@article{TraxlBoersRheinwaltetal.2016, author = {Traxl, Dominik and Boers, Niklas and Rheinwalt, Aljoscha and Goswami, Bedartha and Kurths, J{\"u}rgen}, title = {The size distribution of spatiotemporal extreme rainfall clusters around the globe}, series = {Geophysical research letters}, volume = {43}, journal = {Geophysical research letters}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0094-8276}, doi = {10.1002/2016GL070692}, pages = {9939 -- 9947}, year = {2016}, abstract = {The scaling behavior of rainfall has been extensively studied both in terms of event magnitudes and in terms of spatial extents of the events. Different heavy-tailed distributions have been proposed as candidates for both instances, but statistically rigorous treatments are rare. Here we combine the domains of event magnitudes and event area sizes by a spatiotemporal integration of 3-hourly rain rates corresponding to extreme events derived from the quasi-global high-resolution rainfall product Tropical Rainfall Measuring Mission 3B42. A maximum likelihood evaluation reveals that the distribution of spatiotemporally integrated extreme rainfall cluster sizes over the oceans is best described by a truncated power law, calling into question previous statements about scale-free distributions. The observed subpower law behavior of the distribution's tail is evaluated with a simple generative model, which indicates that the exponential truncation of an otherwise scale-free spatiotemporal cluster size distribution over the oceans could be explained by the existence of land masses on the globe.}, language = {en} } @article{StolbovaSurovyatkinaBookhagenetal.2016, author = {Stolbova, Veronika and Surovyatkina, Elena and Bookhagen, Bodo and Kurths, J{\"u}rgen}, title = {Tipping elements of the Indian monsoon: Prediction of onset and withdrawal}, series = {Geophysical research letters}, volume = {43}, journal = {Geophysical research letters}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0094-8276}, doi = {10.1002/2016GL068392}, pages = {3982 -- 3990}, year = {2016}, abstract = {Forecasting the onset and withdrawal of the Indian summer monsoon is crucial for the life and prosperity of more than one billion inhabitants of the Indian subcontinent. However, accurate prediction of monsoon timing remains a challenge, despite numerous efforts. Here we present a method for prediction of monsoon timing based on a critical transition precursor. We identify geographic regions-tipping elements of the monsoon-and use them as observation locations for predicting onset and withdrawal dates. Unlike most predictability methods, our approach does not rely on precipitation analysis but on air temperature and relative humidity, which are well represented both in models and observations. The proposed method allows to predict onset 2 weeks earlier and withdrawal dates 1.5 months earlier than existing methods. In addition, it enables to correctly forecast monsoon duration for some anomalous years, often associated with El Nino-Southern Oscillation.}, language = {en} } @article{StolbovaMartinBookhagenetal.2014, author = {Stolbova, Veronika and Martin, P. and Bookhagen, Bodo and Marwan, Norbert and Kurths, J{\"u}rgen}, title = {Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka}, series = {Nonlinear processes in geophysics}, volume = {21}, journal = {Nonlinear processes in geophysics}, number = {4}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1023-5809}, doi = {10.5194/npg-21-901-2014}, pages = {901 -- 917}, year = {2014}, abstract = {This paper employs a complex network approach to determine the topology and evolution of the network of extreme precipitation that governs the organization of extreme rainfall before, during, and after the Indian Summer Monsoon (ISM) season. We construct networks of extreme rainfall events during the ISM (June-September), post-monsoon (October-December), and pre-monsoon (March-May) periods from satellite-derived (Tropical Rainfall Measurement Mission, TRMM) and rain-gauge interpolated (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE) data sets. The structure of the networks is determined by the level of synchronization of extreme rainfall events between different grid cells throughout the Indian subcontinent. Through the analysis of various complex-network metrics, we describe typical repetitive patterns in North Pakistan (NP), the Eastern Ghats (EG), and the Tibetan Plateau (TP). These patterns appear during the pre-monsoon season, evolve during the ISM, and disappear during the post-monsoon season. These are important meteorological features that need further attention and that may be useful in ISM timing and strength prediction.}, language = {en} } @article{RheinwaltBoersMarwanetal.2016, author = {Rheinwalt, Aljoscha and Boers, Niklas and Marwan, Norbert and Kurths, J{\"u}rgen and Hoffmann, Peter and Gerstengarbe, Friedrich-Wilhelm and Werner, Peter}, title = {Non-linear time series analysis of precipitation events using regional climate networks for Germany}, series = {Climate dynamics : observational, theoretical and computational research on the climate system}, volume = {46}, journal = {Climate dynamics : observational, theoretical and computational research on the climate system}, publisher = {Springer}, address = {New York}, issn = {0930-7575}, doi = {10.1007/s00382-015-2632-z}, pages = {1065 -- 1074}, year = {2016}, abstract = {Synchronous occurrences of heavy rainfall events and the study of their relation in time and space are of large socio-economical relevance, for instance for the agricultural and insurance sectors, but also for the general well-being of the population. In this study, the spatial synchronization structure is analyzed as a regional climate network constructed from precipitation event series. The similarity between event series is determined by the number of synchronous occurrences. We propose a novel standardization of this number that results in synchronization scores which are not biased by the number of events in the respective time series. Additionally, we introduce a new version of the network measure directionality that measures the spatial directionality of weighted links by also taking account of the effects of the spatial embedding of the network. This measure provides an estimate of heavy precipitation isochrones by pointing out directions along which rainfall events synchronize. We propose a climatological interpretation of this measure in terms of propagating fronts or event traces and confirm it for Germany by comparing our results to known atmospheric circulation patterns.}, 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} } @article{MarwanSchwarzKurthsetal.2000, author = {Marwan, Norbert and Schwarz, Udo and Kurths, J{\"u}rgen and Strecker, Manfred}, title = {ENSO Impact on landslide generation in northwestern Argentina}, issn = {1029-7006}, year = {2000}, abstract = {Climatic changes are of major importance in landslide generation in the Argentine Andes. Increased humidity as a potential influential factor was inferred from the temporal clustering of landslide deposits during a period of significantly wetter climate, 30,000 years ago. A change in seasonality was tested by comparing past (inferred from annual-layered lake deposits, 30,000 years old) and modern (present-day observations) precipitation changes. Quantitative analysis of cross recurrence plots were developed to compare the influence of the El Nino/Southern Oscillation (ENSO) on present and past rainfall variations. This analysis has shown the stronger influence of NE trades in the location of landslide deposits in the intra-andean basin and valleys, what caused a higher contrast between summer and winter rainfall and an increasing of precipitation in La Nina years. This is believed to reduce thresholds for landslide generation in the arid to semiarid intra-andean basins and valleys.}, language = {en} } @article{GoswamiShekatkarRheinwaltetal.2015, author = {Goswami, Bedartha and Shekatkar, Snehal M. and Rheinwalt, Aljoscha and Ambika, G. and Kurths, J{\"u}rgen}, title = {A random interacting network model for complex networks}, series = {Scientific reports}, volume = {5}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/srep18183}, pages = {10}, year = {2015}, abstract = {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.}, language = {en} } @article{GoswamiHeitzigRehfeldetal.2014, author = {Goswami, Bedartha and Heitzig, Jobst and Rehfeld, Kira and Marwan, Norbert and Anoop, Ambili and Prasad, Sushma and Kurths, J{\"u}rgen}, title = {Estimation of sedimentary proxy records together with associated uncertainty}, series = {Nonlinear processes in geophysics}, volume = {21}, journal = {Nonlinear processes in geophysics}, number = {6}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1023-5809}, doi = {10.5194/npg-21-1093-2014}, pages = {1093 -- 1111}, year = {2014}, abstract = {Sedimentary proxy records constitute a significant portion of the recorded evidence that allows us to investigate paleoclimatic conditions and variability. However, uncertainties in the dating of proxy archives limit our ability to fix the timing of past events and interpret proxy record intercomparisons. While there are various age-modeling approaches to improve the estimation of the age-depth relations of archives, relatively little focus has been placed on the propagation of the age (and radiocarbon calibration) uncertainties into the final proxy record. We present a generic Bayesian framework to estimate proxy records along with their associated uncertainty, starting with the radiometric age-depth and proxy-depth measurements, and a radiometric calibration curve if required. We provide analytical expressions for the posterior proxy probability distributions at any given calendar age, from which the expected proxy values and their uncertainty can be estimated. We illustrate our method using two synthetic data sets and then use it to construct the proxy records for groundwater inflow and surface erosion from Lonar lake in central India. Our analysis reveals interrelations between the uncertainty of the proxy record over time and the variance of proxies along the depth of the archive. For the Lonar lake proxies, we show that, rather than the age uncertainties, it is the proxy variance combined with calibration uncertainty that accounts for most of the final uncertainty. We represent the proxy records as probability distributions on a precise, error-free timescale that makes further time series analyses and intercomparisons of proxies relatively simple and clear. Our approach provides a coherent understanding of age uncertainties within sedimentary proxy records that involve radiometric dating. It can be potentially used within existing age modeling structures to bring forth a reliable and consistent framework for proxy record estimation.}, language = {en} } @article{GoswamiBoersRheinwaltetal.2018, author = {Goswami, Bedartha and Boers, Niklas and Rheinwalt, Aljoscha and Marwan, Norbert and Heitzig, Jobst and Breitenbach, Sebastian Franz Martin and Kurths, J{\"u}rgen}, title = {Abrupt transitions in time series with uncertainties}, series = {Nature Communications}, volume = {9}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/s41467-017-02456-6}, pages = {10}, year = {2018}, abstract = {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 Ni{\~n}o-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.}, language = {en} } @article{ErogluMarwanPrasadetal.2014, author = {Eroglu, Deniz and Marwan, Norbert and Prasad, Sushma and Kurths, J{\"u}rgen}, title = {Finding recurrence networks' threshold adaptively for a specific time series}, series = {Nonlinear processes in geophysics}, volume = {21}, journal = {Nonlinear processes in geophysics}, number = {6}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1023-5809}, doi = {10.5194/npg-21-1085-2014}, pages = {1085 -- 1092}, year = {2014}, abstract = {Recurrence-plot-based recurrence networks are an approach used to analyze time series using a complex networks theory. In both approaches - recurrence plots and recurrence networks -, a threshold to identify recurrent states is required. The selection of the threshold is important in order to avoid bias of the recurrence network results. In this paper, we propose a novel method to choose a recurrence threshold adaptively. We show a comparison between the constant threshold and adaptive threshold cases to study period-chaos and even period-period transitions in the dynamics of a prototypical model system. This novel method is then used to identify climate transitions from a lake sediment record.}, language = {en} }