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Back to Departmental Colloquium: Fall 2024

Departmental Colloquium


Date: Thursday, Oct 3, 2024

Time: 4:00PM - 5:00PM

Location: JWB 335


Daniel Sanz-Alonso

University of Chicago

Title

Ensemble Kalman Methods and Structured Operator Estimation

Abstract

Data assimilation is concerned with estimating the state of a dynamical system from partial observations. In applications such as numerical weather prediction where the state is high dimensional and the dynamics are expensive to simulate, ensemble Kalman filters are often the method of choice. In this talk, I will present new results on structured covariance operator estimation that help explain why these algorithms can be effective even when deployed with a small ensemble size. Our theory also explains the importance of using covariance localization in ensemble Kalman methods for global data assimilation.

Applied Mathematics Data Science and Machine Learning

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