Causal networks for climate model evaluation and constrained projections
Algorithms to assess causal relationships in data sets have seen increasing applications in climate science in recent years. Here, the authors show that these techniques can help to systematically evaluate the performance of climate models and, as a result, to constrain uncertainties in future clima...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2020-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-020-15195-y |
| _version_ | 1818839170283470848 |
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| author | Peer Nowack Jakob Runge Veronika Eyring Joanna D. Haigh |
| author_facet | Peer Nowack Jakob Runge Veronika Eyring Joanna D. Haigh |
| author_sort | Peer Nowack |
| collection | DOAJ |
| description | Algorithms to assess causal relationships in data sets have seen increasing applications in climate science in recent years. Here, the authors show that these techniques can help to systematically evaluate the performance of climate models and, as a result, to constrain uncertainties in future climate change projections. |
| first_indexed | 2024-12-19T03:50:02Z |
| format | Article |
| id | doaj.art-f2492531e1f54417b930e5cbab085b2d |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-19T03:50:02Z |
| publishDate | 2020-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-f2492531e1f54417b930e5cbab085b2d2022-12-21T20:37:01ZengNature PortfolioNature Communications2041-17232020-03-0111111110.1038/s41467-020-15195-yCausal networks for climate model evaluation and constrained projectionsPeer Nowack0Jakob Runge1Veronika Eyring2Joanna D. Haigh3Grantham Institute, Imperial College LondonGrantham Institute, Imperial College LondonDeutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der AtmosphäreGrantham Institute, Imperial College LondonAlgorithms to assess causal relationships in data sets have seen increasing applications in climate science in recent years. Here, the authors show that these techniques can help to systematically evaluate the performance of climate models and, as a result, to constrain uncertainties in future climate change projections.https://doi.org/10.1038/s41467-020-15195-y |
| spellingShingle | Peer Nowack Jakob Runge Veronika Eyring Joanna D. Haigh Causal networks for climate model evaluation and constrained projections Nature Communications |
| title | Causal networks for climate model evaluation and constrained projections |
| title_full | Causal networks for climate model evaluation and constrained projections |
| title_fullStr | Causal networks for climate model evaluation and constrained projections |
| title_full_unstemmed | Causal networks for climate model evaluation and constrained projections |
| title_short | Causal networks for climate model evaluation and constrained projections |
| title_sort | causal networks for climate model evaluation and constrained projections |
| url | https://doi.org/10.1038/s41467-020-15195-y |
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