Daryl T. Kleist is an Assistant Professor at the University of Maryland. His research interests include data assimilation, numerical weather prediction, atmospheric predictability, targeted observing, data thinning and forecast sensitivity. His data assimilation research has primarily focused on improving initial conditions through algorithm development for operational numerical weather prediction for short- and medium-range time scales. Most recently, he has worked on developing and testing a hybrid ensemble-variational (EnVar) algorithm with an extension to four dimensions that does not require the use of an adjoint model. Before joining the faculty at Maryland, Dr. Kleist spent more than ten years working at the National Centers for Environmental Prediction (NCEP) Environmental Modeling Center as a member of the data assimilation team and within the global climate and weather modeling branch. There, he worked on various aspects of the operational data assimilation system for the global forecast system. Prior to leaving NCEP, he was leading the effort on the testing and development of the 4D EnVar algorithm for operational implementation in the global data assimilation system. Dr. Kleist earned his Ph.D. in Atmospheric and Oceanic Science from the University of Maryland.