TY - JOUR A1 - Ozturk, Ugur A1 - Malik, Nishant A1 - Cheung, Kevin A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - A network-based comparative study of extreme tropical and frontal storm rainfall over Japan JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - 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. KW - Extreme rainfall KW - Baiu KW - Tropical storms KW - Event synchronization KW - Complex networks Y1 - 2019 U6 - https://doi.org/10.1007/s00382-018-4597-1 SN - 0930-7575 SN - 1432-0894 VL - 53 IS - 1-2 SP - 521 EP - 532 PB - Springer CY - New York ER - TY - JOUR A1 - Goswami, Bedartha A1 - Boers, Niklas A1 - Rheinwalt, Aljoscha A1 - Marwan, Norbert A1 - Heitzig, Jobst A1 - Breitenbach, Sebastian Franz Martin A1 - Kurths, Jürgen T1 - Abrupt transitions in time series with uncertainties JF - Nature Communications N2 - Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an ‘uncertainty-aware’ framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon. Y1 - 2018 U6 - https://doi.org/10.1038/s41467-017-02456-6 SN - 2041-1723 VL - 9 PB - Nature Publ. Group CY - London ER - TY - JOUR A1 - Malik, Nishant A1 - Bookhagen, Bodo A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - 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. KW - Indian summer monsoon KW - Event synchronization KW - Complex networks KW - Rainfall patterns Y1 - 2012 U6 - https://doi.org/10.1007/s00382-011-1156-4 SN - 0930-7575 VL - 39 IS - 3-4 SP - 971 EP - 987 PB - Springer CY - New York ER - TY - JOUR A1 - Schinkel, Stefan A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Brain signal analysis based on recurrences N2 - The EEG is one of the most commonly used tools in brain research. Though of high relevance in research, the data obtained is very noisy and nonstationary. In the present article we investigate the applicability of a nonlinear data analysis method, the recurrence quantification analysis (RQA), to Such data. The method solely rests on the natural property of recurrence which is a phenomenon inherent to complex systems, such as the brain. We show that this method is indeed suitable for the analysis of EEG data and that it might improve contemporary EEG analysis. Y1 - 2009 UR - http://www.sciencedirect.com/science/journal/09284257 U6 - https://doi.org/10.1016/j.jphysparis.2009.05.007 SN - 0928-4257 ER - TY - JOUR A1 - Marwan, Norbert A1 - Trauth, Martin H. A1 - Schwarz, Udo A1 - Kurths, Jürgen A1 - Strecker, Manfred T1 - Climate dynamics of varved pleistocene lake sediments in nw Argentina Y1 - 1999 SN - 1029-7006 ER - TY - JOUR A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Comment on "Stochastic analysis of recurrence plots with applications to the detection of deterministic signals" by Rohde et al. : [Physica D 237 (2008) 619-629] N2 - In the recent article "Stochastic analysis of recurrence plots with applications to the detection of deterministic signals" (Physica D 237 (2008) 619-629), Rohde et al. stated that the performance of RQA in order to detect deterministic signals would be below traditional and well-known detectors. However, we have concerns about such a general statement. Based on our own studies we cannot confirm their conclusions. Our findings suggest that the measures of complexity provided by RQA are useful detectors outperforming well-known traditional detectors, in particular for the detection of signals of complex systems, with phase differences or signals modified due to the measurement process. Y1 - 2009 UR - http://www.sciencedirect.com/science/journal/01672789 U6 - https://doi.org/10.1016/j.physd.2009.04.018 SN - 0167-2789 ER - TY - JOUR A1 - Marwan, Norbert A1 - Trauth, Martin H. A1 - Vuille, Mathias A1 - Kurths, Jürgen T1 - Comparing modern and Pleistocene ENSO-like influences in NW Argentina using nonlinear time series analysis methods N2 - Higher variability in rainfall and river discharge could be of major importance in landslide generation in the north-western Argentine Andes. Annual layered (varved) deposits of a landslide dammed lake in the Santa Maria Basin (26°S, 66°W) with an age of 30,000 14C years provide an archive of precipitation variability during this time. The comparison of these data with present-day rainfall observations tests the hypothesis that increased rainfall variability played a major role in landslide generation. A potential cause of such variability is the El Niño/ Southern Oscillation (ENSO). The causal link between ENSO and local rainfall is quantified by using a new method of nonlinear data analysis, the quantitative analysis of cross recurrence plots (CRP). This method seeks similarities in the dynamics of two different processes, such as an ocean-atmosphere oscillation and local rainfall. Our analysis reveals significant similarities in the statistics of both modern and palaeo-precipitation data. The similarities in the data suggest that an ENSO-like influence on local rainfall was present at around 30,000 14C years ago. Increased rainfall, which was inferred from a lake balance modeling in a previous study, together with ENSO-like cyclicities could help to explain the clustering of landslides at around 30,000 14C years ago. Y1 - 2003 UR - http://arxiv.org/abs/nlin.CD/0303056 ER - TY - JOUR A1 - Ozturk, Ugur A1 - Marwan, Norbert A1 - Korup, Oliver A1 - Saito, H. A1 - Agarwa, Ankit A1 - Grossman, M. J. A1 - Zaiki, M. A1 - Kurths, Jürgen T1 - Complex networks for tracking extreme rainfall during typhoons JF - Chaos : an interdisciplinary journal of nonlinear science N2 - Reconciling the paths of extreme rainfall with those of typhoons remains difficult despite advanced forecasting techniques. We use complex networks defined by a nonlinear synchronization measure termed event synchronization to track extreme rainfall over the Japanese islands. Directed networks objectively record patterns of heavy rain brought by frontal storms and typhoons but mask out contributions of local convective storms. We propose a radial rank method to show that paths of extreme rainfall in the typhoon season (August-November, ASON) follow the overall southwest-northeast motion of typhoons and mean rainfall gradient of Japan. The associated eye-of-the-typhoon tracks deviate notably and may thus distort estimates of heavy typhoon rainfall. We mainly found that the lower spread of rainfall tracks in ASON may enable better hindcasting than for westerly-fed frontal storms in June and July. Y1 - 2018 U6 - https://doi.org/10.1063/1.5004480 SN - 1054-1500 SN - 1089-7682 VL - 28 IS - 7 PB - American Institute of Physics CY - Melville ER - TY - JOUR A1 - Donges, Jonathan Friedemann A1 - Zou, Yong A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Complex networks in climate dynamics : comparing linear and nonlinear network construction methods N2 - Complex network theory provides a powerful framework to statistically investigate the topology of local and non- local statistical interrelationships, i.e. teleconnections, in the climate system. Climate networks constructed from the same global climatological data set using the linear Pearson correlation coefficient or the nonlinear mutual information as a measure of dynamical similarity between regions, are compared systematically on local, mesoscopic and global topological scales. A high degree of similarity is observed on the local and mesoscopic topological scales for surface air temperature fields taken from AOGCM and reanalysis data sets. We find larger differences on the global scale, particularly in the betweenness centrality field. The global scale view on climate networks obtained using mutual information offers promising new perspectives for detecting network structures based on nonlinear physical processes in the climate system. Y1 - 2009 UR - http://www.springerlink.com/content/1951-6355 U6 - https://doi.org/10.1140/epjst/e2009-01098-2 SN - 1951-6355 ER - TY - JOUR A1 - Schinkel, Stefan A1 - Marwan, Norbert A1 - Dimigen, Olaf A1 - Kurths, Jürgen T1 - Confidence bounds of recurrence-based complexity measures N2 - In the recent past, recurrence quantification analysis (RQA) has gained an increasing interest in various research areas. The complexity measures the RQA provides have been useful in describing and analysing a broad range of data. It is known to be rather robust to noise and nonstationarities. Yet, one key question in empirical research concerns the confidence bounds of measured data. In the present Letter we suggest a method for estimating the confidence bounds of recurrence-based complexity measures. We study the applicability of the suggested method with model and real- life data. Y1 - 2009 UR - http://www.sciencedirect.com/science/journal/03759601 U6 - https://doi.org/10.1016/j.physleta.2009.04.045 SN - 0375-9601 ER -