Ensemble data assimilation across a range of scales and phenomena with WRF/DART

Ensemble Kalman filters are appealing for mesoscale data assimilation because of the generality of their background covariance model, which potentially is applicable across a range of flows and phenomena. We have developed a set of interfaces and observation operators for the Weather Research and Forecasting model (WRF) within the Data Assimilation Research Testbed (DART). The capabilities of WRF/DART will be summarized, along with results from applications of an ensemble Kalman filter to convective storms (using Doppler radar observations and resolution of ~1 km), tropical cyclones (using mainly conventional observations and resolution of ~10 km) and mesoscale analyses based on surface observations (at resolution of ~10 km).