An Evaluation of Boundary-Layer Characteristics Predicted by MM5 (Formerly Poster P4.4)

We have completed a study in which we evaluate the performance of the Penn State/NCAR Fifth Generation Mesoscale Model (MM5) using three different turbulence parameterizations against data from two field campaigns. Two of the turbulence parameterizations are simple first-order non-local schemes [Blackadar (BK) and Medium Range Forecast (MRF) 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 predicted surface latent heat fluxes that agreed reasonably well with the observed values, but they substantially overestimated surface sensible heat fluxes due to a significant over-prediction of net radiation. In addition, each parameterization overestimated the sensible and latent heat flux aloft. The results suggest that there is little gain in the overall accuracy of forecasts with increasing complexity of turbulence parameterizations.