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Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks

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Abstract

We present a detailed analysis of summer monsoon rainfall over the Indian peninsular using nonlinear spatial correlations. This analysis is carried out employing the tools of complex networks and a measure of nonlinear correlation for point processes such as rainfall, called event synchronization. This study provides valuable insights into the spatial organization, scales, and structure of the 90th and 94th percentile rainfall events during the Indian summer monsoon (June–September). We furthermore analyse the influence of different critical synoptic atmospheric systems and the impact of the steep Himalayan topography on rainfall patterns. The presented method not only helps us in visualising the structure of the extreme-event rainfall fields, but also identifies the water vapor pathways and decadal-scale moisture sinks over the region. Furthermore a simple scheme based on complex networks is presented to decipher the spatial intricacies and temporal evolution of monsoonal rainfall patterns over the last 6 decades.

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Acknowledgments

This work is supported by a doctoral scholarship from the DFG Graduate School 1364. The authors thank Dr. Yong Zou, Jonathan F. Donges and Arghya Mondal for helpful discussion.

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Authors and Affiliations

  1. Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412, Potsdam, Germany

    Nishant Malik, Norbert Marwan & Jürgen Kurths

  2. Institute of Physics, University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476, Potsdam-Golm, Germany

    Nishant Malik

  3. Department of Geography, University of California Santa Barbara, 1832 Ellison Hall, Santa Barbara, CA, 93106-4060, USA

    Bodo Bookhagen

  4. Department of Physics, Humboldt University, Newtonstr. 15, 12489, Berlin, Germany

    Jürgen Kurths

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  1. Nishant Malik
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Correspondence to Nishant Malik.

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Malik, N., Bookhagen, B., Marwan, N. et al. Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks. Clim Dyn 39, 971–987 (2012). https://doi.org/10.1007/s00382-011-1156-4

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  • DOI: https://doi.org/10.1007/s00382-011-1156-4

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