The Department of Atmospheric and Oceanic Science at the University of Maryland is led by Assistant Professor Jonathan Poterjoy, a renowned expert in advanced data assimilation techniques for geophysical research. With a background in meteorology and applied mathematics, Poterjoy focuses on improving environmental prediction systems, particularly for hazardous weather events like tropical cyclones and severe convective storms. His research involves collaborating with meteorologists, modelers, and scientists in the uncertainty quantification community to develop state-of-the-art methods for probabilistic weather forecasting.
The department is currently involved in several projects, including improving convective-scale weather prediction through advanced Bayesian filtering, verification, and uncertainty quantification, advancing NOAA's Earth system modeling efforts through improvements in model physics and sea ice data assimilation, and investigating new ways to estimate uncertainty for novel environmental measurements. These projects aim to enhance the accuracy and reliability of weather forecasts, addressing the challenges posed by high-dimensional nonlinear systems and limitations in numerical models and observation collection. The department's work contributes to the development of the NOAA Unified Forecast System and supports advancements in seasonal environmental predictions.
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