TY - JOUR A1 - Goswami, Bedartha A1 - Shekatkar, Snehal M. A1 - Rheinwalt, Aljoscha A1 - Ambika, G. A1 - Kurths, Jürgen T1 - A random interacting network model for complex networks JF - Scientific reports N2 - We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems. Y1 - 2015 U6 - https://doi.org/10.1038/srep18183 SN - 2045-2322 VL - 5 PB - Nature Publ. Group CY - London ER - TY - JOUR A1 - Boers, Niklas A1 - Barbosa, Henrique M. J. A1 - Bookhagen, Bodo A1 - Marengo, Jose A. A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Propagation of Strong Rainfall Events from Southeastern South America to the Central Andes JF - Journal of climate N2 - Based on high-spatiotemporal-resolution data, the authors perform a climatological study of strong rainfall events propagating from southeastern South America to the eastern slopes of the central Andes during the monsoon season. These events account for up to 70% of total seasonal rainfall in these areas. They are of societal relevance because of associated natural hazards in the form of floods and landslides, and they form an intriguing climatic phenomenon, because they propagate against the direction of the low-level moisture flow from the tropics. The responsible synoptic mechanism is analyzed using suitable composites of the relevant atmospheric variables with high temporal resolution. The results suggest that the low-level inflow from the tropics, while important for maintaining sufficient moisture in the area of rainfall, does not initiate the formation of rainfall clusters. Instead, alternating low and high pressure anomalies in midlatitudes, which are associated with an eastward-moving Rossby wave train, in combination with the northwestern Argentinean low, create favorable pressure and wind conditions for frontogenesis and subsequent precipitation events propagating from southeastern South America toward the Bolivian Andes. KW - Cold air surges KW - Extreme events KW - Precipitation KW - Subtropical cyclones KW - Convective storms KW - Mesoscale systems Y1 - 2015 U6 - https://doi.org/10.1175/JCLI-D-15-0137.1 SN - 0894-8755 SN - 1520-0442 VL - 28 IS - 19 SP - 7641 EP - 7658 PB - American Meteorological Soc. CY - Boston ER - TY - JOUR A1 - Boers, Niklas A1 - Bookhagen, Bodo A1 - Marengo, Jose A1 - Marwan, Norbert A1 - von Storch, Jin-Song A1 - Kurths, Jürgen T1 - Extreme Rainfall of the South American Monsoon System: A Dataset Comparison Using Complex Networks JF - Journal of climate N2 - In this study, the authors compare six different rainfall datasets for South America with a focus on their representation of extreme rainfall during the monsoon season (December February): the gauge-calibrated TRMM 3B42 V7 satellite product; the near-real-time TRMM 3B42 V7 RT, the GPCP 1 degrees daily (1DD) V1.2 satellite gauge combination product, the Interim ECMWF Re-Analysis (ERA-Interim) product; output of a high-spatial-resolution run of the ECHAM6 global circulation model; and output of the regional climate model Eta. For the latter three, this study can be understood as a model evaluation. In addition to statistical values of local rainfall distributions, the authors focus on the spatial characteristics of extreme rainfall covariability. Since traditional approaches based on principal component analysis are not applicable in the context of extreme events, they apply and further develop methods based on complex network theory. This way, the authors uncover substantial differences in extreme rainfall patterns between the different datasets: (i) The three model-derived datasets yield very different results than the satellite gauge combinations regarding the main climatological propagation pathways of extreme events as well as the main convergence zones of the monsoon system. (ii) Large discrepancies are found for the development of mesoscale convective systems in southeastern South America. (iii) Both TRMM datasets and ECHAM6 indicate a linkage of extreme rainfall events between the central Amazon basin and the eastern slopes of the central Andes, but this pattern is not reproduced by the remaining datasets. The authors' study suggests that none of the three model-derived datasets adequately captures extreme rainfall patterns in South America. Y1 - 2015 U6 - https://doi.org/10.1175/JCLI-D-14-00340.1 SN - 0894-8755 SN - 1520-0442 VL - 28 IS - 3 SP - 1031 EP - 1056 PB - American Meteorological Soc. CY - Boston ER -