Effects of spatial variability in topography, vegetation cover and soil moisture on area‐averaged surface fluxes: A case study using the FIFE 1989 data

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Abstract
A modified version of the simple biosphere model (SiB) of Sellers et al. (1986) was used to investigate the impact of spatial variability in the fields of topography, vegetation cover, and soil moisture on the area‐averaged fluxes of sensible and latent heat for an area of 2×15 km (the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) testbed area) located within the FIFE area. This work builds on a previous study of Sellers et al. (1992a) but makes use of a superior data set (FIFE 1989 rather than FIFE 1987) and has a sharper focus on the nonlinear effects of soil wetness on evapotranspiration. The 2×15 km testbed area was divided into 68×501 pixels of 30×30 m spatial resolution, each of which could be assigned topographic, vegetation condition, and soil moisture parameters from satellite and in situ observations gathered in FIFE‐89. One or more of these surface fields was area averaged in a series of simulation runs to determine the impact of using large‐area means of these initial/boundary conditions on the area‐integrated (aggregated) surface fluxes. Prior to these simulations some validation work was done with the model. The results of the study can be summarized as follows: (1) SiB was initialized with satellite and airborne remotely sensed data for vegetation condition and soil wetness, respectively. The surface fluxes calculated by SiB compared well with surface‐based and airborne flux observations. (2) Analyses and some of the simulations indicated that the relationships describing the effects of moderate topography on the surface radiation budget are near linear and thus largely scale invariant. The relationships linking the simple ratio (SR) vegetation index, the canopy conductance parameter ∇F, and the canopy transpiration flux are also near linear and similarly scale invariant to first order (see also Sellers et al., 1992a). Because of this it appears that simple area‐averaging operations can be applied to these fields with relatively little impact on the calculated surface heat fluxes. (3) The relationships linking surface and root‐zone soil wetness to the soil surface and canopy transpiration rates are nonlinear. However, simulation results and observations indicate that soil moisture variability decreases significantly as the study area dries out, which partially cancels out the effects of these nonlinear functions. (4) The near‐infrared surface reflectance ρN estimated from atmospherically corrected satellite data may be a better predictor of vegetation condition than a two‐band vegetation index, such as the SR, at least for the grasslands represented in the FIFE area. These results support the use of simple averages of topographic and vegetation parameters to calculate surface energy and heat fluxes over a wide range of spatial scales, from a few meters up to many kilometers. Although the relationships between soil moisture and evapotranspiration are nonlinear for intermediate soil wetnesses, the dynamics of soil drying act to progressively reduce soil moisture variability and thus the impacts of these nonlinearities on the area‐averaged surface fluxes. These findings indicate that we can use mean values of topography, vegetation condition, and soil moisture to calculate the surface‐atmosphere fluxes of energy, heat, and moisture at larger length scales to within an acceptable accuracy for climate‐modeling work.