The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

Trebs, I; Mallick, K; Bhattarai, N; Sulis, M; Cleverly, J; Woodgate, W; Silberstein, R; Hinko-Najera, N; Beringer, J; Su, Z; Boulet, G

The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

Trebs, I Mallick, K Bhattarai, N Sulis, M Cleverly, J

Woodgate, W Silberstein, R Hinko-Najera, N Beringer, J Su, Z Boulet, G

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Publisher:: Elsevier
Publication Type:: Other
Citation:: Remote Sensing of Environment: an interdisciplinary journal, 2021, 264, pp. 1-29
Issue Date:: 2021-08-14

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Field	Value	Language
dc.contributor.author	Trebs, I
dc.contributor.author	Mallick, K
dc.contributor.author	Bhattarai, N
dc.contributor.author	Sulis, M
dc.contributor.author	Cleverly, J https://orcid.org/0000-0002-2731-7150
dc.contributor.author	Woodgate, W
dc.contributor.author	Silberstein, R
dc.contributor.author	Hinko-Najera, N
dc.contributor.author	Beringer, J
dc.contributor.author	Su, Z
dc.contributor.author	Boulet, G
dc.date.accessioned	2022-02-14T03:22:30Z
dc.date.available	2022-02-14T03:22:30Z
dc.date.issued	2021-08-14
dc.identifier.citation	Remote Sensing of Environment: an interdisciplinary journal, 2021, 264, pp. 1-29
dc.identifier.issn	0034-4257
dc.identifier.uri	http://hdl.handle.net/10453/154488
dc.description.abstract	<jats:p>&lt;p&gt;&amp;#8216;Aerodynamic resistance&amp;#8217; (hereafter r&lt;sub&gt;a&lt;/sub&gt;) is a preeminent variable in the modelling of evapotranspiration (ET), and its accurate quantification plays a critical role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links r&lt;sub&gt;a&lt;/sub&gt; with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates.&lt;/p&gt;&lt;p&gt;The present study investigates the influence of r&lt;sub&gt;a&lt;/sub&gt; and its relation to LST uncertainties on the performance of three structurally different SEB models by combining nine OzFlux eddy covariance datasets from 2011 to 2019 from sites of different aridity in Australia with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the latent heat flux (LE, energy equivalent of ET in W/m&lt;sup&gt;2&lt;/sup&gt;) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST, LAI, and in-situ meteorological datasets were evaluated using observed flux data across water-limited (semi-arid and arid) and radiation-limited (mesic) ecosystems.&lt;/p&gt;&lt;p&gt;Our results revealed that the three models tend to overestimate instantaneous LE in the water-limited shrubland, woodland and grassland ecosystems by up to 60% on average, which was caused by an underestimation of the sensible heat flux (H). LE overestimation was associated with discrepancies in r&lt;sub&gt;a&lt;/sub&gt; retrievals under conditions of high atmospheric instability, during which errors in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive bias in LST coincides with low r&lt;sub&gt;a&lt;/sub&gt; and causes slight underestimation of LE at the water-limited sites. The impact of r&lt;sub&gt;a&lt;/sub&gt; on the LE residual error was found to be of the same magnitude as the influence of errors in LST in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for mesic forest ecosystems indicated minor dependency on r&lt;sub&gt;a&lt;/sub&gt; for modelling LE (VIP&lt;0.4), which was due to a higher roughness length and lower LST resulting in dominance of mechanically generated turbulence, thereby diminishing the importance of atmospheric stability in the determination of r&lt;sub&gt;a&lt;/sub&gt;.&lt;/p&gt;</jats:p>
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Remote Sensing of Environment: an interdisciplinary journal
dc.relation.isbasedon	10.5194/egusphere-egu21-2186
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0406 Physical Geography and Environmental Geoscience, 0909 Geomatic Engineering
dc.subject.classification	Geological & Geomatics Engineering
dc.title	The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models
dc.type	Other
utslib.citation.volume	264
utslib.for	0406 Physical Geography and Environmental Geoscience
utslib.for	0909 Geomatic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2022-02-14T03:20:24Z
pubs.confidential	false
pubs.volume	264

Abstract:

&#8216;Aerodynamic resistance&#8217; (hereafter ra) is a preeminent variable in the modelling of evapotranspiration (ET), and its accurate quantification plays a critical role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links ra with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates.The present study investigates the influence of ra and its relation to LST uncertainties on the performance of three structurally different SEB models by combining nine OzFlux eddy covariance datasets from 2011 to 2019 from sites of different aridity in Australia with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the latent heat flux (LE, energy equivalent of ET in W/m2) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST, LAI, and in-situ meteorological datasets were evaluated using observed flux data across water-limited (semi-arid and arid) and radiation-limited (mesic) ecosystems.Our results revealed that the three models tend to overestimate instantaneous LE in the water-limited shrubland, woodland and grassland ecosystems by up to 60% on average, which was caused by an underestimation of the sensible heat flux (H). LE overestimation was associated with discrepancies in ra retrievals under conditions of high atmospheric instability, during which errors in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive bias in LST coincides with low ra and causes slight underestimation of LE at the water-limited sites. The impact of ra on the LE residual error was found to be of the same magnitude as the influence of errors in LST in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for mesic forest ecosystems indicated minor dependency on ra for modelling LE (VIP<0.4), which was due to a higher roughness length and lower LST resulting in dominance of mechanically generated turbulence, thereby diminishing the importance of atmospheric stability in the determination of ra.

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