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The statistical representation of multiple land surfaces within a grid cell has received attention as a means to parameterize the nonlinear effects of subgrid-scale heterogeneity on land-atmosphere energy exchange. However, previous analyses have not identified the critical land-surface parameters to which energy exchanges are sensitive; the appropriate number of within-grid-cell classes for a particular parameter, or the effects of interactions among several parameters on the nonlinearity of energy exchanges. The analyses reported here used a land-surface scheme for climate models to examine the effects of subgrid variability in leaf area index, minimum and maximum stomatal resistances, and soil moisture on grid-scale fluxes. Comparisons between energy fluxes obtained using parameter values for the average of 100 subgrid points and the average fluxes for the 100 subgrid points showed minor differences for emitted infrared radiation and reflected solar radiation, but large differences for sensible heat and evapotranspiration. Leaf area index was the most important parameter; stomatal resistances were only important on wet soils. Interactions among parameters increased the nonlinearity of land-atmosphere energy exchange. When considered separately, six to ten values of each parameter greatly reduced the deviation between the two flux estimates. However, this approach became cumbersome when all four parameters varied independently. These analyses suggest that the debate over how to best parameterize the nonlinear effects of subgrid-scale heterogeneity on land-atmosphere interactions will continue.
Bonan et al. (Fri,) studied this question.