Inter-comparison between different PBL options in WRF model. Modification of two PBL schemes for stable conditions

High-resolution runs of the Advanced Research version of the Weather Research and Forecasting (WRF) model were done to test the abilities of the code for mountain terrain numerical modeling. Data from two MATERHORN field experiments (www.nd.edu/~dynamics/materhorn) were used in this study. The importance of boundary layer parameterization has been well recognized and substantial amount of work has been done in this regard. However, the progress of boundary layer parameterization in meso-scale numerical models is still continuing because of the challenges of representing small scale processes, especially during nocturnal and transition periods. The turbulence parameterization continues to be a challenge, and interactions of various scales and associated fluxes are difficult to represent in the models. We investigated the capabilities and limitations of different Planetary Boundary Layer (PBL) options available in the WRF model for MATERHORN data, and tested these options for stable conditions. Six different schemes were used: YSU (YonSei University), MRF (Medium Range Forecast), MYJ (Mellor-Yamada-Janjic), BouLac (Bougeault-LaCarrere), QNSE (Quasi-Normal Scale Elimination) and ACM2 (Asymmetric Convective Model). Modeling outcomes were compared with the observations, and with the results of two modified PBL schemes (K-Theory Approach) - YSU and MRF. Strong, thermally forced, near-surface meso-scale jets developed over the surrounding flat terrain create intense short-lived turbulence. Collisions between katabatic and valley flows produced short lived intense turbulence events that contributed to high fluxes over short periods. The existing parameterizations in meso-scale models cannot capture such transient vigorous episodes, which can play a significant role in determining the flow patterns. Further investigation and proper parameterizations of these processes can help to improve the mountain terrain weather predictions under stable conditions.