Unmanned Aerial Systems for Investigating the Polar Atmospheric Boundary Layer—Technical Challenges and Examples of Applications

Abstract

Unmanned aerial systems (UAS) fill a gap in high-resolution observations of meteorological parameters on small scales in the atmospheric boundary layer (ABL). Especially in the remote polar areas, there is a strong need for such detailed observations with different research foci. In this study, three systems are presented which have been adapted to the particular needs for operating in harsh polar environments: The fixed-wing aircraft M 2 AV with a mass of 6 kg, the quadrocopter ALICE with a mass of 19 kg, and the fixed-wing aircraft ALADINA with a mass of almost 25 kg. For all three systems, their particular modifications for polar operations are documented, in particular the insulation and heating requirements for low temperatures. Each system has completed meteorological observations under challenging conditions, including take-off and landing on the ice surface, low temperatures (down to −28 ∘ C), icing, and, for the quadrocopter, under the impact of the rotor downwash. The influence on the measured parameters is addressed here in the form of numerical simulations and spectral data analysis. Furthermore, results from several case studies are discussed: With the M 2 AV, low-level flights above leads in Antarctic sea ice were performed to study the impact of areas of open water within ice surfaces on the ABL, and a comparison with simulations was performed. ALICE was used to study the small-scale structure and short-term variability of the ABL during a cruise of RV Polarstern to the 79 ∘ N glacier in Greenland. With ALADINA, aerosol measurements of different size classes were performed in Ny-Ålesund, Svalbard, in highly complex terrain. In particular, very small, freshly formed particles are difficult to monitor and require the active control of temperature inside the instruments. The main aim of the article is to demonstrate the potential of UAS for ABL studies in polar environments, and to provide practical advice for future research activities with similar systems.

Weather constraints on global drone flyability

“…Precipitation and condensation not only affect airworthiness, they can also affect other components and reduce the effectiveness of application-specific drone operations where optical sensors and cameras used for navigation, sense and avoid, and imaging are compromised by the accumulation of water or ice 10 , 14 . Ingress protection is effective in limiting water penetration based on international standards, but it does not guarantee that crashes will be prevented 25 or protect against icing caused by freezing drizzle or supercooled droplets, which also affects airworthiness and causes drone crashes 26 , 27 . Icing conditions are not included in our analysis or mentioned in most drone manuals but will further reduce flyability for CDs and WRDs at higher latitudes where favourable icing conditions occur more frequently 28 , 29 .…”

An Exploratory Investigation of UAS Regulations in Europe and the Impact on Effective Use and Economic Potential

“…As an illustrative example, the procedure required to acquire the flight permission for a particular system, which has been operated since 2013, is provided. The UAS "ALAD-INA" [4], with a weight of 24.9 kg and a wingspan of 3.6 m, operated by the Institute of Flight Guidance of TU Braunschweig, is applied for atmospheric research, thus for altitudes up to 1000 m. The UAS has been operated on during different years in Germany [5][6][7], in Benin [8,9] and in Svalbard [10,11].…”

Drone Measurements of Surface-Based Winter Temperature Inversions in the High Arctic at Eureka

“…Although our sensors and data collection system allowed measurements at low temperatures, the response time of our RTDs did affect the temperature readings. The use of fine wire type RTDs would be beneficial since they have faster response (Wildmann et al, 2013), however their readings could suffer from temperature fluctuations due to turbulent flows caused by spinning propellers and would require additional filtering of raw data (Greene et al, 2018;Lampert et al, 2020a). Furthermore, we found that special care has to be taken to the temperature sensor mounting since the mechanical vibrations induced in the drone's air-frame during the flight tends to break the leads of our RTD elements.…”