Limitation of super-resolution machine learning approach to precipitation downscaling
Abstract The present study explores the potential of super-resolution machine learning (ML) models for precipitation downscaling from 100 to 12.5 km at hourly timescale using the Conformal Cubic Atmospheric Model (CCAM) data over the Australian domain. Two approaches were examined: the perfect appro...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-05880-7 |
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