Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data

Latent heat flux (LE) and corresponding water loss in non-moisture-limited ecosystems are well correlated to radiation and temperature. By contrast, in savannahs and arid and semi-arid lands LE is mostly driven by available water and the vegetation exerts a strong control over the rate of transpirat...

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Autores principales: Barraza, V., Restrepo-Coupe, N., Huete, A., Grings, F., Beringer, J., Cleverly, J., Eamus, D.
Formato: JOUR
Materias:
Latent heat flux
Microwave indices
North Australian Tropical Transect
Optical indices
OzFlux
Surface conductance
AMSR-E
Aqua (satellite)
arid region
climate change
drought
estimation method
latent heat flux
microwave radiation
MODIS
optical depth
phenology
savanna
semiarid region
shallow soil
soil moisture
spatiotemporal analysis
temperature effect
tropical region
vegetation cover
water availability
water use efficiency
Australia
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01681923_v232_n_p689_Barraza
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
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spelling todo:paper_01681923_v232_n_p689_Barraza2023-10-03T15:06:20Z Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data Barraza, V. Restrepo-Coupe, N. Huete, A. Grings, F. Beringer, J. Cleverly, J. Eamus, D. Latent heat flux Microwave indices North Australian Tropical Transect Optical indices OzFlux Surface conductance AMSR-E Aqua (satellite) arid region climate change drought estimation method latent heat flux microwave radiation MODIS optical depth phenology savanna semiarid region shallow soil soil moisture spatiotemporal analysis temperature effect tropical region vegetation cover water availability water use efficiency Australia Latent heat flux (LE) and corresponding water loss in non-moisture-limited ecosystems are well correlated to radiation and temperature. By contrast, in savannahs and arid and semi-arid lands LE is mostly driven by available water and the vegetation exerts a strong control over the rate of transpiration. Therefore, LE models that use optical vegetation indices (VIs) to represent the vegetation component (transpiration as a function of surface conductance, Gs) generally overestimate water fluxes in water-limited ecosystems. In this study, we evaluated and compared optical and passive microwave index based retrievals of Gs and LE derived using the Penman-Monteith (PM) formulation over the North Australian Tropical Transect (NATT). The methodology was evaluated at six eddy covariance (EC) sites from the OzFlux network. To parameterize the PM equation for retrievals of LE (PM-Gs), a subset of Gs values was derived from meteorological and EC flux observations and regressed against individual and combined satellite indices, from (1) MODIS AQUA: the Normalized Difference Water Index (NDWI) and the Enhanced Vegetation Index (EVI); and from (2) AMSR-E passive microwave: frequency index (FI), polarization index (PI), vegetation optical depth (VOD) and soil moisture (SM) products. Similarly, we combined optical and passive microwave indices (multi-sensor model) to estimate weekly Gs values, and evaluated their spatial and temporal synergies. The multi-sensor approach explained 40–80% of LE variance at some sites, with root mean square errors (RMSE) lower than 20 W/m2 and demonstrated better performance to other satellite-based estimates of LE. The optical indices represented potential Gs associated with the phenological status of the vegetation (e.g. leaf area index, chlorophyll content) at finer spatial resolution. The microwave indices provided information about water availability and moisture stress (e.g. water content in leaves and shallow soil depths, atmospheric demand) at a high temporal resolution, thereby providing a scaling factor for potential Gs. We applied the newly proposed Gs model to estimate LE at regional scale using global meteorological data. Our derivation could be extended to continental scales providing equally robust estimates of LE in arid and semi-arid biomes. A more accurate estimation of Gs and LE across different savannah classes will improve the analysis of water use efficiency under drought conditions, which is of importance to climate change studies of water, carbon and energy cycling. © 2016 Elsevier B.V. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01681923_v232_n_p689_Barraza
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Latent heat flux
Microwave indices
North Australian Tropical Transect
Optical indices
OzFlux
Surface conductance
AMSR-E
Aqua (satellite)
arid region
climate change
drought
estimation method
latent heat flux
microwave radiation
MODIS
optical depth
phenology
savanna
semiarid region
shallow soil
soil moisture
spatiotemporal analysis
temperature effect
tropical region
vegetation cover
water availability
water use efficiency
Australia
spellingShingle Latent heat flux
Microwave indices
North Australian Tropical Transect
Optical indices
OzFlux
Surface conductance
AMSR-E
Aqua (satellite)
arid region
climate change
drought
estimation method
latent heat flux
microwave radiation
MODIS
optical depth
phenology
savanna
semiarid region
shallow soil
soil moisture
spatiotemporal analysis
temperature effect
tropical region
vegetation cover
water availability
water use efficiency
Australia
Barraza, V.
Restrepo-Coupe, N.
Huete, A.
Grings, F.
Beringer, J.
Cleverly, J.
Eamus, D.
Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data
topic_facet Latent heat flux
Microwave indices
North Australian Tropical Transect
Optical indices
OzFlux
Surface conductance
AMSR-E
Aqua (satellite)
arid region
climate change
drought
estimation method
latent heat flux
microwave radiation
MODIS
optical depth
phenology
savanna
semiarid region
shallow soil
soil moisture
spatiotemporal analysis
temperature effect
tropical region
vegetation cover
water availability
water use efficiency
Australia
description Latent heat flux (LE) and corresponding water loss in non-moisture-limited ecosystems are well correlated to radiation and temperature. By contrast, in savannahs and arid and semi-arid lands LE is mostly driven by available water and the vegetation exerts a strong control over the rate of transpiration. Therefore, LE models that use optical vegetation indices (VIs) to represent the vegetation component (transpiration as a function of surface conductance, Gs) generally overestimate water fluxes in water-limited ecosystems. In this study, we evaluated and compared optical and passive microwave index based retrievals of Gs and LE derived using the Penman-Monteith (PM) formulation over the North Australian Tropical Transect (NATT). The methodology was evaluated at six eddy covariance (EC) sites from the OzFlux network. To parameterize the PM equation for retrievals of LE (PM-Gs), a subset of Gs values was derived from meteorological and EC flux observations and regressed against individual and combined satellite indices, from (1) MODIS AQUA: the Normalized Difference Water Index (NDWI) and the Enhanced Vegetation Index (EVI); and from (2) AMSR-E passive microwave: frequency index (FI), polarization index (PI), vegetation optical depth (VOD) and soil moisture (SM) products. Similarly, we combined optical and passive microwave indices (multi-sensor model) to estimate weekly Gs values, and evaluated their spatial and temporal synergies. The multi-sensor approach explained 40–80% of LE variance at some sites, with root mean square errors (RMSE) lower than 20 W/m2 and demonstrated better performance to other satellite-based estimates of LE. The optical indices represented potential Gs associated with the phenological status of the vegetation (e.g. leaf area index, chlorophyll content) at finer spatial resolution. The microwave indices provided information about water availability and moisture stress (e.g. water content in leaves and shallow soil depths, atmospheric demand) at a high temporal resolution, thereby providing a scaling factor for potential Gs. We applied the newly proposed Gs model to estimate LE at regional scale using global meteorological data. Our derivation could be extended to continental scales providing equally robust estimates of LE in arid and semi-arid biomes. A more accurate estimation of Gs and LE across different savannah classes will improve the analysis of water use efficiency under drought conditions, which is of importance to climate change studies of water, carbon and energy cycling. © 2016 Elsevier B.V.
format JOUR
author Barraza, V.
Restrepo-Coupe, N.
Huete, A.
Grings, F.
Beringer, J.
Cleverly, J.
Eamus, D.
author_facet Barraza, V.
Restrepo-Coupe, N.
Huete, A.
Grings, F.
Beringer, J.
Cleverly, J.
Eamus, D.
author_sort Barraza, V.
title Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data
title_short Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data
title_full Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data
title_fullStr Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data
title_full_unstemmed Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data
title_sort estimation of latent heat flux over savannah vegetation across the north australian tropical transect from multiple sensors and global meteorological data
url http://hdl.handle.net/20.500.12110/paper_01681923_v232_n_p689_Barraza
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