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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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???ViewItemFull_lblCiteItemAs???: https://publications.pik-potsdam.de/pubman/item/item_34029 ???ViewItemFull_lblCiteItemVersionAs???: https://publications.pik-potsdam.de/pubman/item/item_34029_1
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Ludescher_Chaos_ms.pdf (???ENUM_CONTENTCATEGORY_any-fulltext???), 1012???ViewItemMedium_lblFileSizeKB???
 
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Ludescher_Chaos_ms.pdf
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 ???ViewItemFull_lblCreators???:
Ludescher, Josef1, ???ENUM_CREATORROLE_AUTHOR???           
Meng, Jun2, ???ENUM_CREATORROLE_AUTHOR???
Fan , Jingfang2, ???ENUM_CREATORROLE_AUTHOR???
Bunde, Armin2, ???ENUM_CREATORROLE_AUTHOR???
Schellnhuber, Hans Joachim2, ???ENUM_CREATORROLE_AUTHOR???
???ViewItemFull_lblAffiliations???:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 ???ViewItemFull_lblAbstract???: 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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???ViewItemFull_lblLanguages???: eng - English
 ???ViewItemFull_lblDates???: 2026-02-01
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: RD1 - Earth System Analysis
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD1 - Earth System Analysis
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: Lab - Planetary Boundaries Science
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Complex Networks
???ENUM_IDENTIFIERTYPE_REGIONALK???: Global
???ENUM_IDENTIFIERTYPE_MODELMETHOD???: Nonlinear Data Analysis
???ENUM_IDENTIFIERTYPE_MODELMETHOD???: Quantitative Methods
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???ViewItemFull_lblSourceTitle???: Chaos
???ViewItemFull_lblSourceGenre???: ???ENUM_GENRE_JOURNAL???, SCI, Scopus, p3
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???ENUM_IDENTIFIERTYPE_PUBLISHER???: American Institute of Physics (AIP)