@Article{BoersBoBaMaKuMa:2014:PrExFl,
               author = "Boers, N. and Bookhagen, B. and Barbosa, H. M. J. and Marwan, N. 
                         and Kurths, J. and Marengo, Jos{\'e} Antonio",
          affiliation = "Department of Physics, Humboldt University / Potsdam Institute for 
                         Climate Impact Research, PO and Department of Geography, 
                         University of California and Institute of Physics, University of 
                         S{\~a}o Paulo and Potsdam Institute for Climate Impact Research, 
                         PO and Department of Physics, Humboldt University / Potsdam 
                         Institute for Climate Impact Research, PO / Department of Control 
                         Theory, Nizhny Novgorod State University / Institute for Complex 
                         Systems and Mathematical Biology, University of Aberdeen and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Prediction of extreme floods in the eastern Central Andes based on 
                         a complex networks approach",
              journal = "Nature Communications",
                 year = "2014",
               volume = "5",
                pages = "5199",
                month = "oct. 2014",
             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 Nino 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.",
                  doi = "10.1038/ncomms6199",
                  url = "http://dx.doi.org/10.1038/ncomms6199",
                 issn = "2041-1723",
                label = "lattes: 5719239270509869 6 BoersBoBaMaKuMa:2014:PrExFl",
             language = "en",
           targetfile = "ncomms6199.pdf",
        urlaccessdate = "27 abr. 2024"
}