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 - Wendi, Dadiyorto A1 - Merz, Bruno A1 - Marwan, Norbert T1 - Assessing hydrograph similarity and rare runoff dynamics by cross recurrence plots JF - Water resources research N2 - This paper introduces a novel measure to assess similarity between event hydrographs. It is based on cross recurrence plots (CRP) and recurrence quantification analysis (RQA), which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multidimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to cross recurrence plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures. KW - runoff dynamics KW - cross recurrence plot in hydrology KW - rare flood dynamics KW - hydrograph similarity KW - time delay embedding for runoff series Y1 - 2019 U6 - https://doi.org/10.1029/2018WR024111 SN - 0043-1397 SN - 1944-7973 VL - 55 IS - 6 SP - 4704 EP - 4726 PB - American Geophysical Union CY - Washington 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 - Wendi, Dadiyorto A1 - Marwan, Norbert A1 - Merz, Bruno T1 - In Search of Determinism-Sensitive Region to Avoid Artefacts in Recurrence Plots JF - International journal of bifurcation and chaos : in applied sciences and engineering N2 - As an effort to reduce parameter uncertainties in constructing recurrence plots, and in particular to avoid potential artefacts, this paper presents a technique to derive artefact-safe region of parameter sets. This technique exploits both deterministic (incl. chaos) and stochastic signal characteristics of recurrence quantification (i.e. diagonal structures). It is useful when the evaluated signal is known to be deterministic. This study focuses on the recurrence plot generated from the reconstructed phase space in order to represent many real application scenarios when not all variables to describe a system are available (data scarcity). The technique involves random shuffling of the original signal to destroy its original deterministic characteristics. Its purpose is to evaluate whether the determinism values of the original and the shuffled signal remain closely together, and therefore suggesting that the recurrence plot might comprise artefacts. The use of such determinism-sensitive region shall be accompanied by standard embedding optimization approaches, e.g. using indices like false nearest neighbor and mutual information, to result in a more reliable recurrence plot parameterization. KW - Recurrence plot KW - phase space time delay embedding reconstruction KW - artefact avoidance Y1 - 2017 U6 - https://doi.org/10.1142/S0218127418500074 SN - 0218-1274 SN - 1793-6551 VL - 28 IS - 1 PB - World Scientific CY - Singapore ER - TY - GEN A1 - Agarwal, Ankit A1 - Caesar, Levke A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Merz, Bruno T1 - Network-based identification and characterization of teleconnections on different scales T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - Sea surface temperature (SST) patterns can – as surface climate forcing – affect weather and climate at large distances. One example is El Niño-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of – at a certain timescale – similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 731 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-430520 SN - 1866-8372 IS - 731 ER - TY - JOUR A1 - Agarwal, Ankit A1 - Caesar, Levke A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Merz, Bruno T1 - Network-based identification and characterization of teleconnections on different scales JF - Scientific Reports N2 - Sea surface temperature (SST) patterns can – as surface climate forcing – affect weather and climate at large distances. One example is El Niño-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of – at a certain timescale – similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole. Y1 - 2019 U6 - https://doi.org/10.1038/s41598-019-45423-5 SN - 2045-2322 VL - 9 PB - Macmillan Publishers Limited CY - London ER - TY - GEN 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 BT - a wavelet-based approach T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 661 KW - precipitation KW - phase KW - EEG KW - desynchronization KW - interdependences KW - coherence KW - networks KW - monsoon KW - models KW - time Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418274 SN - 1866-8372 IS - 661 ER - 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 - 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 - GEN 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 T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 951 KW - identifying influential nodes KW - climate networks KW - rainfall KW - streamflow KW - synchronization KW - precipitation KW - classification KW - events Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-471006 SN - 1866-8372 IS - 951 ER -