Including Atmospheric Layers in Vegetation and Urban Offline Surface Schemes

Abstract

Abstract A formulation to include prognostic atmospheric layers in offline surface schemes is derived from atmospheric equations. Whereas multilayer schemes developed previously need a complex coupling between atmospheric-model levels and surface-scheme levels, the coupling proposed here remains simple. This is possible because the atmospheric layers interacting with the surface scheme are independent of the atmospheric model that could be coupled above. The surface boundary layer (SBL; both inside and just above the canopy) is resolved prognostically, taking into account large-scale forcing, turbulence, and, if any, drag and canopy forces and surface fluxes. This formulation allows one to retrieve the logarithmic law in neutral conditions, and it has been validated when coupled to a 3D atmospheric model. Systematic comparisons with 2-m observations and 10-m wind have been made for 2 months. The SBL scheme is able to model the 2-m temperature accurately, as well as the 10-m wind, without any use of analytical interpolation. The largest improvement takes place during stable conditions (i.e., by night), during which analytical laws and interpolation methods are known to be less accurate, and in mountainous areas, in which nocturnal low-level flow is strongly influenced by surface cooling. The prognostic SBL scheme is shown to solve the nighttime physical disconnection problem between surface and atmosphere models. The inclusion of the SBL into the urban Town Energy Balance scheme is presented in a paper by Hamdi and Masson in which the ability of the method to simulate the profiles of both mean and turbulent quantities from above the building down to the road surface is shown using data from the Basel Urban Boundary Layer Experiment (BUBBLE). The proposed method will allow the inclusion of the detailed physics of the multilayer schemes (e.g., the interactions of the SBL flow with forest or urban canopy) into a single-layer scheme that is easily coupled with atmospheric models.