Generalizing Monin-Obukhov Similarity Theory (1954) for Complex Atmospheric Turbulence

Monin-Obukhov similarity theory (MOST) forms the basis for parametrizations of turbulent exchange in virtually all numerical models of atmospheric flows. Yet, its limitations to flat and horizontally homogeneous terrain have plagued the theory since its inception. Here we present a first generalized extension of MOST based on the inclusion of turbulence anisotropy as an additional nondimensional term. This novel theory developed based on an unprecedented ensemble of complex atmospheric turbulence datasets covering flat to mountainous terrain, is shown to be valid in conditions in which MOST fails and thus paves the way to a better understanding of complex turbulence.

Automated summary

Monin-Obukhov similarity theory (MOST) is the basis for parameterizations of turbulent exchange in numerical models, but its limitations to flat and horizontally homogeneous terrain have been a long-standing issue. In this study, a generalized extension of MOST based on turbulence anisotropy is presented, which is validated using complex atmospheric turbulence datasets covering various terrains. This novel theory provides a better understanding of complex turbulence where MOST fails.