Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations
Abstract Improving predictions of decadal climate variability is critical for reducing uncertainty in near‐term climate change. Here we investigate the potential to improve prediction skill in the North Pacific by identifying predictable patterns of sea surface temperatures (SSTs) in climate simulat...
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| Format: | Article |
| Language: | English |
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Wiley
2025-03-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2024GL112729 |
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| author | Emily M. Gordon Noah S. Diffenbaugh |
| author_facet | Emily M. Gordon Noah S. Diffenbaugh |
| author_sort | Emily M. Gordon |
| collection | DOAJ |
| description | Abstract Improving predictions of decadal climate variability is critical for reducing uncertainty in near‐term climate change. Here we investigate the potential to improve prediction skill in the North Pacific by identifying predictable patterns of sea surface temperatures (SSTs) in climate simulations, and then applying them to observations. A convolutional neural network (CNN) is first trained to predict basin‐wide SSTs in the North Pacific on 1–5 year time‐scales in nine global climate models (GCMs), and a pattern of high skill is identified from the GCM data. This pattern of high skill learned from GCMs is then skillfully predicted by the CNN when given observations as inputs. The identified pattern is notably not the Pacific Decadal Oscillation, and instead corresponds to basinwide warming and cooling focused in the North Pacific Gyre. We conclude that investigating the mechanisms that contribute to predictability (rather than variability) is an effective avenue for improving near‐term climate predictions. |
| format | Article |
| id | doaj-art-9546a5f5ee344cf5bca62e32e598becf |
| institution | DOAJ |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-9546a5f5ee344cf5bca62e32e598becf2025-08-20T02:57:17ZengWileyGeophysical Research Letters0094-82761944-80072025-03-01525n/an/a10.1029/2024GL112729Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical ObservationsEmily M. Gordon0Noah S. Diffenbaugh1Doerr School of Sustainability Stanford University Stanford CA USADoerr School of Sustainability Stanford University Stanford CA USAAbstract Improving predictions of decadal climate variability is critical for reducing uncertainty in near‐term climate change. Here we investigate the potential to improve prediction skill in the North Pacific by identifying predictable patterns of sea surface temperatures (SSTs) in climate simulations, and then applying them to observations. A convolutional neural network (CNN) is first trained to predict basin‐wide SSTs in the North Pacific on 1–5 year time‐scales in nine global climate models (GCMs), and a pattern of high skill is identified from the GCM data. This pattern of high skill learned from GCMs is then skillfully predicted by the CNN when given observations as inputs. The identified pattern is notably not the Pacific Decadal Oscillation, and instead corresponds to basinwide warming and cooling focused in the North Pacific Gyre. We conclude that investigating the mechanisms that contribute to predictability (rather than variability) is an effective avenue for improving near‐term climate predictions.https://doi.org/10.1029/2024GL112729decadal predictionmachine learningclimate variability and changepattern recognition |
| spellingShingle | Emily M. Gordon Noah S. Diffenbaugh Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations Geophysical Research Letters decadal prediction machine learning climate variability and change pattern recognition |
| title | Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations |
| title_full | Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations |
| title_fullStr | Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations |
| title_full_unstemmed | Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations |
| title_short | Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations |
| title_sort | identifying a pattern of predictable decadal north pacific sst variability in historical observations |
| topic | decadal prediction machine learning climate variability and change pattern recognition |
| url | https://doi.org/10.1029/2024GL112729 |
| work_keys_str_mv | AT emilymgordon identifyingapatternofpredictabledecadalnorthpacificsstvariabilityinhistoricalobservations AT noahsdiffenbaugh identifyingapatternofpredictabledecadalnorthpacificsstvariabilityinhistoricalobservations |