• Author: Mallick, Kaniska

    Luxembourg Institute of Science and Technology, Luxembourg

  • Author: Toivonen, Erika

    Luxembourg Institute of Science and Technology, Luxembourg

  • Author: Trebs, Ivonne

    Luxembourg Institute of Science and Technology, Luxembourg

  • Author: Boegh, Eva

    Roskilde University, Denmark

  • Author: Cleverly, James

    University of Technology Sydney, Australia

  • Author: Eamus, Derek

    University of Technology Sydney, Australia

  • Author: Koivusalo, Harri

    Aalto University, Finland

  • Author: Drewry, Darren

    University of California, United States

  • Author: Arndt, Stefan K

    University of Melbourne, Australia

  • Author: Griebel, Anne

    University of Melbourne, Australia

  • Author: Beringer, Jason

    University of Western Australia, Australia

  • Author: Garcia, Monica

    Air, Land & Water Resources, Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet, 2800, Kgs. Lyngby, Denmark

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Thermal 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 to 0.43), evaporative index (r = 0.77 to 0.90), and climatological dryness (r = 0.60 to 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.
Original languageEnglish
JournalWater Resources Research
Issue number5
Pages (from-to)3409-3435
Number of pages27
Publication statusPublished - 2018

Bibliographical note

This is an open access article under theterms of the Creative CommonsAttribution-NonCommercial-NoDerivsLicense, which permits use anddistribution in any medium, providedthe original work is properly cited, theuse is non-commercial and no modifi-cations or adaptations are made.

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