Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data
Abstract Understanding monthly-to-annual climate variability is essential for adapting to future climate extremes. Key ways to do this are through analysing climate field reconstructions and reanalyses. However, producing such reconstructions can be limited by high production costs, unrealistic line...
Main Authors: | Martin Wegmann, Fernando Jaume-Santero |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-06-01
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Series: | Communications Earth & Environment |
Online Access: | https://doi.org/10.1038/s43247-023-00872-9 |
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