An offline-trained controller augments autoregressive diffusion models to perform fast, feed-forward data assimilation in chaotic spatiotemporal PDEs with order-of-magnitude speedups and improved accuracy over baselines.
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DATO and QMDA represent substantially different assimilation paradigms with distinct advantages and limitations in interpretability, robustness, and scalability.
This is an introductory review of the linear algebraic subproblems and contemporary solvers in variational data assimilation for geophysical applications.
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An Introduction to Solving the Least-Squares Problem in Variational Data Assimilation
This is an introductory review of the linear algebraic subproblems and contemporary solvers in variational data assimilation for geophysical applications.