TY - JOUR A1 - Agarwal, Ankit A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Öztürk, Ugur A1 - Kurths, Jürgen A1 - Merz, Bruno T1 - Optimal design of hydrometric station networks based on complex network analysis JF - Hydrology and Earth System Sciences N2 - Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure – the weighted degree–betweenness (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail. KW - identifying influential nodes KW - climate networks KW - rainfall KW - streamflow KW - synchronization KW - precipitation KW - classification KW - events Y1 - 2020 U6 - https://doi.org/10.5194/hess-24-2235-2020 SN - 1027-5606 SN - 1607-7938 VL - 24 IS - 5 SP - 2235 EP - 2251 PB - Copernicus Publ. CY - Göttingen ER - TY - JOUR A1 - Maheswaran, Rathinasamy A1 - Agarwal, Ankit A1 - Sivakumar, Bellie A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Wavelet analysis of precipitation extremes over India and teleconnections to climate indices JF - Stochastic Environmental Research and Risk Assessment N2 - Precipitation patterns and extremes are significantly influenced by various climatic factors and large-scale atmospheric circulation patterns. This study uses wavelet coherence analysis to detect significant interannual and interdecadal oscillations in monthly precipitation extremes across India and their teleconnections to three prominent climate indices, namely, Nino 3.4, Pacific Decadal Oscillation, and Indian Ocean Dipole (IOD). Further, partial wavelet coherence analysis is used to estimate the standalone relationship between the climate indices and precipitation after removing the effect of interdependency. The wavelet analysis of monthly precipitation extremes at 30 different locations across India reveals that (a) interannual (2-8 years) and interdecadal (8-32 years) oscillations are statistically significant, and (b) the oscillations vary in both time and space. The results from the partial wavelet coherence analysis reveal that Nino 3.4 and IOD are the significant drivers of Indian precipitation at interannual and interdecadal scales. Intriguingly, the study also confirms that the strength of influence of large-scale atmospheric circulation patterns on Indian precipitation extremes varies with spatial physiography of the region. KW - Extreme precipitation KW - Teleconnection patterns KW - Wavelets KW - Partial wavelet coherence KW - India Y1 - 2019 U6 - https://doi.org/10.1007/s00477-019-01738-3 SN - 1436-3240 SN - 1436-3259 VL - 33 IS - 11-12 SP - 2053 EP - 2069 PB - Springer CY - New York ER - TY - JOUR A1 - Kurths, Jürgen A1 - Agarwal, Ankit A1 - Shukla, Roopam A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Caesar, Levke A1 - Krishnan, Raghavan A1 - Merz, Bruno T1 - Unravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach JF - Nonlinear processes in geophysics N2 - A better understanding of precipitation dynamics in the Indian subcontinent is required since India's society depends heavily on reliable monsoon forecasts. We introduce a non-linear, multiscale approach, based on wavelets and event synchronization, for unravelling teleconnection influences on precipitation. We consider those climate patterns with the highest relevance for Indian precipitation. Our results suggest significant influences which are not well captured by only the wavelet coherence analysis, the state-of-the-art method in understanding linkages at multiple timescales. We find substantial variation across India and across timescales. In particular, El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) mainly influence precipitation in the south-east at interannual and decadal scales, respectively, whereas the North Atlantic Oscillation (NAO) has a strong connection to precipitation, particularly in the northern regions. The effect of the Pacific Decadal Oscillation (PDO) stretches across the whole country, whereas the Atlantic Multidecadal Oscillation (AMO) influences precipitation particularly in the central arid and semi-arid regions. The proposed method provides a powerful approach for capturing the dynamics of precipitation and, hence, helps improve precipitation forecasting. Y1 - 2019 U6 - https://doi.org/10.5194/npg-26-251-2019 SN - 1023-5809 SN - 1607-7946 VL - 26 IS - 3 SP - 251 EP - 266 PB - Copernicus CY - Göttingen ER - 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 - 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 - Agarwal, Ankit A1 - Maheswaran, Rathinasamy A1 - Marwan, Norbert A1 - Caesar, Levke A1 - Kurths, Jürgen T1 - Wavelet-based multiscale similarity measure for complex networks JF - The European physical journal : B, Condensed matter and complex systems N2 - In recent years, complex network analysis facilitated the identification of universal and unexpected patterns in complex climate systems. However, the analysis and representation of a multiscale complex relationship that exists in the global climate system are limited. A logical first step in addressing this issue is to construct multiple networks over different timescales. Therefore, we propose to apply the wavelet multiscale correlation (WMC) similarity measure, which is a combination of two state-of-the-art methods, viz. wavelet and Pearson’s correlation, for investigating multiscale processes through complex networks. Firstly we decompose the data over different timescales using the wavelet approach and subsequently construct a corresponding network by Pearson’s correlation. The proposed approach is illustrated and tested on two synthetics and one real-world example. The first synthetic case study shows the efficacy of the proposed approach to unravel scale-specific connections, which are often undiscovered at a single scale. The second synthetic case study illustrates that by dividing and constructing a separate network for each time window we can detect significant changes in the signal structure. The real-world example investigates the behavior of the global sea surface temperature (SST) network at different timescales. Intriguingly, we notice that spatial dependent structure in SST evolves temporally. Overall, the proposed measure has an immense potential to provide essential insights on understanding and extending complex multivariate process studies at multiple scales. KW - Statistical and Nonlinear Physics Y1 - 2018 U6 - https://doi.org/10.1140/epjb/e2018-90460-6 SN - 1434-6028 SN - 1434-6036 VL - 91 IS - 11 PB - Springer CY - New York ER - TY - JOUR A1 - Agarwal, Ankit A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Merz, Bruno A1 - Kurths, Jürgen T1 - Quantifying the roles of single stations within homogeneous regions using complex network analysis JF - Journal of hydrology N2 - Regionalization and pooling stations to form homogeneous regions or communities are essential for reliable parameter transfer, prediction in ungauged basins, and estimation of missing information. Over the years, several clustering methods have been proposed for regional analysis. Most of these methods are able to quantify the study region in terms of homogeneity but fail to provide microscopic information about the interaction between communities, as well as about each station within the communities. We propose a complex network-based approach to extract this valuable information and demonstrate the potential of our approach using a rainfall network constructed from the Indian gridded daily precipitation data. The communities were identified using the network-theoretical community detection algorithm for maximizing the modularity. Further, the grid points (nodes) were classified into universal roles according to their pattern of within- and between-community connections. The method thus yields zoomed-in details of individual rainfall grids within each community. KW - Complex network KW - Event synchronization KW - Rainfall network KW - Z-P approach Y1 - 2018 U6 - https://doi.org/10.1016/j.jhydrol.2018.06.050 SN - 0022-1694 SN - 1879-2707 VL - 563 SP - 802 EP - 810 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Agarwal, Ankit A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Merz, Bruno A1 - Kurths, Jürgen T1 - Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach JF - Nonlinear processes in geophysics N2 - The temporal dynamics of climate processes are spread across different timescales and, as such, the study of these processes at only one selected timescale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. To capture the non-linear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analysing the time series at one reference timescale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, the wavelet-based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various timescales. The proposed method allows the study of spatio-temporal patterns across different timescales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different timescales. Y1 - 2017 U6 - https://doi.org/10.5194/npg-24-599-2017 SN - 1023-5809 VL - 24 SP - 599 EP - 611 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Ramos, Antonio M. T. A1 - Builes-Jaramillo, Alejandro A1 - Poveda, German A1 - Goswami, Bedartha A1 - Macau, Elbert E. N. A1 - Kurths, Jürgen A1 - Marwan, Norbert T1 - Recurrence measure of conditional dependence and applications JF - Physical review : E, Statistical, nonlinear and soft matter physics N2 - Identifying causal relations from observational data sets has posed great challenges in data-driven causality inference studies. One of the successful approaches to detect direct coupling in the information theory framework is transfer entropy. However, the core of entropy-based tools lies on the probability estimation of the underlying variables. Herewe propose a data-driven approach for causality inference that incorporates recurrence plot features into the framework of information theory. We define it as the recurrence measure of conditional dependence (RMCD), and we present some applications. The RMCD quantifies the causal dependence between two processes based on joint recurrence patterns between the past of the possible driver and present of the potentially driven, excepting the contribution of the contemporaneous past of the driven variable. Finally, it can unveil the time scale of the influence of the sea-surface temperature of the Pacific Ocean on the precipitation in the Amazonia during recent major droughts. Y1 - 2017 U6 - https://doi.org/10.1103/PhysRevE.95.052206 SN - 2470-0045 SN - 2470-0053 VL - 95 PB - American Physical Society CY - College Park ER - TY - JOUR A1 - Boers, Niklas A1 - Bookhagen, Bodo A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Spatiotemporal characteristics and synchronization of extreme rainfall in South America with focus on the Andes Mountain range JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - The South American Andes are frequently exposed to intense rainfall events with varying moisture sources and precipitation-forming processes. In this study, we assess the spatiotemporal characteristics and geographical origins of rainfall over the South American continent. Using high-spatiotemporal resolution satellite data (TRMM 3B42 V7), we define four different types of rainfall events based on their (1) high magnitude, (2) long temporal extent, (3) large spatial extent, and (4) high magnitude, long temporal and large spatial extent combined. In a first step, we analyze the spatiotemporal characteristics of these events over the entire South American continent and integrate their impact for the main Andean hydrologic catchments. Our results indicate that events of type 1 make the overall highest contributions to total seasonal rainfall (up to 50%). However, each consecutive episode of the infrequent events of type 4 still accounts for up to 20% of total seasonal rainfall in the subtropical Argentinean plains. In a second step, we employ complex network theory to unravel possibly non-linear and long-ranged climatic linkages for these four event types on the high-elevation Altiplano-Puna Plateau as well as in the main river catchments along the foothills of the Andes. Our results suggest that one to two particularly large squall lines per season, originating from northern Brazil, indirectly trigger large, long-lasting thunderstorms on the Altiplano Plateau. In general, we observe that extreme rainfall in the catchments north of approximately 20 degrees S typically originates from the Amazon Basin, while extreme rainfall at the eastern Andean foothills south of 20 degrees S and the Puna Plateau originates from southeastern South America. KW - Extreme rainfall KW - Synchronization KW - Complex networks KW - South American monsoon system Y1 - 2016 U6 - https://doi.org/10.1007/s00382-015-2601-6 SN - 0930-7575 SN - 1432-0894 VL - 46 SP - 601 EP - 617 PB - Springer CY - New York ER - TY - JOUR A1 - Rheinwalt, Aljoscha A1 - Boers, Niklas A1 - Marwan, Norbert A1 - Kurths, Jürgen A1 - Hoffmann, Peter A1 - Gerstengarbe, Friedrich-Wilhelm A1 - Werner, Peter T1 - Non-linear time series analysis of precipitation events using regional climate networks for Germany JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - 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. KW - Rainfall KW - Complex networks KW - Precipitation events KW - Anisotropy KW - Dominant link directions KW - Isochrones KW - Event synchronization Y1 - 2016 U6 - https://doi.org/10.1007/s00382-015-2632-z SN - 0930-7575 SN - 1432-0894 VL - 46 SP - 1065 EP - 1074 PB - Springer CY - New York 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 - TY - JOUR A1 - Goswami, Bedartha A1 - Heitzig, Jobst A1 - Rehfeld, Kira A1 - Marwan, Norbert A1 - Anoop, Ambili A1 - Prasad, Sushma A1 - Kurths, Jürgen T1 - Estimation of sedimentary proxy records together with associated uncertainty JF - Nonlinear processes in geophysics N2 - 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. Y1 - 2014 U6 - https://doi.org/10.5194/npg-21-1093-2014 SN - 1023-5809 VL - 21 IS - 6 SP - 1093 EP - 1111 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Stolbova, Veronika A1 - Martin, P. A1 - Bookhagen, Bodo A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka JF - Nonlinear processes in geophysics N2 - 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. Y1 - 2014 U6 - https://doi.org/10.5194/npg-21-901-2014 SN - 1023-5809 VL - 21 IS - 4 SP - 901 EP - 917 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Eroglu, Deniz A1 - Marwan, Norbert A1 - Prasad, Sushma A1 - Kurths, Jürgen T1 - Finding recurrence networks' threshold adaptively for a specific time series JF - Nonlinear processes in geophysics N2 - 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. Y1 - 2014 U6 - https://doi.org/10.5194/npg-21-1085-2014 SN - 1023-5809 VL - 21 IS - 6 SP - 1085 EP - 1092 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Goswami, Bedartha A1 - Marwan, Norbert A1 - Feulner, Georg A1 - Kurths, Jürgen T1 - How do global temperature drivers influence each other? JF - European physical journal special topics N2 - We investigate a network of influences connected to global mean temperature. Considering various climatic factors known to influence global mean temperature, we evaluate not only the impacts of these factors on temperature but also the directed dependencies among the factors themselves. Based on an existing recurrence-based connectivity measure, we propose a new and more general measure that quantifies the level of dependence between two time series based on joint recurrences at a chosen time delay. The measures estimated in the analysis are tested for statistical significance using twin surrogates. We find, in accordance with earlier studies, the major drivers for global mean temperature to be greenhouse gases, ENSO, volcanic activity, and solar irradiance. We further uncover a feedback between temperature and ENSO. Our results demonstrate the need to involve multiple, delayed interactions within the drivers of temperature in order to develop a more thorough picture of global temperature variations. Y1 - 2013 U6 - https://doi.org/10.1140/epjst/e2013-01889-8 SN - 1951-6355 VL - 222 IS - 3-4 SP - 861 EP - 873 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Marwan, Norbert A1 - Schinkel, Stefan A1 - Kurths, Jürgen T1 - Recurrence plots 25 years later -Gaining confidence in dynamical transitions JF - epl : a letters journal exploring the frontiers of physics N2 - Recurrence-plot-based time series analysis is widely used to study changes and transitions in the dynamics of a system or temporal deviations from its overall dynamical regime. However, most studies do not discuss the significance of the detected variations in the recurrence quantification measures. In this letter we propose a novel method to add a confidence measure to the recurrence quantification analysis. We show how this approach can be used to study significant changes in dynamical systems due to a change in control parameters, chaos-order as well as chaos-chaos transitions. Finally we study and discuss climate transitions by analysing a marine proxy record for past sea surface temperature. This paper is dedicated to the 25th anniversary of the introduction of recurrence plots. Y1 - 2013 U6 - https://doi.org/10.1209/0295-5075/101/20007 SN - 0295-5075 VL - 101 IS - 2 PB - EDP Sciences CY - Mulhouse ER - TY - JOUR A1 - Malik, Nishant A1 - Zou, Y. A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Dynamical regimes and transitions in plio-pleistocene Asian monsoon JF - epl : a letters journal exploring the frontiers of physics N2 - We propose a novel approach based on the fluctuation of similarity to identify regimes of distinct dynamical complexity in short time series. A statistical test is developed to estimate the significance of the identified transitions. Our method is verified by uncovering bifurcation structures in several paradigmatic models, providing more complex transitions compared with traditional Lyapunov exponents. In a real-world situation, we apply this method to identify millennial-scale dynamical transitions in Plio-Pleistocene proxy records of the South Asian summer monsoon system. We infer that many of these transitions are induced by the external forcing of the solar insolation and are also affected by internal forcing on Monsoonal dynamics, i.e., the glaciation cycles of the Northern Hemisphere and the onset of the Walker circulation. Y1 - 2012 U6 - https://doi.org/10.1209/0295-5075/97/40009 SN - 0295-5075 VL - 97 IS - 4 PB - EDP Sciences CY - Mulhouse 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 - Marwan, Norbert A1 - Beller, Gise A1 - Felsenberg, Dieter A1 - Saparin, Peter A1 - Kurths, Jürgen T1 - quantifying changes in the spatial structure of trabecular bone JF - International journal of bifurcation and chaos : in applied sciences and engineering N2 - We apply recently introduced measures of complexity for the structural quantification of distal tibial bone. For the first time, we are able to investigate the temporal structural alteration of trabecular bone. Based on four patients, we show how the bone may alter due to temporal immobilization. KW - 3D medical image analysis KW - pQCT KW - trabecular bone KW - patient immobilization Y1 - 2012 U6 - https://doi.org/10.1142/S0218127412500277 SN - 0218-1274 VL - 22 IS - 2 PB - World Scientific CY - Singapore ER - TY - JOUR A1 - Breitenbach, Sebastian Franz Martin A1 - Rehfeld, Kira A1 - Goswami, Bedartha A1 - Baldini, James U. L. A1 - Ridley, H. E. A1 - Kennett, D. J. A1 - Prufer, K. M. A1 - Aquino, Valorie V. A1 - Asmerom, Yemane A1 - Polyak, V. J. A1 - Cheng, Hai A1 - Kurths, Jürgen A1 - Marwan, Norbert T1 - Constructing Proxy Records from Age models (COPRA) JF - Climate of the past : an interactive open access journal of the European Geosciences Union N2 - Reliable age models are fundamental for any palaeoclimate reconstruction. Available interpolation procedures between age control points are often inadequately reported, and very few translate age uncertainties to proxy uncertainties. Most available modeling algorithms do not allow incorporation of layer counted intervals to improve the confidence limits of the age model in question. We present a framework that allows detection and interactive handling of age reversals and hiatuses, depth-age modeling, and proxy-record reconstruction. Monte Carlo simulation and a translation procedure are used to assign a precise time scale to climate proxies and to translate dating uncertainties to uncertainties in the proxy values. The presented framework allows integration of incremental relative dating information to improve the final age model. The free software package COPRA1.0 facilitates easy interactive usage. Y1 - 2012 U6 - https://doi.org/10.5194/cp-8-1765-2012 SN - 1814-9324 VL - 8 IS - 5 SP - 1765 EP - 1779 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Donges, Jonathan Friedemann A1 - Donner, Reik Volker A1 - Rehfeld, Kira A1 - Marwan, Norbert A1 - Trauth, Martin H. A1 - Kurths, Jürgen T1 - Identification of dynamical transitions in marine palaeoclimate records by recurrence network analysis JF - Nonlinear processes in geophysics N2 - The analysis of palaeoclimate time series is usually affected by severe methodological problems, resulting primarily from non-equidistant sampling and uncertain age models. As an alternative to existing methods of time series analysis, in this paper we argue that the statistical properties of recurrence networks - a recently developed approach - are promising candidates for characterising the system's nonlinear dynamics and quantifying structural changes in its reconstructed phase space as time evolves. In a first order approximation, the results of recurrence network analysis are invariant to changes in the age model and are not directly affected by non-equidistant sampling of the data. Specifically, we investigate the behaviour of recurrence network measures for both paradigmatic model systems with non-stationary parameters and four marine records of long-term palaeoclimate variations. We show that the obtained results are qualitatively robust under changes of the relevant parameters of our method, including detrending, size of the running window used for analysis, and embedding delay. We demonstrate that recurrence network analysis is able to detect relevant regime shifts in synthetic data as well as in problematic geoscientific time series. This suggests its application as a general exploratory tool of time series analysis complementing existing methods. Y1 - 2011 U6 - https://doi.org/10.5194/npg-18-545-2011 SN - 1023-5809 VL - 18 IS - 5 SP - 545 EP - 562 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Donges, Jonathan Friedemann A1 - Donner, Reik Volker A1 - Trauth, Martin H. A1 - Marwan, Norbert A1 - Schellnhuber, Hans Joachim A1 - Kurths, Jürgen T1 - Nonlinear detection of paleoclimate-variability transitions possibly related to human evolution JF - Proceedings of the National Academy of Sciences of the United States of America N2 - Potential paleoclimatic driving mechanisms acting on human evolution present an open problem of cross-disciplinary scientific interest. The analysis of paleoclimate archives encoding the environmental variability in East Africa during the past 5 Ma has triggered an ongoing debate about possible candidate processes and evolutionary mechanisms. In this work, we apply a nonlinear statistical technique, recurrence network analysis, to three distinct marine records of terrigenous dust flux. Our method enables us to identify three epochs with transitions between qualitatively different types of environmental variability in North and East Africa during the (i) Middle Pliocene (3.35-3.15 Ma B. P.), (ii) Early Pleistocene (2.25-1.6 Ma B. P.), and (iii) Middle Pleistocene (1.1-0.7 Ma B. P.). A deeper examination of these transition periods reveals potential climatic drivers, including (i) large-scale changes in ocean currents due to a spatial shift of the Indonesian throughflow in combination with an intensification of Northern Hemisphere glaciation, (ii) a global reorganization of the atmospheric Walker circulation induced in the tropical Pacific and Indian Ocean, and (iii) shifts in the dominating temporal variability pattern of glacial activity during the Middle Pleistocene, respectively. A reexamination of the available fossil record demonstrates statistically significant coincidences between the detected transition periods and major steps in hominin evolution. This result suggests that the observed shifts between more regular and more erratic environmental variability may have acted as a trigger for rapid change in the development of humankind in Africa. KW - African climate KW - Plio-Pleistocene KW - climate-driven evolution KW - dynamical transitions KW - nonlinear time series analysis Y1 - 2011 U6 - https://doi.org/10.1073/pnas.1117052108 SN - 0027-8424 VL - 108 IS - 51 SP - 20422 EP - 20427 PB - National Acad. of Sciences CY - Washington 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 - Marwan, Norbert A1 - Kurths, Jürgen A1 - Thomsen, Jesper Skovhus A1 - Felsenberg, Dieter A1 - Saparin, Peter T1 - Three-dimensional quantification of structures in trabecular bone using measures of complexity N2 - The study of pathological changes of bone is an important task in diagnostic procedures of patients with metabolic bone diseases such as osteoporosis as well as in monitoring the health state of astronauts during long-term space flights. The recent availability of high-resolution three-dimensional (3D) imaging of bone challenges the development of data analysis techniques able to assess changes of the 3D microarchitecture of trabecular bone. We introduce an approach based on spatial geometrical properties and define structural measures of complexity for 3D image analysis. These measures evaluate different aspects of organization and complexity of 3D structures, such as complexity of its surface or shape variability. We apply these measures to 3D data acquired by high-resolution microcomputed tomography (mu CT) from human proximal tibiae and lumbar vertebrae at different stages of osteoporotic bone loss. The outcome is compared to the results of conventional static histomorphometry and exhibits clear relationships between the analyzed geometrical features of trabecular bone and loss of bone density, but also indicate that the measures reveal additional information about the structural composition of bone, which were not revealed by the static histomorphometry. Finally, we have studied the dependency of the developed measures of complexity on the spatial resolution of the mu CT data sets. Y1 - 2009 UR - http://pre.aps.org/ U6 - https://doi.org/10.1103/Physreve.79.021903 SN - 1539-3755 ER - TY - JOUR A1 - Zolotova, Nadezhda V. A1 - Ponyavin, Dmitri I. A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Long-term asymmetry in the wings of the butterfly diagram N2 - Aims. Sunspot distribution in the northern and southern solar hemispheres exibit striking synchronous behaviour on the scale of a Schwabe cycle. However, sometimes the bilateral symmetry of the Butterfly diagram relative to the solar equatorial plane breaks down. The investigation of this phenomenon is important to explaining the almost-periodic behaviour of solar cycles. Methods. We use cross-recurrence plots for the study of the time-varying phase asymmetry of the northern and southern hemisphere and compare our results with the latitudinal distribution of the sunspots. Results. We observe a long-term persistence of phase leading in one of the hemispheres, which lasts almost 4 solar cycles and probably corresponds to the Gleissberg cycle. Long-term variations in the hemispheric-leading do not demonstrate clear periodicity but are strongly anti-correlated with the long-term variations in the magnetic equator. Y1 - 2009 UR - http://www.aanda.org/ U6 - https://doi.org/10.1051/0004-6361/200811430 SN - 0004-6361 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 - 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 - 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 - Kurths, Jürgen T1 - Line structures in recurrence plots N2 - Recurrence plots exhibit line structures which represent typical behaviour of the investigated system. The local slope of these line structures is connected with a specific transformation of the time scales of different segments of the phase-space trajectory. This provides us a better understanding of the structures occurring in recurrence plots. The relationship between the time-scales and line structures are of practical importance in cross recurrence plots. Using this relationship within cross recurrence plots, the time-scales of differently sampled or time- transformed measurements can be adjusted. An application to geophysical measurements illustrates the capability of this method for the adjustment of time-scales in different measurements. (C) 2005 Elsevier B.V. All rights reserved Y1 - 2005 SN - 0375-9601 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 - Marwan, Norbert A1 - Wessel, Niels A1 - Meyerfeldt, Udo A1 - Schirdewan, Alexander A1 - Kurths, Jürgen T1 - Recurrence-plot-based measures of complexity and its application to heart-rate-variability data N2 - The knowledge of transitions between regular, laminar or chaotic behavior is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods which however require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart rate variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e. chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our new measures to the heart rate variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias. Y1 - 2002 UR - http://arxiv.org/abs/physics/0201064 ER - TY - JOUR A1 - Marwan, Norbert A1 - Nowaczyk, Norbert R. A1 - Kurths, Jürgen A1 - Thiel, Marco T1 - Cross recurrence plot based rescaling of geological time series N2 - The rescaling of geological data series to a geological reference time series is of major interest in many investigations. For example, geophysical borehole data should be correlated to a given data series whose time scale is known in order to achieve an age-depth function or the sedimentation rate for the borehole data. Usually this synchronization is performed visually and by hand. Instead of using this wiggle matching by eye, we present the application of cross recurrence plots for such tasks. Using this method, the synchronization and rescaling of geological data to a given time scale is much easier and faster than by hand. Y1 - 2001 SN - 1029-7006 ER - TY - JOUR A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Nonlinear analysis of bivariate data with cross recurrence plots N2 - We use the extension of the method of recurrence plots to cross recurrence plots (CRP) which enables a nonlinear analysis of bivariate data. To quantify CRPs, we develop further three measures of complexity mainly basing on diagonal structures in CRPs. The CRP analysis of prototypical model systems with nonlinear interactions demonstrates that this technique enables to find these nonlinear interrelations from bivariate time series, whereas linear correlation tests do not. Applying the CRP analysis to climatological data, we find a complex relationship between rainfall and El Nino data. Y1 - 2001 UR - http://arxiv.org/abs/physics/0201061 ER - TY - JOUR A1 - Wessel, Niels A1 - Marwan, Norbert A1 - Meyerfeldt, Udo A1 - Schirdewan, Alexander A1 - Kurths, Jürgen T1 - Recurrence quantification analysis to characterise the heart rate variability before the onset of ventricular tachycardia N2 - Ventricular tachycardia or fibrillation (VT) as fatal cardiac arrhythmias are the main factors triggering sudden cardiac death. The objective of this recurrence quantification analysis approach is to find early signs of sustained VT in patients with an implanted cardioverter-defibrillator (ICD). These devices are able to safeguard patients by returning their hearts to a normal rhythm via strong defibrillatory shocks; additionally, they are able to store at least 1000 beat-to-beat intervals immediately before the onset of a life-threatening arrhythmia. We study the Y1 - 2001 UR - http://link.springer.de/link/service/series/0558/bibs/2199/21990295.htm ER - TY - JOUR A1 - Marwan, Norbert A1 - Schwarz, Udo A1 - Kurths, Jürgen A1 - Strecker, Manfred T1 - ENSO Impact on landslide generation in northwestern Argentina N2 - 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. Y1 - 2000 SN - 1029-7006 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 -