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Benchmarking Generative Models for Weather Data Assimilation on Real Station Observations
Weather reanalysis products rely on computationally intensive numerical weather predictions followed by data assimilation that corrects the forecast toward observations. Deep generative models offer a cheaper alternative that shifts much of this cost from inference to offline training. However, exis
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