Steady progresses have been made developing and applying variational and ensemble-based DA methods by the research community over the past two decades, and the progress has accelerated over the most recent decade with the application of ensemble-based methods to this problem. Ensemble Kalman filter (EnKF) has now been successfully applied to the assimilation of radar data with different measurement characteristics, and in combination with multi-moment microphysics schemes that predict particle number concentrations as well as hydrometer mixing ratios. Such analyses and forecasts are now capable of re-producing observed polarimetric radar signatures, and some progresses have also been made to assimilate polarimetric radar parameters. Algorithms and systems to effectively assimilate fast-scan phased-array radars and to assimilate full-volume data from continental-scale radar networks have also been developed and applied to realtime experimental forecasts. Operational NWP systems have started assimilate radar data that have been shown to significantly reduce the precipitation spinup problem. Techniques that combine variational and ensemble approaches provide additional avenues for research. This talk will try to review research progresses in the above areas, with emphasis on research and operational progresses within the United States over the past 10 years. Future challenges will also be discussed.
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