Abstract
Abstract. The absence of sunlight during the winter in the High Arctic results in a strong surface-based atmospheric temperature inversion, especially during clear skies and light surface wind conditions. The inversion suppresses turbulent heat transfer between the ground and the boundary layer. As a result, the difference between the surface air temperature, measured at a height of 2 m, and the ground skin temperature can exceed several degrees Celsius. Such inversions occur very frequently in polar regions, are of interest to understand the mechanisms responsible for surface–atmosphere heat, mass, and momentum exchanges, and are critical for satellite validation studies. In this paper we present the results of operations of two commercial remotely piloted aircraft systems, or drones, at the Polar Environment Atmospheric Research Laboratory, Eureka, Nunavut, Canada, at 80∘ N latitude. The drones are the Matrice 100 and Matrice 210 RTK quadcopters manufactured by DJI and were flown over Eureka during the February–March field campaigns in 2017 and 2020. They were equipped with a temperature measurement system built on a Raspberry Pi single-board computer, three platinum-wire temperature sensors, a Global Navigation Satellite System receiver, and a barometric altimeter. We demonstrate that the drones can be effectively used in the extremely challenging High Arctic conditions to measure vertical temperature profiles up to 75 m above the ground and sea ice surface at ambient temperatures down to −46 ∘C. Our results indicate that the inversion lapse rates within the 0–10 m altitude range above the ground can reach values of ∼ 10–30 ∘C(100m)-1 (∼ 100–300 ∘Ckm-1). The results are in good agreement with the coincident surface air temperatures measured at 2, 6, and 10 m levels at the National Oceanic and Atmospheric Administration flux tower at the Polar Environment Atmospheric Research Laboratory. Above 10 m more gradual inversion with order-of-magnitude smaller lapse rates is recorded by the drone. This inversion lapse rate agrees well with the results obtained from the radiosonde temperature measurements. Above the sea ice drone temperature profiles are found to have an isothermal layer above a surface-based layer of instability, which is attributed to the heat flux through the sea ice. With the drones we were able to evaluate the influence of local topography on the surface-based inversion structure above the ground and to measure extremely cold temperatures of air that can pool in topographic depressions. The unique technical challenges of conducting drone campaigns in the winter High Arctic are highlighted in the paper.
Highlights
Atmospheric temperature is one of the key parameters used to study climate (World Meteorological Organization, 2021)
In this paper we present the results of operations of two commercial remotely piloted aircraft systems, or drones, at the Polar Environment Atmospheric Research Laboratory, Eureka, Nunavut, Canada, at 80◦ N latitude
The purpose of the tests was to evaluate the possibility of automatic flights and demonstrate the capability of the sensors and data collection system to provide reliable data at ambient temperatures below −30 ◦C in the High Arctic
Summary
Atmospheric temperature is one of the key parameters used to study climate (World Meteorological Organization, 2021). Atmospheric temperature measurements are conducted in situ using different types of temperature sensors installed at meteorological observing stations on the ground (Taalas, 2018), marine platforms, i.e. ships and buoys (Cold Regions Research and Engineering Laboratory, 2021; International Arctic Buoy Programme, 2021; National Data Buoy Center, 2021; Multidisciplinary Drifting Observatory for the Study of Arctic Climate, 2021), and airborne platforms, i.e. radiosondes (Luers and Eskridge, 1998; DuBois et al, 2002), dropsondes (Skony et al, 1994; Cohn et al, 2013; Wang et al, 2013; Intrieri et al, 2014), sounding rockets Tikhomirov et al.: Drone measurements of surface-based winter temperature inversions et al, 1961), and aircraft (Antokhin et al, 2012; McBeath, 2014; Nédélec et al, 2015; Berkes et al, 2017). In situ measurements provide high-accuracy and high-temporalresolution temperature datasets and serve as a “golden standard” for validation for other methods
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