Daryl Kleist Homepage

As of January 2017, I have formally returned to the federal government, where I have spent more than a decade at NOAA/National Centers for Environmental Prediction/Environmental Modeling Center working as a member of the data assimilation team in the global weather and climate modeling branch. I maintain a close connection to the department as an adjunct assistant professor.

My primary interest is in the use of data assimilation to improve numerical weather prediction, most recently through the use of the hybrid EnVar algorithm for the NCEP Global Forecast System model. I am also interested in atmospheric predictability, ensemble forecasting methods, and numerical modeling.

More generally, I am interested in a wide variety of atmospheric phenomenon including mid-latitude cyclones, tropical cyclones, and severe weather.

My primary teaching responsibility is Synoptic Meteorology (AOSC 470/600).

Data Assimilation

Data assimilation is used for state estimation by combining observations with numerical models of a physical system. My main area of interest is in algorithm development aimed at improving initial conditions for numerical weather prediction. As part of my PhD thesis as well as my efforts at NCEP/EMC, I worked on developing and testing a hybrid ensemble-variational (EnVar) algorithm for use with the operational global data assimilation system and global forecast system model. Recently, work has been focused on extending this to four dimensions, i.e. 4DEnVar: a unique 4D variational-based method that does not require a tangent linear or adjoint model.

Publications

Image from Lahoz, W. A., and P. Schneider, Data Assimilation: Making Sense of Earth Observation, Frontiers in Environmental Science

(DOI=10.3389/fenvs.2014.00016)