Articles | Volume 15, issue 1
https://doi.org/10.5194/gmd-15-251-2022
https://doi.org/10.5194/gmd-15-251-2022
Model evaluation paper
 | 
13 Jan 2022
Model evaluation paper |  | 13 Jan 2022

Convolutional conditional neural processes for local climate downscaling

Anna Vaughan, Will Tebbutt, J. Scott Hosking, and Richard E. Turner

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Latest update: 13 Jul 2025
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Short summary
We develop a new method for climate downscaling, i.e. transforming low-resolution climate model output to high-resolution projections, using a deep-learning model known as a convolutional conditional neural process. This model is shown to outperform an ensemble of baseline methods for downscaling daily maximum temperature and precipitation and provides a powerful new downscaling framework for climate impact studies.
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