Preprints
https://doi.org/10.5194/amt-2021-383
https://doi.org/10.5194/amt-2021-383
 
03 Jan 2022
03 Jan 2022
Status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

Testing the efficacy of atmospheric boundary layer height detection algorithms using uncrewed aircraft system data from MOSAiC

Gina Jozef1,2,3, John Cassano1,2,3, Sandro Dahlke4, and Gijs de Boer2,5,6 Gina Jozef et al.
  • 1Dept. of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA
  • 2Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
  • 3National Snow and Ice Data Center, University of Colorado Boulder, Boulder, CO, USA
  • 4Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
  • 5NOAA Physical Sciences Laboratory, Boulder, CO, USA
  • 6Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, CO, USA

Abstract. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed wing uncrewed aircraft system (UAS). Of particular interest is the atmospheric boundary layer (ABL) height, as ABL structure can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to subjectively identify ABL height for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ABL height with the ABL heights identified by various previously published objective methods allows us to determine which objective methods are most successful at accurately identifying ABL height in the central Arctic environment. The objective methods we use are the Liu-Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ABL height determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ABL height, while the Liu-Liang method is least successful.

Gina Jozef et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-383', Anonymous Referee #1, 17 Jan 2022
    • AC1: 'Reply on RC1', Gina Jozef, 17 Mar 2022
  • RC2: 'Comment on amt-2021-383', Anonymous Referee #2, 26 Jan 2022
    • AC2: 'Reply on RC2', Gina Jozef, 17 Mar 2022
  • RC3: 'Comment on amt-2021-383', Anonymous Referee #3, 26 Jan 2022
    • AC3: 'Reply on RC3', Gina Jozef, 17 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-383', Anonymous Referee #1, 17 Jan 2022
    • AC1: 'Reply on RC1', Gina Jozef, 17 Mar 2022
  • RC2: 'Comment on amt-2021-383', Anonymous Referee #2, 26 Jan 2022
    • AC2: 'Reply on RC2', Gina Jozef, 17 Mar 2022
  • RC3: 'Comment on amt-2021-383', Anonymous Referee #3, 26 Jan 2022
    • AC3: 'Reply on RC3', Gina Jozef, 17 Mar 2022

Gina Jozef et al.

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Short summary
During the MOSAiC expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 uncrewed aircraft system. These data were used to identify the best method for atmospheric boundary layer height detection, by comparing visually identified subjective boundary layer height to that identified by several objective automated detection methods. The results show a bulk Richardson number-based approach gives the best estimate of boundary layer height.