Prediction of extreme floods in the eastern Central Andes based on a complex networks approach
Prediction of extreme floods in the eastern Central Andes based on a complex networks approach
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DOI：
10.1038/ncomms6199
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发表时间：
2014-10-01
影响因子：
16.6
通讯作者：
Marengo, J. A.
中科院分区：
文献类型：
--
作者：
Boers, N.;Bookhagen, B.;Marengo, J. A.
气候条件的变化导致南美洲安第斯山脉中部极端降雨事件的强度和频率显着增加。这些事件的空间范围广泛，常常对人口、经济和生态造成重大自然灾害。在这里，我们通过引入从非线性同步测量导出的有向网络上的网络发散概念，开发了一个预测极端事件的通用框架。我们将我们的方法应用于实时卫星衍生的降雨数据，并预测安第斯山脉中部 60% 以上（厄尔尼诺条件下为 90%）的降雨事件超过 99%。除了预测自然灾害的社会效益外，我们的研究还揭示了极地和热带气候之间的联系作为负责任的机制：向北迁移的锋面系统和从亚马逊西部到亚热带的低层风道的相互作用。
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.