Journal article : Letter
Multi-decadal skill variability in predicting the spatial patterns of ENSO events
- Abstract:
- Seasonal hindcasts have previously been demonstrated to show multi-decadal variability in skill across the twentieth century in indices describing El-Niño Southern Oscillation (ENSO), which drives global seasonal predictability. Here, we analyze the skill of predicting ENSO events' magnitude and spatial pattern, in the CSF-20C coupled seasonal hindcasts in 1901–2010. We find minima in the skill of predicting the first (in 1930–1950) and second (in 1940–1960) principal components of sea-surface temperature (SST) in the tropical Pacific. This minimum is also present in the spatial correlation of SSTs, in 1930–1960. The skill reduction is explained by lower ENSO magnitude and variance in 1930–1960, as well as decreased SST persistence. The SST skill minima project onto surface winds, leading to worse predictions in coupled hindcasts compared to hindcasts using prescribed SSTs. Questions remain about the offset between the first and second principal components' skill minima, and how the skill minima impact the extra-tropics.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.1MB, Terms of use)
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- Publisher copy:
- 10.1029/2023GL107971
Authors
- Publisher:
- American Geophysical Union
- Journal:
- Geophysical Research Letters More from this journal
- Volume:
- 51
- Issue:
- 12
- Article number:
- e2023GL107971
- Publication date:
- 2024-06-14
- Acceptance date:
- 2024-05-28
- DOI:
- EISSN:
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1944-8007
- ISSN:
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0094-8276
- Language:
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English
- Subtype:
-
Letter
- Pubs id:
-
2003024
- Local pid:
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pubs:2003024
- Deposit date:
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2024-06-03
Terms of use
- Copyright holder:
- Wright et al
- Copyright date:
- 2024
- Rights statement:
- © 2024. The Authors. Geophysical Research Letters published by Wiley Periodicals LLC on behalf of American Geophysical Union. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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