Subgrid parametrizations mediate the large‐scale effects of soil macroporosity on the water cycle in the ORCHIDEE land surface model

Soil structure is nearly as important as soil texture in determining the soil hydraulic properties at the core scale. At plot scale, soil structure—and particularly soil macroporosity—strongly affects drainage and the runoff–infiltration partition. At the 100‐km scale typical for land surface models, however, the effects of soil macroporosity appear suppressed. This is most likely due to the smearing of precipitation over large grid cells and over long time steps, which decreases precipitation intensity and results in soils rarely approaching saturation, where the effect of macroporosity on soil hydraulic properties is the strongest. Here, we show that accounting for the subgrid variabilities of soil hydraulic properties or precipitation counteracts the scale‐induced suppression of soil‐structural effects in a land surface model. We show this by introducing a physically motivated representation of soil macroporosity in the ORCHIDEE land surface model and testing to what extent its effects are mediated by the model's existing subgrid parametrizations. Specifically, we investigate the role of the temporal redistribution of precipitation within the forcing time step and the subgrid variability of soil hydraulic conductivity in the infiltration routine. By deactivating these parametrizations, we find that they mediate two‐thirds of the effect of soil macroporosity on the mean global runoff and on the mean global soil moisture. We also find that the effect of soil macroporosity on runoff in ORCHIDEE is an order of magnitude larger than previously reported for a similar soil structure parametrization in another land surface model. Moreover, the effect of macroporosity on soil moisture in ORCHIDEE is large enough to cause statistically significant regional atmospheric cooling in coupled land–atmosphere runs. Our results show that soil structure can play an important role at large scales, but capturing it requires representing the spatial or temporal subgrid variabilities of soil hydraulic properties or of precipitation.