The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models
Aerodynamic resistance (hereafter ra) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of ra plays a pivotal role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to...
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| Veröffentlicht in: | Remote sensing of environment 2021-10, Vol.264, p.112602, Article 112602 |
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| creator | Trebs, Ivonne Mallick, Kaniska Bhattarai, Nishan Sulis, Mauro Cleverly, Jamie Woodgate, William Silberstein, Richard Hinko-Najera, Nina Beringer, Jason Meyer, Wayne S. Su, Zhongbo Boulet, Gilles |
| description | Aerodynamic resistance (hereafter ra) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of ra plays a pivotal 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. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE, the 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 against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019.
Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in ra retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low ra (high wind speeds) and caused a 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 LST uncertainties 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 the mesic forest ecosystems indicated minor dependency on ra for modelling LE (VIP |
| doi_str_mv | 10.1016/j.rse.2021.112602 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_04615813v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0034425721003229</els_id><sourcerecordid>2580074337</sourcerecordid><originalsourceid>FETCH-LOGICAL-c450t-3f22d3e2a71aab0f0ea130532b476c33c65dc13a6291418f4d7b8b809bb14733</originalsourceid><addsrcrecordid>eNp9kEFr3DAQhUVoIdu0PyA3QU49eDsjyZaXnkJom8JCL3ssiLE87mqxra3kLOTfV4tLjz0NPN57zPuEuEfYImDz6bRNmbcKFG4RVQPqRmywtbsKLJg3YgOgTWVUbW_Fu5xPAFi3Fjfi5-HIMsWRZRwkcYr960xT8DJxDnmh2bMMs1yOnCYaizrFhWXmOYf5V9VR5l7yhc5xSTTnc0i0hDjLKfY85vfi7UBj5g9_7504fP1yeHqu9j--fX963Ffe1LBUelCq16zIIlEHAzChhlqrztjGa-2buveoqVE7NNgOprdd27Ww6zo0Vus78XGtPdLozilMlF5dpOCeH_fuqoFpylzUFyzeh9V7TvH3C-fFneJLmst3TtUtgDVa2-LC1eVTzDnx8K8WwV15u5MrvN2Vt1t5l8znNVOG8yVwctkHLvz6kNgvro_hP-k_EHCHxw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2580074337</pqid></control><display><type>article</type><title>The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models</title><source>Access via ScienceDirect (Elsevier)</source><creator>Trebs, Ivonne ; Mallick, Kaniska ; Bhattarai, Nishan ; Sulis, Mauro ; Cleverly, Jamie ; Woodgate, William ; Silberstein, Richard ; Hinko-Najera, Nina ; Beringer, Jason ; Meyer, Wayne S. ; Su, Zhongbo ; Boulet, Gilles</creator><creatorcontrib>Trebs, Ivonne ; Mallick, Kaniska ; Bhattarai, Nishan ; Sulis, Mauro ; Cleverly, Jamie ; Woodgate, William ; Silberstein, Richard ; Hinko-Najera, Nina ; Beringer, Jason ; Meyer, Wayne S. ; Su, Zhongbo ; Boulet, Gilles</creatorcontrib><description>Aerodynamic resistance (hereafter ra) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of ra plays a pivotal 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. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE, the 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 against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019.
Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in ra retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low ra (high wind speeds) and caused a 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 LST uncertainties 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 the 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 the dominance of mechanically generated turbulence, thereby diminishing the importance of buoyancy production for the determination of ra.
•Modelled latent heat flux is uncertain under drought due to aerodynamic resistance.•Overestimation of aerodynamic resistance at water-limited sites for low wind speed.•Stability links aerodynamic resistance with surface temperature and sensible heat.•Novel formulations for aerodynamic resistance are needed to model latent heat flux.</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/j.rse.2021.112602</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>Aerodynamic resistance ; Aerodynamics ; Aridity ; Atmospheric models ; Atmospheric stability ; Ecosystems ; Eddy covariance ; Energy balance ; Energy limitation ; Enthalpy ; Environmental Sciences ; Evapotranspiration ; Evapotranspiration estimates ; Evapotranspiration models ; Fluctuations ; Forest ecosystems ; Grasslands ; Heat flux ; Heat transfer ; Land surface temperature ; Latent heat ; Latent heat flux ; Leaf area ; Leaf area index ; Least squares method ; Modelling ; MODIS ; Remote sensing ; Roughness length ; Sensible heat ; Sensible heat flux ; Surface energy ; Surface energy balance ; Surface energy balance model ; Surface properties ; Surface stability ; Surface temperature ; Terrestrial ecosystems ; Thermal remote sensing ; Thermal resistance ; Uncertainty ; Wind speed ; Woodlands</subject><ispartof>Remote sensing of environment, 2021-10, Vol.264, p.112602, Article 112602</ispartof><rights>2021 The Authors</rights><rights>Copyright Elsevier BV Oct 2021</rights><rights>Attribution - NonCommercial - NoDerivatives</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c450t-3f22d3e2a71aab0f0ea130532b476c33c65dc13a6291418f4d7b8b809bb14733</citedby><cites>FETCH-LOGICAL-c450t-3f22d3e2a71aab0f0ea130532b476c33c65dc13a6291418f4d7b8b809bb14733</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.rse.2021.112602$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://hal.science/hal-04615813$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Trebs, Ivonne</creatorcontrib><creatorcontrib>Mallick, Kaniska</creatorcontrib><creatorcontrib>Bhattarai, Nishan</creatorcontrib><creatorcontrib>Sulis, Mauro</creatorcontrib><creatorcontrib>Cleverly, Jamie</creatorcontrib><creatorcontrib>Woodgate, William</creatorcontrib><creatorcontrib>Silberstein, Richard</creatorcontrib><creatorcontrib>Hinko-Najera, Nina</creatorcontrib><creatorcontrib>Beringer, Jason</creatorcontrib><creatorcontrib>Meyer, Wayne S.</creatorcontrib><creatorcontrib>Su, Zhongbo</creatorcontrib><creatorcontrib>Boulet, Gilles</creatorcontrib><title>The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models</title><title>Remote sensing of environment</title><description>Aerodynamic resistance (hereafter ra) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of ra plays a pivotal 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. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE, the 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 against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019.
Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in ra retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low ra (high wind speeds) and caused a 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 LST uncertainties 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 the 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 the dominance of mechanically generated turbulence, thereby diminishing the importance of buoyancy production for the determination of ra.
•Modelled latent heat flux is uncertain under drought due to aerodynamic resistance.•Overestimation of aerodynamic resistance at water-limited sites for low wind speed.•Stability links aerodynamic resistance with surface temperature and sensible heat.•Novel formulations for aerodynamic resistance are needed to model latent heat flux.</description><subject>Aerodynamic resistance</subject><subject>Aerodynamics</subject><subject>Aridity</subject><subject>Atmospheric models</subject><subject>Atmospheric stability</subject><subject>Ecosystems</subject><subject>Eddy covariance</subject><subject>Energy balance</subject><subject>Energy limitation</subject><subject>Enthalpy</subject><subject>Environmental Sciences</subject><subject>Evapotranspiration</subject><subject>Evapotranspiration estimates</subject><subject>Evapotranspiration models</subject><subject>Fluctuations</subject><subject>Forest ecosystems</subject><subject>Grasslands</subject><subject>Heat flux</subject><subject>Heat transfer</subject><subject>Land surface temperature</subject><subject>Latent heat</subject><subject>Latent heat flux</subject><subject>Leaf area</subject><subject>Leaf area index</subject><subject>Least squares method</subject><subject>Modelling</subject><subject>MODIS</subject><subject>Remote sensing</subject><subject>Roughness length</subject><subject>Sensible heat</subject><subject>Sensible heat flux</subject><subject>Surface energy</subject><subject>Surface energy balance</subject><subject>Surface energy balance model</subject><subject>Surface properties</subject><subject>Surface stability</subject><subject>Surface temperature</subject><subject>Terrestrial ecosystems</subject><subject>Thermal remote sensing</subject><subject>Thermal resistance</subject><subject>Uncertainty</subject><subject>Wind speed</subject><subject>Woodlands</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kEFr3DAQhUVoIdu0PyA3QU49eDsjyZaXnkJom8JCL3ssiLE87mqxra3kLOTfV4tLjz0NPN57zPuEuEfYImDz6bRNmbcKFG4RVQPqRmywtbsKLJg3YgOgTWVUbW_Fu5xPAFi3Fjfi5-HIMsWRZRwkcYr960xT8DJxDnmh2bMMs1yOnCYaizrFhWXmOYf5V9VR5l7yhc5xSTTnc0i0hDjLKfY85vfi7UBj5g9_7504fP1yeHqu9j--fX963Ffe1LBUelCq16zIIlEHAzChhlqrztjGa-2buveoqVE7NNgOprdd27Ww6zo0Vus78XGtPdLozilMlF5dpOCeH_fuqoFpylzUFyzeh9V7TvH3C-fFneJLmst3TtUtgDVa2-LC1eVTzDnx8K8WwV15u5MrvN2Vt1t5l8znNVOG8yVwctkHLvz6kNgvro_hP-k_EHCHxw</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Trebs, Ivonne</creator><creator>Mallick, Kaniska</creator><creator>Bhattarai, Nishan</creator><creator>Sulis, Mauro</creator><creator>Cleverly, Jamie</creator><creator>Woodgate, William</creator><creator>Silberstein, Richard</creator><creator>Hinko-Najera, Nina</creator><creator>Beringer, Jason</creator><creator>Meyer, Wayne S.</creator><creator>Su, Zhongbo</creator><creator>Boulet, Gilles</creator><general>Elsevier Inc</general><general>Elsevier BV</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TG</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KL.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>1XC</scope><scope>VOOES</scope></search><sort><creationdate>202110</creationdate><title>The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models</title><author>Trebs, Ivonne ; Mallick, Kaniska ; Bhattarai, Nishan ; Sulis, Mauro ; Cleverly, Jamie ; Woodgate, William ; Silberstein, Richard ; Hinko-Najera, Nina ; Beringer, Jason ; Meyer, Wayne S. ; Su, Zhongbo ; Boulet, Gilles</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c450t-3f22d3e2a71aab0f0ea130532b476c33c65dc13a6291418f4d7b8b809bb14733</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Aerodynamic resistance</topic><topic>Aerodynamics</topic><topic>Aridity</topic><topic>Atmospheric models</topic><topic>Atmospheric stability</topic><topic>Ecosystems</topic><topic>Eddy covariance</topic><topic>Energy balance</topic><topic>Energy limitation</topic><topic>Enthalpy</topic><topic>Environmental Sciences</topic><topic>Evapotranspiration</topic><topic>Evapotranspiration estimates</topic><topic>Evapotranspiration models</topic><topic>Fluctuations</topic><topic>Forest ecosystems</topic><topic>Grasslands</topic><topic>Heat flux</topic><topic>Heat transfer</topic><topic>Land surface temperature</topic><topic>Latent heat</topic><topic>Latent heat flux</topic><topic>Leaf area</topic><topic>Leaf area index</topic><topic>Least squares method</topic><topic>Modelling</topic><topic>MODIS</topic><topic>Remote sensing</topic><topic>Roughness length</topic><topic>Sensible heat</topic><topic>Sensible heat flux</topic><topic>Surface energy</topic><topic>Surface energy balance</topic><topic>Surface energy balance model</topic><topic>Surface properties</topic><topic>Surface stability</topic><topic>Surface temperature</topic><topic>Terrestrial ecosystems</topic><topic>Thermal remote sensing</topic><topic>Thermal resistance</topic><topic>Uncertainty</topic><topic>Wind speed</topic><topic>Woodlands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Trebs, Ivonne</creatorcontrib><creatorcontrib>Mallick, Kaniska</creatorcontrib><creatorcontrib>Bhattarai, Nishan</creatorcontrib><creatorcontrib>Sulis, Mauro</creatorcontrib><creatorcontrib>Cleverly, Jamie</creatorcontrib><creatorcontrib>Woodgate, William</creatorcontrib><creatorcontrib>Silberstein, Richard</creatorcontrib><creatorcontrib>Hinko-Najera, Nina</creatorcontrib><creatorcontrib>Beringer, Jason</creatorcontrib><creatorcontrib>Meyer, Wayne S.</creatorcontrib><creatorcontrib>Su, Zhongbo</creatorcontrib><creatorcontrib>Boulet, Gilles</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology 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Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Trebs, Ivonne</au><au>Mallick, Kaniska</au><au>Bhattarai, Nishan</au><au>Sulis, Mauro</au><au>Cleverly, Jamie</au><au>Woodgate, William</au><au>Silberstein, Richard</au><au>Hinko-Najera, Nina</au><au>Beringer, Jason</au><au>Meyer, Wayne S.</au><au>Su, Zhongbo</au><au>Boulet, Gilles</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models</atitle><jtitle>Remote sensing of environment</jtitle><date>2021-10</date><risdate>2021</risdate><volume>264</volume><spage>112602</spage><pages>112602-</pages><artnum>112602</artnum><issn>0034-4257</issn><eissn>1879-0704</eissn><abstract>Aerodynamic resistance (hereafter ra) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of ra plays a pivotal 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. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE, the 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 against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019.
Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in ra retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low ra (high wind speeds) and caused a 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 LST uncertainties 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 the 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 the dominance of mechanically generated turbulence, thereby diminishing the importance of buoyancy production for the determination of ra.
•Modelled latent heat flux is uncertain under drought due to aerodynamic resistance.•Overestimation of aerodynamic resistance at water-limited sites for low wind speed.•Stability links aerodynamic resistance with surface temperature and sensible heat.•Novel formulations for aerodynamic resistance are needed to model latent heat flux.</abstract><cop>New York</cop><pub>Elsevier Inc</pub><doi>10.1016/j.rse.2021.112602</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Aerodynamic resistance Aerodynamics Aridity Atmospheric models Atmospheric stability Ecosystems Eddy covariance Energy balance Energy limitation Enthalpy Environmental Sciences Evapotranspiration Evapotranspiration estimates Evapotranspiration models Fluctuations Forest ecosystems Grasslands Heat flux Heat transfer Land surface temperature Latent heat Latent heat flux Leaf area Leaf area index Least squares method Modelling MODIS Remote sensing Roughness length Sensible heat Sensible heat flux Surface energy Surface energy balance Surface energy balance model Surface properties Surface stability Surface temperature Terrestrial ecosystems Thermal remote sensing Thermal resistance Uncertainty Wind speed Woodlands |
| title | The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models |
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