Investigation of conditional SGS stress and conditional SGS stress production using surface layer (HATS) data

Subgrid-scale (SGS) stress in the atmospheric surface layer is studied using field measurements (HATS) data. We analyze the conditional SGS stress and the conditional SGS stress production rate conditional on the resolvable-scale velocity, which must be modeled accurately for large eddy simulation to reproduce the one-point resolvable-scale velocity statistics. The results show that the normal conditional SGS stress generally increases with both the vertical and the streamwise velocity components. The magnitudes of the shear stress components also increase with the resolvable-scale vertical velocity. The conditional production is generally enhanced by positive vertical velocity and the conditional energy transfer is forward. Large negative vertical velocity, on the other hand, causes the energy transfer to decreases and could lead to conditional backscatter. Buoyancy production and inter-component energy exchange are also shown to be important for the SGS stress evolution. The standard Smagorinsky model correctly predicts the trends of some shear stress components but not the normal components. More importantly it does not correctly predict the properties of the conditional SGS stress production. The results suggest that predicting the SGS stress through a model SGS stress transport equation has the potential to correctly predict both the conditional SGS stress and the conditional SGS stress production rate. Supported by NSF