Thermal infrared (TIR) remote sensing of vegetation temperature, combined with surface energy balance modeling, allows efficient estimation of spatially distributed evapotranspiration (ET). Many ET models are sensitive to the parameterization of stomatal control; yet, modelers often employ spatially uniform stomatal resistance values, even in distributed applications. Unfortunately, assuming uniform resistance across a canopy with large temperature variance is physically unrealistic and may produce artifacts in ET magnitude. To account for spatial variations in stomatal control that likely accompany temperature variations, we propose nesting a new submodel within some well-established ET models. The submodel derives, for the canopy patch of interest, a concave-downward relationship between stomatal conductance and temperature, as expected from plant biology. Using the submodel, each pixel's contribution to the total canopy patch ET is influenced both by its observed temperature and by its location-specific estimated stomatal resistance. The submodel requires only one more parameter than the unmodified ET models, which can be obtained from the literature; it conserves energy between the pixel and image scales, unlike single-valued resistance approaches; it produces realistic ET values at extreme temperature locations; and provides a remote sensing-based way to estimate the in situ canopy stomatal conductance-temperature relationship, which otherwise must be measured under controlled conditions. Since very high-resolution TIR data provide one means to observe large temperature variance, the submodel was tested using data with cm-scale pixels collected over 1.5 m2 patches of two vegetation types. The biophysical relationships derived by the submodel were successfully verified against laboratory data.