@article{MalikBookhagenMarwanetal.2012,
  author    = {Malik, Nishant and Bookhagen, Bodo and Marwan, Norbert and Kurths, J{\"u}rgen},
  title     = {Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks},
  series = {Climate dynamics : observational, theoretical and computational research on the climate system},
  volume    = {39},
  journal   = {Climate dynamics : observational, theoretical and computational research on the climate system},
  number    = {3-4},
  publisher = {Springer},
  address   = {New York},
  issn      = {0930-7575},
  doi       = {10.1007/s00382-011-1156-4},
  pages     = {971 -- 987},
  year      = {2012},
  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.},
  language  = {en}
}
@article{OzturkMalikCheungetal.2019,
  author    = {Ozturk, Ugur and Malik, Nishant and Cheung, Kevin and Marwan, Norbert and Kurths, J{\"u}rgen},
  title     = {A network-based comparative study of extreme tropical and frontal storm rainfall over Japan},
  series = {Climate dynamics : observational, theoretical and computational research on the climate system},
  volume    = {53},
  journal   = {Climate dynamics : observational, theoretical and computational research on the climate system},
  number    = {1-2},
  publisher = {Springer},
  address   = {New York},
  issn      = {0930-7575},
  doi       = {10.1007/s00382-018-4597-1},
  pages     = {521 -- 532},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}