Computer Science and Engineering, Department of

 

Authors

Lindsay Barbieri, University of VermontFollow
Stephan T. Kral, University of BergenFollow
Sean C. C. Bailey, University of KentuckyFollow
Amy E. Frazier, Arizona State UniversityFollow
Jamey D. Jacob, Oklahoma State UniversityFollow
Joachim Reuder, University of BergenFollow
David Brus, Finnish Meteorological InstituteFollow
Phillip B. Chilson, University of OklahomaFollow
Christopher Crick, Oklahoma State UniversityFollow
Carrick Detweiler, University of Nebraska–LincolnFollow
Abhiram Doddi, University of Colorado, BoulderFollow
Jack Elston, Black Swift TechnologiesFollow
Hosein Foroutan, Virginia TechFollow
Javier Gonzalez-Rocha, Virginia TechFollow
Brian R. Greene, University of OklahomaFollow
Marcelo I. Guzman, University of KentuckyFollow
Adam L. Houston, University of Nebraska—LincolnFollow
Ashraful Islam, University of Nebraska - LincolnFollow
Osku Kemppinen, Kansas State UniversityFollow
Dale Lawrence, University of Colorado, BoulderFollow
Elizabeth A. Pillar-Little, University of OklahomaFollow
Shane D. Ross, Virginia TechFollow
Michael Sama, University of KentuckyFollow
David G. Schmale III, Virginia TechFollow
Travis J. Schuyler, University of KentuckyFollow
Ajay Shankar, University of Nebraska - LincolnFollow
Suzanne W. Smith, University of KentuckyFollow
Sean Waugh, NOAA National Severe Storms LaboratoryFollow
Cory Dixon, University of Colorado, BoulderFollow
Steve Borenstein, University of Colorado, BoulderFollow
Gijs de Boer, University of Colorado, BoulderFollow

ORCID IDs

0000-0001-8495-6402

0000-0002-7966-8585

0000-0002-9807-9858

0000-0003-4552-4935

0000-0002-3376-503X

0000-0002-0802-4838

0000-0002-8766-7873

0000-0002-8049-2644

0000-0002-1635-823X

0000-0002-6369-4009

0000-0001-9159-9028

0000-0003-4185-3571

0000-0003-3638-2664

0000-0003-4376-6818

0000-0002-6730-7766

0000-0002-9005-9510

0000-0002-2826-269X

0000-0002-7490-2432

0000-0003-0444-2300

0000-0001-5523-2376

0000-0002-0971-7759

0000-0002-7003-7429

0000-0002-0380-3269

0000-0003-4652-7150

Document Type

Article

Date of this Version

2019

Citation

Sensors 2019, 19, 2179

Comments

© 2019 by the authors.

Open access

doi:10.3390/s19092179

Abstract

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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