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Christina Winkler

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Climate Variable Downscaling with Conditional Normalizing Flows
Christina Winkler
Paula Harder
David Rolnick
Predictions of global climate models typically operate on coarse spatial scales due to the large computational costs of climate simulations.… (see more) This has led to a considerable interest in methods for statistical downscaling, a similar process to super-resolution in the computer vision context, to provide more local and regional climate information. In this work, we apply conditional normalizing flows to the task of climate variable downscaling. We showcase its successful performance on an ERA5 water content dataset for different upsampling factors. Additionally, we show that the method allows us to assess the predictive uncertainty in terms of standard deviation from the fitted conditional distribution mean.
2024-05-30
ArXiv (preprint)
doi.org
arxiv.org
Towards Climate Variable Prediction with Conditioned Spatio-Temporal Normalizing Flows
Christina Winkler
David Rolnick
2023-11-11
ArXiv (preprint)
arxiv.org
arxiv.org