been developed and has convened annual meetings and “flight weeks.” The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE), involved a 1-week deployment to Colorado’s San Luis Valley. Between 14 and 20 July 2018 over 100 students, scientists, engineers, pilots, and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated “Community Day” which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1,300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques, and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science. 

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 ± 2.6 ∘ C and 0.22 ± 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.