Improved High-Fidelity Forecasting Capability using Combined Mesoscale and Microscale Models

We propose to improve the accuracy and capability of Numerical Weather Prediction (NWP) and Atmospheric Transport and Dispersion (ATD) models by performing a tight, downscale/upscale coupling of a community NWP forecasting system, WRF, with a special purpose, urban-to-microscale Computational Fluid Dynamics (CFD) model. This new capability addresses “bridging the gap” between the mesoscale and microscale, providing improved mesoscale-to-urban-scale wind, turbulence and contaminant transport and dispersion modeling fidelity and accuracy. We will couple the models using the public-domain, Model Coupling Environmental Library (MCEL), whose client/server, dataflow model provides the framework that both the NWP and CFD need to implement and assess a range of upscale and downscale data transfer methods. To provide this state-of-the-science and readily-distributable microscale modeling capability, we will modify a special-purpose CFD solver that uses Adaptive Cartesian Mesh Refinement methods that has been developed under previous DTRA SBIR funding. This special-purpose, microscale CFD capability will solve meteorologically consistent governing equations, employ scale appropriate building and terrain treatments, and be designed to be effectively coupled within the environment. The software capability and framework may be readily extended to other community NWP and microscale models, and lays the framework to bridge the gap between mesoscale and urban/microscale models.