Hyperlocal Downscaling using WRF: Science, Technology and Applications
Weather Analytics has begun to construct a continuously updated, hyper-local database of weather events at a resolution higher than is produced by any operational NWP or analysis system. Using the advanced research version of the Weather Research and Forecasting Model (WRF-ARW), cloud-based computing infrastructure, and a dynamical data assimilation method, a number of high-impact variables are created through a downscaling process. By utilizing a multi-dimensional nudging data assimilation system with a quality-controlled set of several observation types, downscaling to 1 km resolution captures well the actual atmospheric state when compared to available observations. The hyper-local simulated data is then merged with various observational data to produce a global historical dataset that enables verification and understanding of past events. With the database as the foundation, several products are under development to inform “weather intelligent” business decisions.