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

<p>Organised motion of air in the roughness sublayer of the atmosphere was investigated using novel temperature sensing and data science methods. Despite accuracy drawbacks, current fibre-optic distributed temperature sensing (DTS) and thermal imaging (TIR) instruments offer frequent, moderate...

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Autor principal:	M. Zeeman
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Environmental engineering TA170-171 Earthwork. Foundations TA715-787
Acceso en línea:	https://doaj.org/article/643d5d82940e4fd68c67e40f23b131f2
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id	oai:doaj.org-article:643d5d82940e4fd68c67e40f23b131f2
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spelling	oai:doaj.org-article:643d5d82940e4fd68c67e40f23b131f22021-12-01T11:23:15ZUse of thermal signal for the investigation of near-surface turbulence10.5194/amt-14-7475-20211867-13811867-8548https://doaj.org/article/643d5d82940e4fd68c67e40f23b131f22021-12-01T00:00:00Zhttps://amt.copernicus.org/articles/14/7475/2021/amt-14-7475-2021.pdfhttps://doaj.org/toc/1867-1381https://doaj.org/toc/1867-8548<p>Organised motion of air in the roughness sublayer of the atmosphere was investigated using novel temperature sensing and data science methods. Despite accuracy drawbacks, current fibre-optic distributed temperature sensing (DTS) and thermal imaging (TIR) instruments offer frequent, moderately precise and highly localised observations of thermal signal in a domain geometry suitable for micrometeorological applications near the surface. The goal of this study was to combine DTS and TIR for the investigation of temperature and wind field statistics. 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. Events in the temperature signal on the order of seconds to minutes could be identified, localised, 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 visually. The results highlight a need for physics-aware data science techniques that treat scale and shape of temperature structures in combination, rather than as separate features.</p>M. ZeemanCopernicus PublicationsarticleEnvironmental engineeringTA170-171Earthwork. FoundationsTA715-787ENAtmospheric Measurement Techniques, Vol 14, Pp 7475-7493 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Environmental engineering TA170-171 Earthwork. Foundations TA715-787
spellingShingle	Environmental engineering TA170-171 Earthwork. Foundations TA715-787 M. Zeeman Use of thermal signal for the investigation of near-surface turbulence
description	<p>Organised motion of air in the roughness sublayer of the atmosphere was investigated using novel temperature sensing and data science methods. Despite accuracy drawbacks, current fibre-optic distributed temperature sensing (DTS) and thermal imaging (TIR) instruments offer frequent, moderately precise and highly localised observations of thermal signal in a domain geometry suitable for micrometeorological applications near the surface. The goal of this study was to combine DTS and TIR for the investigation of temperature and wind field statistics. 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. Events in the temperature signal on the order of seconds to minutes could be identified, localised, 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 visually. The results highlight a need for physics-aware data science techniques that treat scale and shape of temperature structures in combination, rather than as separate features.</p>
format	article
author	M. Zeeman
author_facet	M. Zeeman
author_sort	M. Zeeman
title	Use of thermal signal for the investigation of near-surface turbulence
title_short	Use of thermal signal for the investigation of near-surface turbulence
title_full	Use of thermal signal for the investigation of near-surface turbulence
title_fullStr	Use of thermal signal for the investigation of near-surface turbulence
title_full_unstemmed	Use of thermal signal for the investigation of near-surface turbulence
title_sort	use of thermal signal for the investigation of near-surface turbulence
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/643d5d82940e4fd68c67e40f23b131f2
work_keys_str_mv	AT mzeeman useofthermalsignalfortheinvestigationofnearsurfaceturbulence
_version_	1718405236964458496

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

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