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  Predicting ENSO dynamics with network & complexity analyses

Ludescher, J., Meng, J., Fan, J., Bunde, A., Schellnhuber, H. J. (in press): Predicting ENSO dynamics with network & complexity analyses. - Chaos.

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_34029 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_34029_1
Genre: Journal Article

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Ludescher_Chaos_ms.pdf (Any fulltext), 1012KB
 
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 Creators:
Ludescher, Josef1, Author           
Meng, Jun2, Author
Fan , Jingfang2, Author
Bunde, Armin2, Author
Schellnhuber, Hans Joachim2, Author
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Abstract: The El Niño Southern Oscillation (ENSO) consists of El Niño, La Niña and neutral events. Recently, we have developed two approaches (a climate network and a complexity-based approach) that allow forecasting the onset of El Niño events about 1 year in advance. The complexity-based approach additionally enables forecasting the magnitude of an upcoming El Niño event. Here, we propose the interannual relationship of the Oceanic Niño Index as an additional predictor for forecasting La Niña and neutral events. Combining the three approaches therefore enables probabilistic forecasting of all three phases of ENSO dynamics. Based on these approaches, in December 2024 we correctly forecasted the absence of an El Niño in 2025 (with 91.4% probability) and a resulting temporary decrease in the global mean temperature. With 69.6% probability, we predicted a neutral event as the most likely outcome.

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Language(s): eng - English
 Dates: 2026-02-01
 Publication Status: Accepted / In Press
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: PIKDOMAIN: RD1 - Earth System Analysis
Organisational keyword: RD1 - Earth System Analysis
Organisational keyword: Lab - Planetary Boundaries Science
Research topic keyword: Complex Networks
Regional keyword: Global
Model / method: Nonlinear Data Analysis
Model / method: Quantitative Methods
MDB-ID: No data to archive
 Degree: -

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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)