Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching
Data assimilation (DA) uses Bayesian inference to update the state of a numerical forecast model with observed data. In this study, we propose a fundamentally different, unified approach to atmospheric data assimilation. We use latent video flow-matching to sample temporally consistent trajectories from a prior trained using ERA5 reanalysis (69 variables over an 8-day window). We also use posterior sampling to assimilate real observation sources, such as those from the NOAA Integrated Global Radiosonde Archive and the Integrated Surface Database. Because the prior generates a continuous trajectory, it naturally propagates information between observed and unobserved frames. Therefore, we c...
| Authors | Dibyajyoti Chakraborty, Romit Maulik |
|---|---|
| Primary category | cs.LG |
| Published | 5 August 2026 |
| Last updated at source | 6 August 2026 |
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