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arXiv · 2509.21399

Downscaling climate projections to 1 km with single-image super resolution

Petr Košťál·Pavel Kordík·Ondřej Podsztavek
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Abstract

High-resolution climate projections are essential for local decision-making. However, available climate projections have low spatial resolution (e.g. 12.5 km), which limits their usability. We address this limitation by leveraging single-image super-resolution models to statistically downscale climate projections to 1-km resolution. Since high-resolution climate projections are unavailable, we train models on a high-resolution observational gridded data set and apply them to low-resolution climate projections. We cannot evaluate downscaled climate projections with common metrics (e.g. pixel-wise root-mean-square error) because we lack ground-truth high-resolution climate projections. Therefore, we evaluate climate indicators computed at weather station locations. Experiments on daily mean temperature demonstrate that single-image super-resolution models can downscale climate projections without increasing the error of climate indicators compared to low-resolution climate projections.

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Petr Košťál, Pavel Kordík, Ondřej Podsztavek. 2025-09-24. Downscaling climate projections to 1 km with single-image super resolution. https://arxiv.org/abs/2509.21399

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