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Earth System Dynamics An interactive open-access journal of the European Geosciences Union

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doi:10.5194/esd-2017-12
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
14 Feb 2017
Review status
This discussion paper is under review for the journal Earth System Dynamics (ESD).
Classification of mechanisms, Climatic Context, Areal Scaling, and Synchronization of floods: the hydroclimatology of floods in the Upper Paraná River Basin, Brazil
Carlos Lima1, Amir AghaKouchak2, and Upmanu Lall3 1Civil and Environmental Engineering, University of Brasil ia, Brasilia, Distrito Federal, Brazil
2Civil and Environmental Engineering, University of Califo rnia, Irvine, Irvine, California United States
3Earth and Environmental Engineering, Columbia University , New York, New York, United States
Abstract. 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.

Citation: Lima, C., AghaKouchak, A., and Lall, U.: Classification of mechanisms, Climatic Context, Areal Scaling, and Synchronization of floods: the hydroclimatology of floods in the Upper Paraná River Basin, Brazil, Earth Syst. Dynam. Discuss., doi:10.5194/esd-2017-12, in review, 2017.
Carlos Lima et al.
Carlos Lima et al.
Carlos Lima et al.

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Short summary
Flood is the main natural disaster in Brazil, causing substantial economic damage and losses of lives. Here we seek to better understand the flood generating mechanisms in the flood prone Parana River Basin, including large scale patterns of the ocean and atmospheric circulation. This study provides new insights for understanding causes of floods in the region and around the world and are a step forward to improve flood risk management, statistical assessments and short-term flood forecasts.
Flood is the main natural disaster in Brazil, causing substantial economic damage and losses of...
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