
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Bridging Thermal Infrared Sensing and Physically‐Based Evapotranspiration Modeling: From Theoretical Implementation to Validation Across an Aridity Gradient in Australian Ecosystems

doi: 10.1029/2017wr021357
handle: 10138/298954
Bridging Thermal Infrared Sensing and Physically‐Based Evapotranspiration Modeling: From Theoretical Implementation to Validation Across an Aridity Gradient in Australian Ecosystems
AbstractThermal infrared sensing of evapotranspiration (E) through surface energy balance (SEB) models is challenging due to uncertainties in determining the aerodynamic conductance (gA) and due to inequalities between radiometric (TR) and aerodynamic temperatures (T0). We evaluated a novel analytical model, the Surface Temperature Initiated Closure (STIC1.2), that physically integrates TR observations into a combined Penman‐Monteith Shuttleworth‐Wallace (PM‐SW) framework for directly estimating E, and overcoming the uncertainties associated with T0 and gA determination. An evaluation of STIC1.2 against high temporal frequency SEB flux measurements across an aridity gradient in Australia revealed a systematic error of 10–52% in E from mesic to arid ecosystem, and low systematic error in sensible heat fluxes (H) (12–25%) in all ecosystems. Uncertainty in TR versus moisture availability relationship, stationarity assumption in surface emissivity, and SEB closure corrections in E were predominantly responsible for systematic E errors in arid and semi‐arid ecosystems. A discrete correlation (r) of the model errors with observed soil moisture variance (r = 0.33–0.43), evaporative index (r = 0.77–0.90), and climatological dryness (r = 0.60–0.77) explained a strong association between ecohydrological extremes and TR in determining the error structure of STIC1.2 predicted fluxes. Being independent of any leaf‐scale biophysical parameterization, the model might be an important value addition in working group (WG2) of the Australian Energy and Water Exchange (OzEWEX) research initiative which focuses on observations to evaluate and compare biophysical models of energy and water cycle components.
- University of Melbourne Australia
- King’s University United States
- Roskilde University Denmark
- Luxembourg Institute of Science and Technology Luxembourg
- Jet Propulsion Lab United States
550, WATER-RESOURCES, Penman-Monteith, evapotranspiration, land surface temperature, AERODYNAMIC RESISTANCE, ENERGY-BALANCE CLOSURE, MEDITERRANEAN DRYLANDS, XXXXXX - Unknown, Shuttleworth-Wallace, ta218, infrared imaging, thermal infrared sensing, PRIESTLEY-TAYLOR, surface energy balance, aridity gradient, Australia, Physical sciences, EVAPORATION, RADIOMETRIC SURFACE-TEMPERATURE, HEAT-FLUX, LATENT-HEAT, 2-SOURCE PERSPECTIVE, ecosystems, mathematical models
550, WATER-RESOURCES, Penman-Monteith, evapotranspiration, land surface temperature, AERODYNAMIC RESISTANCE, ENERGY-BALANCE CLOSURE, MEDITERRANEAN DRYLANDS, XXXXXX - Unknown, Shuttleworth-Wallace, ta218, infrared imaging, thermal infrared sensing, PRIESTLEY-TAYLOR, surface energy balance, aridity gradient, Australia, Physical sciences, EVAPORATION, RADIOMETRIC SURFACE-TEMPERATURE, HEAT-FLUX, LATENT-HEAT, 2-SOURCE PERSPECTIVE, ecosystems, mathematical models
2 Research products, page 1 of 1
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).40 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
