Preprints
https://doi.org/10.5194/amt-2020-500
https://doi.org/10.5194/amt-2020-500

  11 May 2021

11 May 2021

Review status: this preprint is currently under review for the journal AMT.

Use of thermal signal for the investigation of near-surface turbulence

Matthias Zeeman Matthias Zeeman
  • Karlsruhe Institute of Technology, Atmospheric Environmental Research Institute of Meteorology and Climate Research, Garmisch-Partenkirchen, Germany

Abstract. Organized motions in the roughness sub-layer were investigated using novel temperature sensing and data science methods. Despite accuracy draw backs, current fibre-optic temperature (DTS) and thermal imaging (TIR) instruments offer frequent, moderately precise and highly localized observations of thermal signal in a domain geometry suitable for micro-meteorological applications near the surface. Horizontal and vertical cross-sections allowed a tomographic investigation of the spanwise and streamwise evolution of organised motion, opening avenues for analysis without assumptions on scale relationships. Variance events on the order of seconds to minutes could be identified, localized, and classified using signal decomposition and machine learning techniques. However, small-scale turbulence patterns at the surface appeared difficult to resolve due to the heterogeneity of the thermal properties of the vegetation canopy, which are not immediately evident with the naked eye. The results highlight a need for physics-aware data sciences techniques that treat scale and shape of temperature structures in combination, rather than as separate features.

Matthias Zeeman

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2020-500', Nikolas Angelou, 14 Jun 2021
    • AC1: 'Reply on RC1', Matthias Zeeman, 28 Jun 2021
    • AC2: 'Reply on RC1 (General Comments)', Matthias Zeeman, 28 Jun 2021
    • AC3: 'Reply on RC1 (Specific Comments)', Matthias Zeeman, 28 Jun 2021
    • AC4: 'Reply on RC1 (Technical Corrections)', Matthias Zeeman, 28 Jun 2021
  • RC2: 'Comment on amt-2020-500', Anonymous Referee #3, 12 Aug 2021
    • AC5: 'Reply on RC2', Matthias Zeeman, 23 Aug 2021

Matthias Zeeman

Matthias Zeeman

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Short summary
Understanding turbulence near the surface is important for many applications. In this work, methods for observing and analysing temperature structures in a near-surface volume were explored. Experiments were conducted to identify modes of organized motion. These help explain interactions between the vegetation and the atmosphere that are not currently well-understood. Techniques used include fibre-optic sensing, thermal infrared imaging, signal decomposition, and machine learning.