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Lima, Carlos; AghaKouchak, Amir; Lall, Upmanu (2017)
Publisher: Copernicus Publications
Languages: English
Types: Article
Subjects: Q, QE500-639.5, Dynamic and structural geology, Science, QE1-996.5, Geology
Flood is the main natural disaster in Brazil, causing substantial economic damage and losses of lives. Recent studies suggest that some extreme floods in different parts of the world do not appear as random as they are represented in traditional flood frequency analysis (FFA), but result from a causal chain, where exceptional rain and floods in basins from different sizes are related with large scale anomalies and persistent patterns in the atmospheric and oceanic circulations. Moreover, floods result from different generating mechanisms or are subject to temporal changes in the forcing mechanisms and surface conditions, which violates the common homogeneity and stationary assumptions in FFA. An Eulerian-Lagrangian model of ocean-atmosphere circulation would ideally be needed to test a causal chain hypothesis. However, some progress may be possible through empirical data analysis. Here we seek to advance the traditional statistical flood analysis, through understanding the flood generating mechanisms including large scale patterns of the ocean and atmospheric circulation. We outline a methodological framework based on the Self-Organizing Map (SOM) clustering that allows linking large scale processes to local scale observations. The proposed methodology is applied to flood data from several sites in the flood prone Upper Parana River Basin (UPRB) in southern Brazil. The SOM clustering approach is employed to classify the six-day rainfall field over UPRB into four categories, which are then used to classify floods into four types based on the spatio-temporal dynamics of the rainfall field prior to the observed flood events. An analysis of the vertically integrated moisture fluxes, vorticity and high level atmospheric circulation revealed that these four clusters are related to tropical and extra-tropical processes, including the South America low-level jet (SALLJ), extra-tropical cyclones and the South Atlantic Convergence Zone (SACZ). Persistent anomalies in the sea surface temperature fields in the Pacific and Atlantic oceans are also found to be associated with these processes. Floods associated with each cluster present different patterns in terms of frequency, magnitude, spatial variability, scaling and synchronization of events across the sites and subbasins. These findings and the methodological framework proposed in this study provide new insights for understanding causes of floods around the world and are a step forward to improve flood risk management, interpreting statistical assessments and short-term flood forecasting.
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