@article{MarwanTrauthVuilleetal.2003, author = {Marwan, Norbert and Trauth, Martin H. and Vuille, Mathias and Kurths, J{\"u}rgen}, title = {Comparing modern and Pleistocene ENSO-like influences in NW Argentina using nonlinear time series analysis methods}, year = {2003}, abstract = {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 Ni{\~n}o/ 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.}, language = {en} } @article{MarwanWesselMeyerfeldtetal.2002, author = {Marwan, Norbert and Wessel, Niels and Meyerfeldt, Udo and Schirdewan, Alexander and Kurths, J{\"u}rgen}, title = {Recurrence-plot-based measures of complexity and its application to heart-rate-variability data}, year = {2002}, abstract = {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.}, language = {en} } @article{MarwanThielNowaczyk2002, author = {Marwan, Norbert and Thiel, Marco and Nowaczyk, Norbert R.}, title = {Cross recurrence plot based synchronization of time series}, year = {2002}, abstract = {The method of recurrence plots is extended to the cross recurrence plots (CRP), which among others enables the study of synchronization or time differences in two time series. This is emphasized in a distorted main diagonal in the cross recurrence plot, the line of synchronization (LOS). A non-parametrical fit of this LOS can be used to rescale the time axis of the two data series (whereby one of it is e.g. compressed or stretched) so that they are synchronized. An application of this method to geophysical sediment core data illustrates its suitability for real data. The rock magnetic data of two different sediment cores from the Makarov Basin can be adjusted to each other by using this method, so that they are comparable.}, language = {en} } @phdthesis{Marwan2003, author = {Marwan, Norbert}, title = {Encounters with neighbours}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0000856}, school = {Universit{\"a}t Potsdam}, year = {2003}, abstract = {Diese Arbeit besch{\"a}ftigt sich mit verschiedenen Aspekten und Anwendungen von Recurrence Plots. Nach einer {\"U}bersicht {\"u}ber Methoden, die auf Recurrence Plots basieren, werden neue Komplexit{\"a}tsmaße eingef{\"u}hrt, die geometrische Strukturen in den Recurrence Plots beschreiben. Diese neuen Maße erlauben die Identifikation von Chaos-Chaos-{\"U}berg{\"a}ngen in dynamischen Prozessen. In einem weiteren Schritt werden Cross Recurrence Plots eingef{\"u}hrt, mit denen zwei verschiedene Prozesse untersucht werden. Diese bivariate Analyse erm{\"o}glicht die Bewertung von Unterschieden zwischen zwei Prozessen oder das Anpassen der Zeitskalen von zwei Zeitreihen. Diese Technik kann auch genutzt werden, um {\"a}hnliche Abschnitte in zwei verschiedenen Datenreihen zu finden. Im Anschluß werden diese neuen Entwicklungen auf Daten verschiedener Art angewendet. Methoden, die auf Recurrence Plots basieren, k{\"o}nnen an die speziellen Probleme angepaßt werden, so daß viele weitere Anwendungen m{\"o}glich sind. Durch die Anwendung der neu eingef{\"u}hrten Komplexit{\"a}tsmaße k{\"o}nnen Chaos-Chaos-{\"U}berg{\"a}nge in Herzschlagdaten vor dem Auftreten einer lebensbedrohlichen Herzrhythmusst{\"o}rung festgestellt werden, was f{\"u}r die Entwicklung neuer Therapien dieser Herzrhythmusst{\"o}rungen von Bedeutung sein k{\"o}nnte. In einem weiteren Beispiel, in dem EEG-Daten aus einem kognitiv orientierten Experiment untersucht werden, erm{\"o}glichen diese Komplexit{\"a}tsmaße das Erkennen von spezifischen Reaktionen im Gehirn bereits in Einzeltests. Normalerweise k{\"o}nnen diese Reaktionen erst durch die Auswertung von vielen Einzeltests erkannt werden. Mit der Hilfe von Cross Recurrence Plots wird die Existenz einer klimatischen Zirkulation, die der heutigen El Ni{\~n}o/ Southern Oscillation sehr {\"a}hnlich ist, im Nordwesten Argentiniens vor etwa 34000 Jahren nachgewiesen. Außerdem k{\"o}nnen mit Cross Recurrence Plots die Zeitskalen verschiedener Bohrlochdaten aufeinander abgeglichen werden. Diese Methode kann auch dazu genutzt werden, ein geologisches Profil mit Hilfe eines Referenzprofiles mit bekannter Zeitskala zu datieren. Weitere Beispiele aus den Gebieten der Molekularbiologie und der Spracherkennung unterstreichen das Potential dieser Methode.}, language = {en} } @article{KraemerDonnerHeitzigetal.2018, author = {Kr{\"a}mer, Hauke Kai and Donner, Reik Volker and Heitzig, Jobst and Marwan, Norbert}, title = {Recurrence threshold selection for obtaining robust recurrence characteristics in different embedding dimensions}, series = {Chaos : an interdisciplinary journal of nonlinear science}, volume = {28}, journal = {Chaos : an interdisciplinary journal of nonlinear science}, number = {8}, publisher = {American Institute of Physics}, address = {Melville}, issn = {1054-1500}, doi = {10.1063/1.5024914}, pages = {11}, year = {2018}, abstract = {The appropriate selection of recurrence thresholds is a key problem in applications of recurrence quantification analysis and related methods across disciplines. Here, we discuss the distribution of pairwise distances between state vectors in the studied system's state space reconstructed by means of time-delay embedding as the key characteristic that should guide the corresponding choice for obtaining an adequate resolution of a recurrence plot. Specifically, we present an empirical description of the distance distribution, focusing on characteristic changes of its shape with increasing embedding dimension. Our results suggest that selecting the recurrence threshold according to a fixed percentile of this distribution reduces the dependence of recurrence characteristics on the embedding dimension in comparison with other commonly used threshold selection methods. Numerical investigations on some paradigmatic model systems with time-dependent parameters support these empirical findings. Recurrence plots (RPs) provide an intuitive tool for visualizing the (potentially multi-dimensional) trajectory of a dynamical system in state space. In case only univariate observations of the system's overall state are available, time-delay embedding has become a standard procedure for qualitatively reconstructing the dynamics in state space. The selection of a threshold distance 𝜀 , which distinguishes close from distant pairs of (reconstructed) state vectors, is known to have a substantial impact on the recurrence plot and its quantitative characteristics, but its corresponding interplay with the embedding dimension has not yet been explicitly addressed. Here, we point out that the results of recurrence quantification analysis (RQA) and related methods are qualitatively robust under changes of the (sufficiently high) embedding dimension only if the full distribution of pairwise distances between state vectors is considered for selecting 𝜀, which is achieved by consideration of a fixed recurrence rate.}, language = {en} } @article{WendiMarwan2018, author = {Wendi, Dadiyorto and Marwan, Norbert}, title = {Extended recurrence plot and quantification for noisy continuous dynamical systems}, series = {Chaos : an interdisciplinary journal of nonlinear science}, volume = {28}, journal = {Chaos : an interdisciplinary journal of nonlinear science}, number = {8}, publisher = {American Institute of Physics}, address = {Melville}, issn = {1054-1500}, doi = {10.1063/1.5025485}, pages = {9}, year = {2018}, abstract = {One main challenge in constructing a reliable recurrence plot (RP) and, hence, its quantification [recurrence quantification analysis (RQA)] of a continuous dynamical system is the induced noise that is commonly found in observation time series. This induced noise is known to cause disrupted and deviated diagonal lines despite the known deterministic features and, hence, biases the diagonal line based RQA measures and can lead to misleading conclusions. Although discontinuous lines can be further connected by increasing the recurrence threshold, such an approach triggers thick lines in the plot. However, thick lines also influence the RQA measures by artificially increasing the number of diagonals and the length of vertical lines [e.g., Determinism (DET) and Laminarity (LAM) become artificially higher]. To take on this challenge, an extended RQA approach for accounting disrupted and deviated diagonal lines is proposed. The approach uses the concept of a sliding diagonal window with minimal window size that tolerates the mentioned deviated lines and also considers a specified minimal lag between points as connected. This is meant to derive a similar determinism indicator for noisy signal where conventional RQA fails to capture. Additionally, an extended local minima approach to construct RP is also proposed to further reduce artificial block structures and vertical lines that potentially increase the associated RQA like LAM. The methodology and applicability of the extended local minima approach and DET equivalent measure are presented and discussed, respectively.}, 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{MaheswaranAgarwalSivakumaretal.2019, author = {Maheswaran, Rathinasamy and Agarwal, Ankit and Sivakumar, Bellie and Marwan, Norbert and Kurths, J{\"u}rgen}, title = {Wavelet analysis of precipitation extremes over India and teleconnections to climate indices}, series = {Stochastic Environmental Research and Risk Assessment}, volume = {33}, journal = {Stochastic Environmental Research and Risk Assessment}, number = {11-12}, publisher = {Springer}, address = {New York}, issn = {1436-3240}, doi = {10.1007/s00477-019-01738-3}, pages = {2053 -- 2069}, year = {2019}, abstract = {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.}, language = {en} } @article{RamosBuilesJaramilloPovedaetal.2017, author = {Ramos, Antonio M. T. and Builes-Jaramillo, Alejandro and Poveda, German and Goswami, Bedartha and Macau, Elbert E. N. and Kurths, J{\"u}rgen and Marwan, Norbert}, title = {Recurrence measure of conditional dependence and applications}, series = {Physical review : E, Statistical, nonlinear and soft matter physics}, volume = {95}, journal = {Physical review : E, Statistical, nonlinear and soft matter physics}, publisher = {American Physical Society}, address = {College Park}, issn = {2470-0045}, doi = {10.1103/PhysRevE.95.052206}, pages = {8}, year = {2017}, abstract = {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.}, language = {en} } @article{MarwanKurthsThomsenetal.2009, author = {Marwan, Norbert and Kurths, J{\"u}rgen and Thomsen, Jesper Skovhus and Felsenberg, Dieter and Saparin, Peter}, title = {Three-dimensional quantification of structures in trabecular bone using measures of complexity}, issn = {1539-3755}, doi = {10.1103/Physreve.79.021903}, year = {2009}, abstract = {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.}, language = {en} }