Preprints
https://doi.org/10.5194/amt-2021-335
https://doi.org/10.5194/amt-2021-335
 
07 Dec 2021
07 Dec 2021
Status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

Adaptive Thermal Image Velocimetry of spatial wind movement on landscapes using near target infrared cameras

Benjamin Schumacher1, Marwan Katurji1, Jiawei Zhang1, Peyman Zawar-Reza1, Benjamin Adams2, and Matthias Zeeman3 Benjamin Schumacher et al.
  • 1School of Earth and Environment, University of Canterbury, Christchurch, New Zealand
  • 2Department of Computer Science and Software Engineering, University of Canterbury, Christchurch, New Zealand
  • 3Institute of Meteorology and Climate Research - Atmospheric Environmental Research, Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany

Abstract. Thermal Image Velocimetry (TIV) is a near-target remote sensing technique for estimating two- dimensional near-surface wind velocity based on spatiotemporal displacement of fluctuations in surface brightness temperature captured by an infrared camera. The addition of an automated parameterization and the combination of ensemble TIV results into one output made the method more suitable to changing meteorological conditions and less sensitive to noise stemming from the airborne sensor platform. Three field campaigns were carried out to evaluate the algorithm over turf, dry grass and wheat stubble. The derived velocities were validated with independently acquired observations from fine wire thermocouples and sonic anemometers. It was found that the TIV technique correctly derives atmospheric flow patterns close to the ground. Moreover, the modified method resolves wind speed statistics close to the surface at a higher resolution than the traditional measurement methods. Adaptive Thermal Image Velocimetry (A-TIV) is capable of providing contact-less spatial information about near-surface atmospheric motion and can help to be a useful tool in researching turbulent transport processes close to the ground.

Benjamin Schumacher et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-335', Anonymous Referee #1, 17 Dec 2021
    • AC1: 'Reply on RC1', Benjamin Schumacher, 10 May 2022
    • AC7: 'Reply on RC1', Benjamin Schumacher, 11 May 2022
  • RC2: 'Comment on amt-2021-335', Anonymous Referee #2, 15 Mar 2022
    • AC2: 'Reply on RC2', Benjamin Schumacher, 10 May 2022
    • AC8: 'Reply on RC2', Benjamin Schumacher, 11 May 2022
  • AC6: 'Comment on amt-2021-335', Benjamin Schumacher, 10 May 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-335', Anonymous Referee #1, 17 Dec 2021
    • AC1: 'Reply on RC1', Benjamin Schumacher, 10 May 2022
    • AC7: 'Reply on RC1', Benjamin Schumacher, 11 May 2022
  • RC2: 'Comment on amt-2021-335', Anonymous Referee #2, 15 Mar 2022
    • AC2: 'Reply on RC2', Benjamin Schumacher, 10 May 2022
    • AC8: 'Reply on RC2', Benjamin Schumacher, 11 May 2022
  • AC6: 'Comment on amt-2021-335', Benjamin Schumacher, 10 May 2022

Benjamin Schumacher et al.

Benjamin Schumacher et al.

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Short summary
This investigation presents Adaptive Thermal Image Velocimetry (A-TIV) a newly developed algorithm to spatially measure near-surface atmospheric velocities using an infrared camera mounted on uncrewed aerial vehicles. A validation and accuracy assessment of the retrieved velocity fields show the successful application of the algorithm over short cut grass and turf surfaces in dry conditions. This provides new opportunities for atmospheric scientist to study surface-atmospheric interactions.