Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign

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.

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Wind Estimation in the Lower Atmosphere Using Multirotor Aircraft

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-16-0177.1 ◽

2017 ◽

Vol 34 (5) ◽

pp. 1183-1191 ◽

Cited By ~ 52

Author(s):

Ross T. Palomaki ◽

Nathan T. Rose ◽

Michael van den Bossche ◽

Thomas J. Sherman ◽

Stephan F. J. De Wekker

Keyword(s):

Wind Speed ◽

Sonic Anemometer ◽

Unmanned Aircraft ◽

Lower Atmosphere ◽

Promising Alternative ◽

Atmospheric Structure ◽

Structure And Dynamics ◽

Sonic Anemometers ◽

Vertical Profiling ◽

Good Agreement

AbstractUnmanned aerial vehicles are increasingly used to study atmospheric structure and dynamics. While much emphasis has been on the development of fixed-wing unmanned aircraft for atmospheric investigations, the use of multirotor aircraft is relatively unexplored, especially for capturing atmospheric winds. The purpose of this article is to demonstrate the efficacy of estimating wind speed and direction with 1) a direct approach using a sonic anemometer mounted on top of a hexacopter and 2) an indirect approach using attitude data from a quadcopter. The data are collected by the multirotor aircraft hovering 10 m above ground adjacent to one or more sonic anemometers. Wind speed and direction show good agreement with sonic anemometer measurements in the initial experiments. Typical errors in wind speed and direction are smaller than 0.5 and 30°, respectively. Multirotor aircraft provide a promising alternative to traditional platforms for vertical profiling in the atmospheric boundary layer, especially in conditions where a tethered balloon system is typically deployed.

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Development of a small unmanned aircraft system to derive CO<sub>2</sub> emissions of anthropogenic point sources

10.5194/amt-2020-234 ◽

2020 ◽

Author(s):

Maximilian Reuter ◽

Heinrich Bovensmann ◽

Michael Buchwitz ◽

Jakob Borchardt ◽

Sven Krautwurst ◽

...

Keyword(s):

Wind Speed ◽

Point Sources ◽

Unmanned Aircraft ◽

Horizontal Wind ◽

Observation System ◽

Calibration Model ◽

Unmanned Aircraft System ◽

Airborne Measurements ◽

Wind Measurements ◽

Aircraft System

Abstract. A reduction of the anthropogenic emissions of CO2 (carbon dioxide) is necessary to stop or slow down man-made climate change. To verify mitigation strategies, a global monitoring system such as the envisaged European Copernicus anthropogenic CO2 monitoring mission (CO2M) is required. Those satellite data are going to be complemented and validated with airborne measurements. UAV (unmanned aerial vehicle) based measurements can provide a cost-effective way to contribute to this activities. Here we present the development of a sUAS (small unmanned aircraft system) to quantify the CO2 emissions of a nearby point source from its downwind mass flux without the need for any ancillary data. Specifically, CO2 is measured by a NDIR (non-dispersive infrared) detector and the wind speed and direction is measured with a 2D ultrasonic acoustic resonance anemometer. By means of laboratory measurements and an in-flight validation at the ICOS (Integrated Carbon Observation System) atmospheric station Steinkimmen (STE) near Bremen, Germany, we estimate that the individual CO2 measurements have a precision of 3 ppm and that CO2 enhancements can be determined with an accuracy of 1.3 % or 0.9 ppm, whichever is larger. We introduce an anemometer calibration method to minimize the effect of rotor downwash on the wind measurements. This method derives the fit parameters of a linear calibration model accounting for scaling, rotation, and a potential constant bias. For this purpose it analyzes wind measurements taken while following a suitable flight pattern and assuming stationary wind conditions. From the calibration and validation experiments, we estimate the single measurement precision of the horizontal wind speed to be 0.40 m s−1 and the accuracy to be 0.33 m s−1. By means of two flights downwind of the ExxonMobil natural gas processing facility in Großenkneten about 40 km east of Bremen, Germany, we demonstrate how the measurements of elevated CO2 concentrations can be used to infer mass fluxes of atmospheric CO2 related to the emissions of the facility.

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Development of a small unmanned aircraft system to derive CO<sub>2</sub> emissions of anthropogenic point sources

Atmospheric Measurement Techniques ◽

10.5194/amt-14-153-2021 ◽

2021 ◽

Vol 14 (1) ◽

pp. 153-172

Author(s):

Maximilian Reuter ◽

Heinrich Bovensmann ◽

Michael Buchwitz ◽

Jakob Borchardt ◽

Sven Krautwurst ◽

...

Keyword(s):

Wind Speed ◽

Point Sources ◽

Unmanned Aircraft ◽

Horizontal Wind ◽

Observation System ◽

Calibration Model ◽

Unmanned Aircraft System ◽

Airborne Measurements ◽

Wind Measurements ◽

Aircraft System

Abstract. A reduction of the anthropogenic emissions of CO2 (carbon dioxide) is necessary to stop or slow down man-made climate change. To verify mitigation strategies, a global monitoring system such as the envisaged European Copernicus anthropogenic CO2 monitoring mission (CO2M) is required. Those satellite data are going to be complemented and validated with airborne measurements. Unmanned aerial vehicle (UAV)-based measurements can provide a cost-effective way to contribute to these activities. Here, we present the development of an sUAS (small unmanned aircraft system) to quantify the CO2 emissions of a nearby point source from its downwind mass flux without the need for any ancillary data. Specifically, CO2 is measured by an NDIR (non-dispersive infrared) detector, and the wind speed and direction are measured with a 2-D ultrasonic acoustic resonance anemometer. By means of laboratory measurements and an in-flight validation at the ICOS (Integrated Carbon Observation System) atmospheric station Steinkimmen (STE) near Bremen, Germany, we estimate that the individual CO2 measurements have a precision of 3 ppm and that CO2 enhancements can be determined with an accuracy of 1.3 % or 0.9 ppm, whichever is larger. We introduce an anemometer calibration method to minimize the effect of rotor downwash on the wind measurements. This method derives the fit parameters of a linear calibration model accounting for scaling, rotation, and a potential constant bias. For this purpose, it analyzes wind measurements taken while following a suitable flight pattern and assuming stationary wind conditions. From the calibration and validation experiments, we estimate the single measurement precision of the horizontal wind speed to be 0.40 m s−1 and the accuracy to be 0.33 m s−1. By means of two flights downwind of the ExxonMobil natural gas processing facility in Großenkneten about 40 km west of Bremen, Germany, we demonstrate how the measurements of elevated CO2 concentrations can be used to infer mass fluxes of atmospheric CO2 related to the emissions of the facility.

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