A network-based comparative study of extreme tropical and frontal storm rainfall over Japan

  • Ugur OzturkEmail author
  • Nishant Malik
  • Kevin Cheung
  • Norbert Marwan
  • Juergen Kurths


Frequent and intense rainfall events demand innovative techniques to better predict the extreme rainfall dynamics. This task requires essentially the assessment of the basic types of atmospheric processes that trigger extreme rainfall, and then to examine the differences between those processes, which may help to identify key patterns to improve predictive algorithms. We employ tools from network theory to compare the spatial features of extreme rainfall over the Japanese archipelago and surrounding areas caused by two atmospheric processes: the Baiu front, which occurs mainly in June and July (JJ), and the tropical storms from August to November (ASON). We infer from complex networks of satellite-derived rainfall data, which are based on the nonlinear correlation measure of event synchronization. We compare the spatial scales involved in both systems and identify different regions which receive rainfall due to the large spatial scale of the Baiu and tropical storm systems. We observed that the spatial scales involved in the Baiu driven rainfall extremes, including the synoptic processes behind the frontal development, are larger than tropical storms, which even have long tracks during extratropical transitions. We further delineate regions of coherent rainfall during the two seasons based on network communities, identifying the horizontal (east–west) rainfall bands during JJ over the Japanese archipelago, while during ASON these bands align with the island arc of Japan.


Extreme rainfall Baiu Tropical storms Event synchronization Complex networks 



We thank Ankit Agarwal, Aljoscha Rheinwalt and Bedartha Goswami for helping with some of the computations. We acknowledge Vera Ozturk for helping us in visualization. We also thank Kevin Fleming for proofreading the manuscript. Our research is funded by the Deutsche Forschungsgemeinschaft within the Research Training Group “Natural Hazards and Risks in a Changing World (NatRiskChange)” (DFG GRK 2043/1) at the University of Potsdam. Ugur Ozturk is partly funded by the Federal Ministry of Education and Research (BMBF) within the project CLIENT II-CaTeNA (FKZ 03G0878A). We are grateful to the Tropical Rainfall Measuring Mission (TRMM) for providing the data for this research (


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Earth and Environmental SciencesUniversity of PotsdamPotsdamGermany
  2. 2.Potsdam Institute for Climate Impact Research, PIKPotsdamGermany
  3. 3.Helmholtz Centre Potsdam, GFZ German Research Centre for GeosciencesPotsdamGermany
  4. 4.School of Mathematical SciencesRochester Institute of TechnologyRochesterUSA
  5. 5.Department of Environmental SciencesMacquarie UniversitySydneyAustralia
  6. 6.Department of PhysicsHumboldt UniversityBerlinGermany

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