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. Accurately estimating large-scale evapotranspiration (ET) rates is essential to understanding and predicting global change. Evapotranspiration modelsthat are applied at a continental scale typically operate on relatively large spatial grids, with the result that the heterogeneity in land surfaceproperties and processes at smaller spatial scales cannot be explicitly represented. Averaging over this spatial heterogeneity may lead to biasedestimates of energy and water fluxes. Here we estimate how averaging over spatial heterogeneity in precipitation ( P ) and potentialevapotranspiration (PET) may affect grid-cell-averaged evapotranspiration rates, as seen from the atmosphere over heterogeneous landscapesacross the globe. Our goal is to identify where, under what conditions, and at what scales this “heterogeneity bias” could be most important butnot to quantify its absolute magnitude. We use Budyko curves as simple functions that relate ET to precipitation and potentialevapotranspiration. Because the relationships driving ET are nonlinear, averaging over subgrid heterogeneity in  P  and PET will lead to biasedestimates of average ET. We examine the global distribution of this bias, its scale dependence, and its sensitivity to variations in  P  vs.PET. Our analysis shows that this heterogeneity bias is more pronounced in mountainous terrain, in landscapes where spatial variations in  P  and PETare inversely correlated, and in regions with temperate climates and dry summers. We also show that this heterogeneity bias increases on average,and expands over larger areas, as the grid cell size increases.

hydrology and earth system sciences

Global assessment of how averaging over spatial heterogeneity in precipitation and potential evapotranspiration affects modeled evapotranspiration rates