PNNL

Abstract

The sensitivity of high resolution mesoscale simulations over simple and complex terrain to boundary layer turbulence parameterizations is investigated using the Penn State/NCAR Fifth Generation Mesoscale Model (MM5) and observations from two field campaigns. Three widely-used turbulence parameterizations were selected for evaluation, two of which [Blackadar (BK) and Medium Range Forecast (MRF) schemes] are simple first-order non-local schemes and one [Gayno-Seaman scheme (GS)] of which is a more complex 1.5-order local scheme that solves a prognostic equation for turbulence kinetic energy (TKE). The two data sets are the summer 1996 Boundary Layer Experiment (BLX96) in the Southern Great Plains and the fall 2000 Vertical Transport and Mixing (VTMX) field campaign in the Salt Lake Valley, Utah. Comparisons are made between observed and simulated mean variables and turbulence statistics. Despite the differences in their complexity, all three schemes show similar skill predicting near-surface and boundary-layer mean temperature, humidity, and winds at both locations. The BK and MRF schemes produced daytime boundary layers that are more mixed than those produced by the GS scheme. The mixed-layer depths are generally overestimated by the MRF scheme, underestimated by the GS scheme, and well estimated by the BK scheme. All schemes substantially overestimated surface sensible heat fluxes, but predicted surface latent heat fluxes agreed reasonably well with the observed values. In addition, each parameterization overestimated the sensible and latent heat flux aloft when compared to the aircraft observations made during BLX96, implying an overestimate of the flux divergence across the convective boundary layer. The results indicate that there is little gain in the overall accuracy of forecasts with increasing complexity of turbulence parameterizations. Therefore, it follows that in applications for which computational time is a critical factor, such as emergency response modeling, would benefit from using the relatively quick MRF scheme.