PnP-DA combines a lightweight variational observation update with a pretrained conditional flow-matching denoiser to reduce analysis error in chaotic data assimilation, outperforming 3D-Var on Lorenz 63, Lorenz 96, and Kuramoto-Sivashinsky testbeds.
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PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models
PnP-DA combines a lightweight variational observation update with a pretrained conditional flow-matching denoiser to reduce analysis error in chaotic data assimilation, outperforming 3D-Var on Lorenz 63, Lorenz 96, and Kuramoto-Sivashinsky testbeds.