Dr. Jonathan Poterjoy is an Associate Professor at the University of Maryland, where he serves as the Graduate Program Director for the Department of Atmospheric and Oceanic Science. His research focuses on improving numerical modeling and data assimilation for Earth system prediction. He obtained his academic training in meteorology and atmospheric science, earning a Ph.D. in Meteorology from Pennsylvania State University, where he specialized in ensemble-based data assimilation techniques to enhance forecast accuracy.

Dr. Poterjoy has contributed to advancing ensemble Kalman filter (EnKF) approaches, four-dimensional variational (4DVar) methods, localized particle filters (PFs), and hybrid data assimilation frameworks. His research has emphasized applications in high-impact weather events—such as hurricanes and mid-latitude cyclones—and has explored ways to optimize predictive skill within operational forecasting systems. His present research focuses on bridging new data assimilation theory to large applications, using mathematical developments in state and parameter estimation and machine learning.

In addition to his technical contributions, Dr. Poterjoy has mentored numerous graduate students and early career scientists. He regularly serves on committees and panels aimed at bridging gaps between meteorological research and operational forecasting and currently serves as an associate editor for the American Meteorological Society, American Geophysical Union, and Royal Meteorological Society.