Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3‐Bins. (29th March 2017) - Baker, I. T.; Sellers, P. J.; Denning, A. S.; Medina, I.; Kraus, P.; Haynes, K. D.; Biraud, S. C.
Abstract: The interaction of land with the atmosphere is sensitive to soil moisture ( W ). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f ( W ), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell‐average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed to represent subgrid scale heterogeneity, including: (1) statistical‐dynamical representations of grid subelements of varying wetness, (2) relaxation of f ( W ), (3) moderating f ( W ) with approximations of catchment hydrology, (4)" tiling" the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape‐scale W is represented as a series of" Bins" of increasing wetness from dry to saturated. The grid cell‐level f ( W ) is defined by the integral of the fractional area of the wetness bins and the value of f ( W ) associated with each. This approach accounts for the spatiotemporal dynamics of W . We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W . We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs. Key Points: Soil moisture is a strong regulator of evapotranspiration (ET), and varies on spatial scales much smaller than atmospheric model grid cells We present a method to account for subgrid scale variability, using wetness bins of variable area to relate soil moisture to ET In a test against tower flux data, this new method performs well in regions where soils transition from wet to dry during the seasonal cycle