Journal article

Publication year: 2021

Journal: Proceedings of the National Academy of Sciences

Volume number: 118

Issue number: 47

ISSN: 0027-8424

eISSN: 1091-6490

Open access status: Green

DOI Link: https://doi.org/10.1073/pnas.1922872118

Publisher: National Academy of Sciences

Abstract: 
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 Nino 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.

Harvard Citation style: Ludescher, J., Martin, M., Boers, N., Bunde, A., Ciemer, C., Fan, J., et al. (2021) Network-based forecasting of climate phenomena, Proceedings of the National Academy of Sciences, 118(47), Article e1922872118. https://doi.org/10.1073/pnas.1922872118

APA Citation style: Ludescher, J., Martin, M., Boers, N., Bunde, A., Ciemer, C., Fan, J., Havlin, S., Kretschmer, M., Kurths, J., Runge, J., Stolbova, V., Surovyatkina, E., & Schellnhuber, H. (2021). Network-based forecasting of climate phenomena. Proceedings of the National Academy of Sciences. 118(47), Article e1922872118. https://doi.org/10.1073/pnas.1922872118