scholarly journals Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two Source Energy Balance Model (TSEB) II—Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images

2018 ◽  
Vol 10 (4) ◽  
pp. 558 ◽  
Author(s):  
Ana Andreu ◽  
William Kustas ◽  
Maria Polo ◽  
Arnaud Carrara ◽  
Maria González-Dugo
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Spatial Resolution ◽  
Satellite Images ◽  
Energy Balance Model ◽  
Balance Model ◽  
Oak Savanna ◽  
Energy Fluxes ◽  
Surface Energy Fluxes

scholarly journals Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two-Source Energy Balance Model (TSEB) I

2018 ◽  
Vol 10 (4) ◽  
pp. 567 ◽  
Author(s):  
Ana Andreu ◽  
William Kustas ◽  
Maria Polo ◽  
Arnaud Carrara ◽  
Maria González-Dugo
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Energy Balance Model ◽  
Balance Model ◽  
Oak Savanna ◽  
Energy Fluxes ◽  
Surface Energy Fluxes

scholarly journals Evaluation of a Two-Source Snow–Vegetation Energy Balance Model for Estimating Surface Energy Fluxes in a Rangeland Ecosystem

2014 ◽  
Vol 15 (1) ◽  
pp. 143-158 ◽  
Author(s):  
Cezar Kongoli ◽  
William P. Kustas ◽  
Martha C. Anderson ◽  
John M. Norman ◽  
Joseph G. Alfieri ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Snow Cover ◽  
Sensible Heat Flux ◽  
Energy Balance Model ◽  
Balance Model ◽  
Sensible Heat ◽  
Energy Fluxes ◽  
Surface Energy Fluxes

Abstract The utility of a snow–vegetation energy balance model for estimating surface energy fluxes is evaluated with field measurements at two sites in a rangeland ecosystem in southwestern Idaho during the winter of 2007: one site dominated by aspen vegetation and the other by sagebrush. Model parameterizations are adopted from the two-source energy balance (TSEB) modeling scheme, which estimates fluxes from the vegetation and surface substrate separately using remotely sensed measurements of land surface temperature. Modifications include development of routines to account for surface snowmelt energy flux and snow masking of vegetation. Comparisons between modeled and measured surface energy fluxes of net radiation and turbulent heat showed reasonable agreement when considering measurement uncertainties in snow environments and the simplified algorithm used for the snow surface heat flux, particularly on a daily basis. There was generally better performance over the aspen field site, likely due to more reliable input data of snow depth/snow cover. The model was robust in capturing the evolution of surface energy fluxes during melt periods. The model behavior was also consistent with previous studies that indicate the occurrence of upward sensible heat fluxes during daytime owing to solar heating of vegetation limbs and branches, which often exceeds the downward sensible heat flux driving the snowmelt. However, model simulations over aspen trees showed that the upward sensible heat flux could be reversed for a lower canopy fraction owing to the dominance of downward sensible heat flux over snow. This indicates that reliable vegetation or snow cover fraction inputs to the model are needed for estimating fluxes over snow-covered landscapes.

scholarly journals Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model

2017 ◽  
Vol 21 (3) ◽  
pp. 1339-1358 ◽  
Author(s):  
Jordi Cristóbal ◽  
Anupma Prakash ◽  
Martha C. Anderson ◽  
William P. Kustas ◽  
Eugénie S. Euskirchen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Arctic Tundra ◽  
Soil Heat Flux ◽  
Energy Balance Model ◽  
The Arctic ◽  
Balance Model ◽  
Climate Conditions

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is key to forecasting ecological responses to changing climate conditions in the Arctic. An extensive local evaluation of the Two-Source Energy Balance model (TSEB) – a remote-sensing-based model using thermal infrared retrievals of land surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for Arctic tundra. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean turbulent flux errors generally less than 50 W m−2 at half-hourly time steps, similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. The MODIS leaf area index (LAI) remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data on the local biomass amount. Model refinements found in this work at the local scale build toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.

scholarly journals Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model

2016 ◽  
Author(s):  
Jordi Cristóbal ◽  
Anupma Prakash ◽  
Martha C. Anderson ◽  
William P. Kustas ◽  
Eugénie S. Euskirchen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Arctic Tundra ◽  
Soil Heat Flux ◽  
Energy Balance Model ◽  
The Arctic ◽  
Balance Model ◽  
Climate Conditions

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as one of the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is a key to forecasting ecological responses to changing climate conditions in the Arctic regions. An extensive evaluation of the two-source energy balance model (TSEB) – a remote sensing-based model using thermal infrared retrievals of land–surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for the unique Arctic tundra conditions. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean flux errors around 50 W m−2 at half-hourly timesteps similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. MODIS LAI remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data. This work builds toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.

Surface energy balance model of transpiration from variable canopy cover and evaporation from residue-covered or bare-soil systems

2009 ◽  
Vol 28 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Luis Octavio Lagos ◽  
Derrel L. Martin ◽  
Shashi B. Verma ◽  
Andrew Suyker ◽  
Suat Irmak
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Canopy Cover ◽  
Bare Soil ◽  
Energy Balance Model ◽  
Balance Model ◽  
Soil Systems
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