Prediction of extreme floods in the eastern Central Andes based on a complex networks approach

• Published in: Nature communications Vol. 5; no. 1; p. 5199
• Main Authors: Boers, N., Bookhagen, B., Barbosa, H. M. J., Marwan, N., Kurths, J., Marengo, J. A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.10.2014; Nature Publishing Group
• Subjects: 704/106/35; 704/106/694/2786; Humanities and Social Sciences; multidisciplinary; Science; Science (multidisciplinary)
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms6199

Changing climatic conditions have led to a significant increase in the magnitude and frequency of extreme rainfall events in the Central Andes of South America. These events are spatially extensive and often result in substantial natural hazards for population, economy and ecology. Here we develop a general framework to predict extreme events by introducing the concept of network divergence on directed networks derived from a non-linear synchronization measure. We apply our method to real-time satellite-derived rainfall data and predict more than 60% (90% during El Niño conditions) of rainfall events above the 99th percentile in the Central Andes. In addition to the societal benefits of predicting natural hazards, our study reveals a linkage between polar and tropical regimes as the responsible mechanism: the interplay of northward migrating frontal systems and a low-level wind channel from the western Amazon to the subtropics. Extreme rainfall events in the eastern Central Andes can result in substantial economic and ecological damage, yet their prediction is difficult. Here, the authors introduce the concept of network divergence and propose a general framework for the prediction of extreme events.