Local similarity functions for katabatic flows derived from field observations over steep- and shallow-angled slopes

Katabatic flows, or buoyantly driven drainage flows over sloping terrain, play an important role in heat transport, cold pool formation in basins and valleys, CO2 and pollutant transport, fog and frost formation, etc. However, these flows are notoriously difficult to simulate in numerical weather prediction models for a variety of practical reasons; Most notably, Monin-Obukhov similarity theory (MOST), which was developed for horizontal terrain, has been shown to be inadequate for katabatic flows because they exhibit significant flux divergence in the slope-normal (and vertical) direction. Several recent studies of the near-surface turbulence in katabatic flows over mountainous terrain provide adequate resolution to explore this flux divergence and its implications for local flux-gradient similarity scaling. In this work, we show that local scaling for katabatic flow does not follow the traditional, horizontal-terrain parameterizations such as the Businger-Dyer relations and propose modified local-MOST stability-correction functions for katabatic flows, informed by near-surface turbulence observations collected from two mountainous slopes at different angles (α). The field sites are the east slope of Granite Mountain (UT, USA,α≈5º) from the MATERHORN-X campaign and a west-facing Alpine slope in Val Ferret (Switzerland,α≈35.5º). Both sites have short sparse vegetation, mainly grasses, bushes and shrubs. The proposed relations include directly, and data from both the steep- and shallow-angled slopes collapse with unprecedented agreement compared to previous attempts to develop flux-gradient relations for katabatic flows. Results from this study can be used in prescribing the wall-model and/or turbulence closures in numerical simulations of katabatic flows.