Generalized MOST Framework with Turbulence Anisotropy as a Boundary Condition for High Resolution Large-Eddy-Simulations.

Since its original conception, Monin-Obukhov similarity theory (MOST) has served as the foundational framework for parameterizing land-atmosphere momentum, energy, and scalar exchanges at the ground surface in atmospheric models of different resolution. MOST is literally implemented in every climate and weather model, allowing the coupling of surface processes with the atmosphere. However, the limitations of MOST under non-homogeneous surface conditions—where a roughness sublayer develops and the assumptions of homogeneity, stationarity, and the absence of subsidence breakdown— remain a limitation in the representation of near-surface processes and pose significant challenges for the advancement and accuracy of climate and weather models. Corrections to the theory for specific applications have been developed through time, but a generalized framework for all surface conditions has remained elusive. More recent research has suggested the possibility of including turbulence anisotropy as an additional non-dimensional term, as a means to generalize the framework to all complex surface and flow conditions, and thus expanding its applications. New formulations for the variances and flux-gradient scaling relations, integrating the anisotropy invariant y B , were developed with the goal of implementing them in all atmospheric modeling frameworks. In this study, we incorporate for the first time, turbulence anisotropy as a correction to traditional MOST scaling relations in a high-resolution LES framework. The needed anisotropy invariants are computed on-the-fly at each iteration using a local time-averaging algorithm. This work will investigate the performance of such corrections for different ABL and surface configurations.