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

N. Boers (), B. Bookhagen, H. M. J. Barbosa, N. Marwan, J. Kurths and J. A. Marengo
Additional contact information
N. Boers: Humboldt University
B. Bookhagen: University of California
H. M. J. Barbosa: Institute of Physics, University of São Paulo, Rua do Matao
N. Marwan: Potsdam Institute for Climate Impact Research
J. Kurths: Humboldt University
J. A. Marengo: CCST INPE, Rodovia Presidente Dutra Km 39, Cachoeira Paulista

Nature Communications, 2014, vol. 5, issue 1, 1-7

Abstract: Abstract 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.

Date: 2014
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DOI: 10.1038/ncomms6199

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