I utilize ensemble data assimilation within my research to combine model forecasts and observations in order to obtain the best estimate of the current state of the atmosphere, including uncertainties, and improve forecasts. The Ensemble Kalman Filter (EnKF) uses a flow-dependent background error covariance estimate from short-term ensemble forecasts to propagate information from observations to model state variables, as depicted below. In my research I assimilate a combination of conventional and airborne observations as well as all-sky satellite radiances.