Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance
Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity...
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| Format: | Article |
| Language: | English |
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Wiley
2024-07-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2024GL109179 |
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| author | Jakob Schlör Felix Strnad Antonietta Capotondi Bedartha Goswami |
| author_facet | Jakob Schlör Felix Strnad Antonietta Capotondi Bedartha Goswami |
| author_sort | Jakob Schlör |
| collection | DOAJ |
| description | Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events. |
| format | Article |
| id | doaj-art-2ceca7b7a3b2427aa913313e4dd3a53c |
| institution | Kabale University |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-2ceca7b7a3b2427aa913313e4dd3a53c2025-08-20T03:49:46ZengWileyGeophysical Research Letters0094-82761944-80072024-07-015114n/an/a10.1029/2024GL109179Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO VarianceJakob Schlör0Felix Strnad1Antonietta Capotondi2Bedartha Goswami3Machine Learning in Climate Science University of Tübingen Tübingen GermanyMachine Learning in Climate Science University of Tübingen Tübingen GermanyCooperative Institute for Research in Environmental Sciences University of Colorado Boulder CO USAMachine Learning in Climate Science University of Tübingen Tübingen GermanyAbstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events.https://doi.org/10.1029/2024GL109179El Niño Southern Oscillationdecadal variabilityunsupervised clusteringmachine learning |
| spellingShingle | Jakob Schlör Felix Strnad Antonietta Capotondi Bedartha Goswami Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance Geophysical Research Letters El Niño Southern Oscillation decadal variability unsupervised clustering machine learning |
| title | Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance |
| title_full | Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance |
| title_fullStr | Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance |
| title_full_unstemmed | Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance |
| title_short | Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance |
| title_sort | contribution of el nino southern oscillation enso diversity to low frequency changes in enso variance |
| topic | El Niño Southern Oscillation decadal variability unsupervised clustering machine learning |
| url | https://doi.org/10.1029/2024GL109179 |
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