Search

Thermal infrared sensing of evapotranspiration (E) through surface energy balance (SEB) models is challenging due to uncertainties in determining the aerodynamic conductance (g(A)) and due to inequalities between radiometric (T-R) and aerodynamic temperatures (T-0). We evaluated a novel analytical model, the Surface Temperature Initiated Closure (STIC1.2), that physically integrates T-R 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 T-R 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. Plain Language Summary Evapotranspiration modeling and mapping in arid and semi-arid ecosystems are uncertain due to empirical approximation of surface and atmospheric conductances. Here we demonstrate the performance of a fully analytical model which is independent of any leaf-scale empirical parameterization of the conductances and can be potentially used for continental scale mapping of ecosystem water use as well as water stress using thermal remote sensing satellite data.d

Here we demonstrate a novel method to physically integrate radiometric surface temperature (TR) into the Penman-Monteith (PM) formulation for estimating the terrestrial sensible and latent heat fluxes (H and λE) in the framework of a modified Surface Temperature Initiated Closure (STIC). It combines TR data with standard energy balance closure models for deriving a hybrid scheme that does not require parameterization of the surface (or stomatal) and aerodynamic conductances (gS and gB). STIC is formed by the simultaneous solution of four state equations and it uses TR as an additional data source for retrieving the “near surface” moisture availability (M) and the Priestley-Taylor coefficient (α). The performance of STIC is tested using high-temporal resolution TR observations collected from different international surface energy flux experiments in conjunction with corresponding net radiation (RN), ground heat flux (G), air temperature (TA), and relative humidity (RH) measurements. A comparison of the STIC outputs with the eddy covariance measurements of λE and H revealed RMSDs of 7–16% and 40–74% in half-hourly λE and H estimates. These statistics were 5–13% and 10–44% in daily λE and H. The errors and uncertainties in both surface fluxes are comparable to the models that typically use land surface parameterizations for determining the unobserved components (gS and gB) of the surface energy balance models. However, the scheme is simpler, has the capabilities for generating spatially explicit surface energy fluxes and independent of submodels for boundary layer developments.