Mengs successfully defended his dissertation on April 28, 2009.
Investigation of Stable and Unstable Boundary Layer Phenomena Using Observations and a Numerical Weather Prediction Model
Despite significant advances in the simulation of synoptic scale weather events, current numerical weather prediction models show poor skill in their capability to accurately simulate sub-grid scale features, such as cloud-precipitation processes and planetary boundary layer (PBL) evolution, because too many semi-empirical parameterizations are involved. The goal of the work presented here is to evaluate the next-generation mesoscale Weather Research and Forecasting (WRF) model in simulating mesoscale weather phenomena under different PBL stratifications. The work presented in this thesis investigates the performance of the state-of-the-art mesoscale WRF model in simulating the structure and development of a daytime convective boundary layer phenomenon, (the dryline over the Southern Great Plains), and a nocturnal stable boundary layer phenomenon, (the Low-Level-Jet (LLJ) over the Mid-Atlantic region). The dryline and LLJ are two examples of boundary layer phenomena that occur under very different conditions and thus together they provide a good test of the PBL dynamics in the model. Extensive, high spatial and temporal resolution data collected during these case studies is used to evaluate the numerical results. For the unstable boundary layer, a detailed observational analysis of a non-convective dryline investigates an incorrect forecast. For the stable boundary layer, the accuracy of the timing and spatial characteristics of the LLJ for different PBL parameterizations is investigated and discussed in terms of the LLJ forcing mechanisms.