Machine learning shows a limit to rain-snow partitioning accuracy when using near-surface meteorology
Abstract Partitioning precipitation into rain and snow with near-surface meteorology is a well-known challenge. However, whether a limit exists to its potential performance remains unknown. Here, we evaluate this possibility by applying a set of benchmark precipitation phase partitioning methods plu...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-58234-2 |
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