Professor Benjamin Kirtman received his BS in Applied Mathematics from the University of California-San Diego in 1987, and his MS and PhD in 1992 from the University of Maryland-College Park. From 1993-2002 Dr. Kirtman was a research scientist with the Center for Ocean-Land-Atmosphere Studies and in 2002 joined the faculty of George Mason University as a tenured Associate Professor. In 2007, Dr. Kirtman moved to the University of Miami – Rosenstiel School for Marine and Atmospheric Science as a full professor and also serves as the Program Director of Physical Sciences and Engineering at the Center for Computational Science. In 2011, he was appointed Associate Dean for Research for the Rosenstiel School. In 2008, Professor Kirtman received the Distinguished Alumnus Award from the Department of Atmospheric and Oceanic Science at the University of Maryland.
Currently, Dr. Kirtman is co-Chair of the NOAA Climate Prediction Task Force and is a member of the NOAA Climate and Global Change Post-Doctoral Fellowship committee. Internationally, Dr. Kirtman has enjoyed a leadership role in the World Climate Research Program (WCRP) seasonal-to-interannual prediction activities. In particular, he has chaired the International Clivar Working Group on Seasonal to Interannual Prediction (WGSIP), and the WCRP Task Force for Seasonal Prediction (TFSP). Dr. Kirtman is a coordinating lead author for the Intergovenmental Panel on Climate Change (IPCC) working group one – the Scientific Basis. Professor Kirtman is also an Executive Editor of Climate Dynamics one the most prestigious peer reviewed journals in the field and is an Associate Editor of the American Geophysical Union Journal of Geophysical Research (Atmospheres). Dr. Kirtman has received numerous research grants from the National Science Foundation, Departement of Energy, NOAA, NASA, and the Office of Naval Research, and he leads the North American Multi-Model Ensemble Prediction (NMME) Experiment. Professor Kirtman is the author and/or co-author of over 100 peer reviewed papers focused on understanding and predicting climate variability on time scales from intra-seasonal to multi-decadal.