Network-based forecasting of climate phenomena

Network theory, as emerging from complex systems science, can provide critical predictive power for mitigating the global warming crisis and other societal challenges. Here we discuss the main differences of this approach to classical numerical modeling and highlight several cases where the network...

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Published in:Proceedings of the National Academy of Sciences - PNAS 2021-11, Vol.118 (47), p.1-10
Main Authors: Ludescher, Josef, Martin, Maria, Boers, Niklas, Bunde, Armin, Ciemer, Catrin, Fan, Jingfang, Havlin, Shlomo, Kretschmer, Marlene, Kurths, Jürgen, Runge, Jakob, Stolbova, Veronika, Surovyatkina, Elena, Schellnhuber, Hans Joachim
Format: Article
Language:English
Subjects:
Climate change
Complex systems
Drought
El Nino
Extreme weather
Global warming
Mathematical models
PERSPECTIVE
Physical Sciences
Polar vortex
Rainfall
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cited_by cdi_FETCH-LOGICAL-c443t-f6c650c29084ce30b47ec41609844231c0fe8b996f6bba9689042f80e8f900973
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container_title Proceedings of the National Academy of Sciences - PNAS
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creator Ludescher, Josef
Martin, Maria
Boers, Niklas
Bunde, Armin
Ciemer, Catrin
Fan, Jingfang
Havlin, Shlomo
Kretschmer, Marlene
Kurths, Jürgen
Runge, Jakob
Stolbova, Veronika
Surovyatkina, Elena
Schellnhuber, Hans Joachim
description Network theory, as emerging from complex systems science, can provide critical predictive power for mitigating the global warming crisis and other societal challenges. Here we discuss the main differences of this approach to classical numerical modeling and highlight several cases where the network approach substantially improved the prediction of high-impact phenomena: 1) El Niño events, 2) droughts in the central Amazon, 3) extreme rainfall in the eastern Central Andes, 4) the Indian summer monsoon, and 5) extreme stratospheric polar vortex states that influence the occurrence of wintertime cold spells in northern Eurasia. In this perspective, we argue that network-based approaches can gainfully complement numerical modeling.
doi_str_mv 10.1073/pnas.1922872118
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subjects Climate change
Complex systems
Drought
El Nino
Extreme weather
Global warming
Mathematical models
PERSPECTIVE
Physical Sciences
Polar vortex
Rainfall
title Network-based forecasting of climate phenomena
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