Abstract

Abstract. This paper describes the data collected by the University of Nebraska-Lincoln (UNL) as part of the field deployments during the Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) flight campaign in July 2018. The UNL deployed two multirotor unmanned aerial systems (UASs) at multiple sites in the San Luis Valley (Colorado, USA) for data collection to support three science missions: convection initiation, boundary layer transition, and cold air drainage flow. We conducted 172 flights resulting in over 21 h of cumulative flight time. Our novel design for the sensor housing onboard the UAS was employed in these flights to meet the aspiration and shielding requirements of the temperature and humidity sensors and to separate them from the mixed turbulent airflow from the propellers. Data presented in this paper include timestamped temperature and humidity data collected from the sensors, along with the three-dimensional position and velocity of the UAS. Data are quality-controlled and time-synchronized using a zero-order-hold interpolation without additional post-processing. The full dataset is also made available for download at https://doi.org/10.5281/zenodo.4306086 (Islam et al., 2020).

Highlights

  • A team of researchers from the University of NebraskaLincoln (UNL) participated in the Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) flight campaign between 14– 19 July 2018 at San Luis Valley of Colorado, USA

  • The housing’s inlet is pointed outwards from the unmanned aerial system (UAS) to sample just outside of the UAS turbulence in both ascent and descent. This is different from existing methods of placing the sensor under the arm without shielding but aspirated by the propeller (Hemingway et al, 2017), on the body of the UAS without shielding and aspiration (Lee et al, 2018), or on a different part of the UAS with shielding and possible aspiration from propellers (Greene et al, 2018) or shielding the sensor inside the UAS and with active aspiration using a fan while pointing the inlet towards the wind (Greene et al, 2019)

  • Measurement objectives of LAPSE-RATE in which the UNL participated in data collection are calibration flight (CLF), boundary layer transition (BLT), convection initiation (CI), cold air drainage flow (CDF)

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Summary

Introduction

A team of researchers from the University of NebraskaLincoln (UNL) participated in the Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) flight campaign between 14– 19 July 2018 at San Luis Valley of Colorado, USA. The UNL’s contribution to this collaborative data collection effort was 172 atmospheric boundary layer (ABL) profiling flights using two multirotor unmanned aerial system (UAS) platforms. The housing’s inlet is pointed outwards from the UAS to sample just outside of the UAS turbulence in both ascent and descent This is different from existing methods of placing the sensor under the arm without shielding but aspirated by the propeller (Hemingway et al, 2017), on the body of the UAS without shielding and aspiration (Lee et al, 2018), or on a different part of the UAS with shielding and possible aspiration from propellers (Greene et al, 2018) or shielding the sensor inside the UAS and with active aspiration using a fan while pointing the inlet towards the wind (Greene et al, 2019). For the LAPSE-RATE campaign, the UNL deployed two identical UASs with one primary-sensor suite for measurements and a secondary-sensor suite for redundancy and testing These flights were conducted at five locations in San Luis Valley (Colorado, USA) through 14–19 July 2018. We conclude with example profile data and provide details regarding the availability of the dataset

UAS platform
Sensors
Sensor housing
Data acquisition
UAS sensor mounting configuration and payload
UAS platform M600P1
UAS platform M600P2
Flight locations
Flight strategies
Objective
Data processing and quality control
Calibration
Effect of ascent and descent speed
Detection of inversion
Effect of body-relative wind direction and horizontal transect
Examples of collected profiles
Conclusions
Full Text
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