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, J A Marengo

Research output: Contribution to journalArticle

73 Citations (Scopus)

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.
Original languageEnglish
Article number5199
JournalNature Communications
Volume5
DOIs
Publication statusPublished - 14 Oct 2014

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South America
Complex networks
Ecology
Rain
Hazards
predictions
Population
hazards
ecology
Synchronization
economy
linkages
Satellites
synchronism
divergence

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Boers, N., Bookhagen, B., Barbosa, H. M. J., Marwan, N., Kurths, J., & Marengo, J. A. (2014). Prediction of extreme floods in the eastern Central Andes based on a complex networks approach. Nature Communications, 5, [5199]. https://doi.org/10.1038/ncomms6199

Prediction of extreme floods in the eastern Central Andes based on a complex networks approach. / Boers, N; Bookhagen, B; Barbosa, H M J; Marwan, N; Kurths, J; Marengo, J A .

In: Nature Communications, Vol. 5, 5199, 14.10.2014.

Research output: Contribution to journalArticle

Boers, N ; Bookhagen, B ; Barbosa, H M J ; Marwan, N ; Kurths, J ; Marengo, J A . / Prediction of extreme floods in the eastern Central Andes based on a complex networks approach. In: Nature Communications. 2014 ; Vol. 5.
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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 Ni{\~n}o 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.",
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N1 - This paper was developed within the scope of the IRTG 1740/TRP 2011/50151-0, funded by the DFG/FAPESP. H.M.J.B. was supported by FAPESP project 2013/50510-5 and CNPq project 478314/2012-4. N.M. was supported by the DFG project MA 4759/4-1. J.K. acknowledges financial support from the Government of the Russian Federation (Agreement No. 14.Z50.31.0033). J.A.M. was supported by the Rede-CLIMA, the National Institute of Science and Technology (INCT) for Climate Change funded by CNPq Grant Number 573797/2008-0, the FAPESP project 57719-9, the FAPESPAssessment of Impacts and Vulnerability to Climate Change in Brazil and strategies for Adaptation Options Project (Grant Number 2008/58161-1) and the FAPESP project Go Amazon 2013/50538-7. We thank Leila Carvalho, Gonzalo Ramirez Avila, Rodrigo Bombardi, Bedartha Goswami, Charles Jones, and Aljoscha Rheinwalt for stimulating discussions and comments.

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N2 - 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.

AB - 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.

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