TY - JOUR A1 - Ekhtiari, Nikoo A1 - Agarwal, Ankit A1 - Marwan, Norbert A1 - Donner, Reik Volker T1 - Disentangling the multi-scale effects of sea-surface temperatures on global precipitation BT - a coupled networks approach JF - Chaos : an interdisciplinary journal of nonlinear science N2 - The oceans and atmosphere interact via a multiplicity of feedback mechanisms, shaping to a large extent the global climate and its variability. To deepen our knowledge of the global climate system, characterizing and investigating this interdependence is an important task of contemporary research. However, our present understanding of the underlying large-scale processes is greatly limited due to the manifold interactions between essential climatic variables at different temporal scales. To address this problem, we here propose to extend the application of complex network techniques to capture the interdependence between global fields of sea-surface temperature (SST) and precipitation (P) at multiple temporal scales. For this purpose, we combine time-scale decomposition by means of a discrete wavelet transform with the concept of coupled climate network analysis. Our results demonstrate the potential of the proposed approach to unravel the scale-specific interdependences between atmosphere and ocean and, thus, shed light on the emerging multiscale processes inherent to the climate system, which traditionally remain undiscovered when investigating the system only at the native resolution of existing climate data sets. Moreover, we show how the relevant spatial interdependence structures between SST and P evolve across time-scales. Most notably, the strongest mutual correlations between SST and P at annual scale (8-16 months) concentrate mainly over the Pacific Ocean, while the corresponding spatial patterns progressively disappear when moving toward longer time-scales. Published under license by AIP Publishing. Y1 - 2019 U6 - https://doi.org/10.1063/1.5095565 SN - 1054-1500 SN - 1089-7682 VL - 29 IS - 6 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 - Bronstert, Axel A1 - Agarwal, Ankit A1 - Boessenkool, Berry A1 - Crisologo, Irene A1 - Fischer, Madlen A1 - Heistermann, Maik A1 - Koehn-Reich, Lisei A1 - Andres Lopez-Tarazon, Jose A1 - Moran, Thomas A1 - Ozturk, Ugur A1 - Reinhardt-Imjela, Christian A1 - Wendi, Dadiyorto T1 - Forensic hydro-meteorological analysis of an extreme flash flood BT - the 2016-05-29 event in Braunsbach, SW Germany JF - The science of the total environment : an international journal for scientific research into the environment and its relationship with man N2 - The flash-flood in Braunsbach in the north-eastern part of Baden-Wuerttemberg/Germany was a particularly strong and concise event which took place during the floods in southern Germany at the end of May/early June 2016. This article presents a detailed analysis of the hydro-meteorological forcing and the hydrological consequences of this event. A specific approach, the "forensic hydrological analysis" was followed in order to include and combine retrospectively a variety of data from different disciplines. Such an approach investigates the origins, mechanisms and course of such natural events if possible in a "near real time" mode, in order to follow the most recent traces of the event. The results show that it was a very rare rainfall event with extreme intensities which, in combination with catchment properties, led to extreme runoff plus severe geomorphological hazards, i.e. great debris flows, which together resulted in immense damage in this small rural town Braunsbach. It was definitely a record-breaking event and greatly exceeded existing design guidelines for extreme flood discharge for this region, i.e. by a factor of about 10. Being such a rare or even unique event, it is not reliably feasible to put it into a crisp probabilistic context. However, one can conclude that a return period clearly above 100 years can be assigned for all event components: rainfall, peak discharge and sediment transport. Due to the complex and interacting processes, no single flood cause or reason for the very high damage can be identified, since only the interplay and the cascading characteristics of those led to such an event. The roles of different human activities on the origin and/or intensification of such an extreme event are finally discussed. (C) 2018 Elsevier B.V. All rights reserved. KW - Flash flood analysis KW - Forensic disaster analysis KW - Radar rainfall data KW - Extreme discharge data KW - Extreme event Y1 - 2018 U6 - https://doi.org/10.1016/j.scitotenv.2018.02.241 SN - 0048-9697 SN - 1879-1026 VL - 630 SP - 977 EP - 991 PB - Elsevier CY - Amsterdam 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 - Shukla, Roopam A1 - Agarwal, Ankit A1 - Sachdeva, Kamna A1 - Kurths, Jürgen A1 - Joshi, P. K. T1 - Climate change perception BT - an analysis of climate change and risk perceptions among farmer types of Indian Western Himalayas JF - Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change N2 - Climate change and variability have created widespread risks for farmers’ food and livelihood security in the Himalayas. However, the extent of impacts experienced and perceived by farmers varies, as there is substantial diversity in the demographic, social, and economic conditions. Therefore, it is essential to understand how farmers with different resource-endowment and household characteristics perceive climatic risks. This study aims to analyze how farmer types perceive climate change processes and its impacts to gain insight into locally differentiated concerns by farming communities. The present study is based in the Uttarakhand state of Indian Western Himalayas. We examine farmer perceptions of climate change and how perceived impacts differ across farmer types. Primary household interviews with farming households (n = 241) were done in Chakrata and Bhikiyasian tehsil in Uttarakhand, India. In addition, annual and seasonal patterns of historical data of temperature (1951–2013) and precipitation (1901–2013) were analyzed to estimate trends and validate farmers’ perception. Using statistical methods farmer typology was constructed, and five unique farmer types are identified. Majority of respondents across all farmer types noticed a decrease in summer and winter precipitation and an increase in summer temperature. Whereas the perceptions of impacts of climate change diverged across farmer types, as specific farmer types exclusively experienced few impacts. Impact of climatic risks on household food security and income was significantly perceived stronger by low-resource-endowed subsistence farmers, whereas the landless farmer type exclusively felt impacts on the communities social bond. This deeper understanding of the differentiated perception of impacts has strong implications for agricultural and development policymaking, highlighting the need for providing flexible adaptation options rather than specific solutions to avoid inequalities in fulfilling the needs of the heterogeneous farming communities. Y1 - 2018 U6 - https://doi.org/10.1007/s10584-018-2314-z SN - 0165-0009 SN - 1573-1480 VL - 152 IS - 1 SP - 103 EP - 119 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Agarwal, Ankit A1 - Maheswaran, Rathinasamy A1 - Kurths, Jürgen A1 - Khosa, R. T1 - Wavelet Spectrum and Self-Organizing Maps-Based Approach for Hydrologic Regionalization -a Case Study in the Western United States JF - Water Resources Management N2 - Hydrologic regionalization deals with the investigation of homogeneity in watersheds and provides a classification of watersheds for regional analysis. The classification thus obtained can be used as a basis for mapping data from gauged to ungauged sites and can improve extreme event prediction. This paper proposes a wavelet power spectrum (WPS) coupled with the self-organizing map method for clustering hydrologic catchments. The application of this technique is implemented for gauged catchments. As a test case study, monthly streamflow records observed at 117 selected catchments throughout the western United States from 1951 through 2002. Further, based on WPS of each station, catchments are classified into homogeneous clusters, which provides a representative WPS pattern for the streamflow stations in each cluster. KW - Wavelet power spectrum KW - Regionalization KW - Ungauged catchments KW - K-means technique KW - Self-organizing map Y1 - 2016 U6 - https://doi.org/10.1007/s11269-016-1428-1 SN - 0920-4741 SN - 1573-1650 VL - 30 SP - 4399 EP - 4413 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Ozturk, Ugur A1 - Wendi, Dadiyorto A1 - Crisologo, Irene A1 - Riemer, Adrian A1 - Agarwal, Ankit A1 - Vogel, Kristin A1 - Andres Lopez-Tarazon, Jose A1 - Korup, Oliver T1 - Rare flash floods and debris flows in southern Germany JF - The science of the total environment : an international journal for scientific research into the environment and its relationship with man N2 - Flash floods and debris flows are iconic hazards inmountainous regions with steep relief, high rainfall intensities, rapid snowmelt events, and abundant sediments. The cuesta landscapes of southern Germany hardly come to mind when dealing with such hazards. A series of heavy rainstorms dumping up to 140mm in 2 h caused destructive flash floods and debris flows in May 2016. The most severe damage occurred in the Braunsbach municipality, which was partly buried by 42,000 m(3) of boulders, gravel, mud, and anthropogenic debris from the small catchment of Orlacher Bach (similar to 6 km(2)). We analysed this event by combining rainfall patterns, geological conditions, and geomorphic impacts to estimate an average sediment yield of 14,000 t/km(2) that mostly (similar to 95%) came from some 50 riparian landslides and channel-bed incision of similar to 2 m. This specific sediment yield ranks among the top 20% globally, while the intensity-duration curve of the rainstormis similarly in the upper percentile range of storms that had triggered landslides. Compared to similar-sized catchments in the greater region hit by the rainstorms, we find that the Orlacher Bach is above the 95th percentile in terms of steepness, storm-rainfall intensity, and topographic curvatures. The flash flood transported a sediment volume equal to as much as 20-40% of the Pleistocene sediment volume stored in the Orlacher Bach fan, andmay have had several predecessors in the Holocene. River control structures from 1903 and records of a debris flow in the 1920s in a nearby catchment indicate that the local inhabitants may have been aware of the debris-flow hazards earlier. Such recurring and destructive events elude flood-hazard appraisals in humid landscapes of gentle relief, and broaden mechanistic views of how landslides and debris flows contribute to shaping small and deeply cut tributaries in the southern Germany cuesta landscape. KW - Flash flood KW - Debris flow KW - Rainfall-triggered landslide KW - Hazard KW - Germany Y1 - 2018 U6 - https://doi.org/10.1016/j.scitotenv.2018.01.172 SN - 0048-9697 SN - 1879-1026 VL - 626 SP - 941 EP - 952 PB - Elsevier CY - Amsterdam 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 - 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 - 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 - 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 - THES A1 - Agarwal, Ankit T1 - Unraveling spatio-temporal climatic patterns via multi-scale complex networks T1 - Aufklärung raumzeitlicher Klimamuster über komplexe Netzwerke mit mehreren Maßstäben N2 - The climate is a complex dynamical system involving interactions and feedbacks among different processes at multiple temporal and spatial scales. Although numerous studies have attempted to understand the climate system, nonetheless, the studies investigating the multiscale characteristics of the climate are scarce. Further, the present set of techniques are limited in their ability to unravel the multi-scale variability of the climate system. It is completely plausible that extreme events and abrupt transitions, which are of great interest to climate community, are resultant of interactions among processes operating at multi-scale. For instance, storms, weather patterns, seasonal irregularities such as El Niño, floods and droughts, and decades-long climate variations can be better understood and even predicted by quantifying their multi-scale dynamics. This makes a strong argument to unravel the interaction and patterns of climatic processes at different scales. With this background, the thesis aims at developing measures to understand and quantify multi-scale interactions within the climate system. In the first part of the thesis, I proposed two new methods, viz, multi-scale event synchronization (MSES) and wavelet multi-scale correlation (WMC) to capture the scale-specific features present in the climatic processes. The proposed methods were tested on various synthetic and real-world time series in order to check their applicability and replicability. The results indicate that both methods (WMC and MSES) are able to capture scale-specific associations that exist between processes at different time scales in a more detailed manner as compared to the traditional single scale counterparts. In the second part of the thesis, the proposed multi-scale similarity measures were used in constructing climate networks to investigate the evolution of spatial connections within climatic processes at multiple timescales. The proposed methods WMC and MSES, together with complex network were applied to two different datasets. In the first application, climate networks based on WMC were constructed for the univariate global sea surface temperature (SST) data to identify and visualize the SSTs patterns that develop very similarly over time and distinguish them from those that have long-range teleconnections to other ocean regions. Further investigations of climate networks on different timescales revealed (i) various high variability and co-variability regions, and (ii) short and long-range teleconnection regions with varying spatial distance. The outcomes of the study not only re-confirmed the existing knowledge on the link between SST patterns like El Niño Southern Oscillation and the Pacific Decadal Oscillation, but also suggested new insights into the characteristics and origins of long-range teleconnections. In the second application, I used the developed non-linear MSES similarity measure to quantify the multivariate teleconnections between extreme Indian precipitation and climatic patterns with the highest relevance for Indian sub-continent. The results confirmed significant non-linear influences that were not well captured by the traditional methods. Further, there was a substantial variation in the strength and nature of teleconnection across India, and across time scales. Overall, the results from investigations conducted in the thesis strongly highlight the need for considering the multi-scale aspects in climatic processes, and the proposed methods provide robust framework for quantifying the multi-scale characteristics. N2 - Das Klima ist ein komplexes Zusammenspiel verschiedener Mechanismen und Rückkopplungen auf mehreren zeitlichen und räumlichen Skalen. Viele Studien beschäftigten sich mit dem diesem System, nur wenige jedoch konzentrierten sich auf das Multiskalenverhalten des Klimas. Vor allem die bis dato verfügbaren Techniken schränkten eine vertiefte Analyse der Klimavariabilität auf unterschiedlichen Skalen ein. Von großen Interesse in der aktuellen Klimaforschung sind Extremereignisse und plötzliche Veränderungen, welche höchstwahrscheinlich aus dem Zusammenwirken von Prozessen auf unterschiedlichen Skalen hervorgehen. Um Stürme, wiederkehrende Wetterlagen, jahreszeitliche Phänomene wie El Niño, Fluten, Dürren oder Klimaschwankungen über Jahrzehnte besser zu verstehen oder sogar vorhersagen zu können, müssen wir deren Dynamik auf unterschiedlichen Skalen quantifizieren. In der vorliegenden Arbeit werden Mittel und Wege präsentiert um das Zusammenwirken auf verschiedenen Skalen im Klimasystem besser zu verstehen und zu quantifizieren. Im ersten Teil dieser Arbeit stelle ich zwei Methoden, multi-scale event synchronization (MSES) und wavelet multi-scale correlation (WMC) vor, welche skalenspezifischen Eigenschaften in klimatischen Prozessen abbilden. Die vorgestellte Methode wurde mit mehreren synthetischen und realen Zeitreihen getestet um ihre Anwendbarkeit und Reproduzierbarkeit zu überprüfen. Die Ergebnisse zeigen, dass beide Methoden Beziehungen auf unterschiedlichen zeitlichen Skalen detaillierter als traditionelle Ansätze abbilden können. Im zweiten Teil dieser Arbeit bilde ich klimatische Netzwerke mithilfe eines Maßes zur Ähnlichkeit auf Multiskalen. Dabei untersuche ich die Entwicklung von räumlichen Beziehungen um klimatische Prozesse auf mehreren Zeitskalen zu verstehen. Die Methoden WMC und MSES werden zusammen mit komplexen Netzwerken auf zwei Datensätze angewendet. In der ersten Anwendung werden klimatische Netzwerke mit WMC für univariate globale Meeresoberflächentemperaturen gebildet. Auf unterschiedlichen Zeitskalen sollen dabei kurze und lange Fernwirkungen, welche andernfalls auf einer einzigen Zeitskale unerkannt blieben, entdeckt werden. In diesem Klimanetzwerk ließ sich eine starke Variabilität über die Zeit feststellen, was auf eine skalenfreie und kleinräumige Netzstruktur auf großem, beziehungsweise kleinem Maßstab schließen lässt. Weitere Untersuchungen von Klimanetzwerken auf unterschiedlichen Zeitskalen zeigte (i) hohe Variabilität und Co-Variabilität in Regionen, und (ii) Fernbeziehungen auf kurzen und langen Entfernungen mit variabler räumlicher Distanz. Die Ergebnisse bestätigen bekannte physikalischen Wechselwirkungen und daher auch die Stärken meines Ansatzes. Dadurch ergeben sich neue Einblicke in die Klimatologie von Ozeanen, sodass beispielsweise konvektive Prozesse in der Atmosphäre eine Abhängigkeit über weite Entfernungen aufweisen können. In der zweiten Anwendung verwendeten wir das von mir entwickelte, nicht-lineare MSES Ähnlichkeitsmaß um multivariate Fernbeziehungen zwischen Starkniederschlägen und klimatischen Mustern über Indien zu quantifizieren. Unsere Ergebnisse bestätigen signifikante, nicht-lineare Einflüsse, welche von traditionellen Methoden bisher unzureichend abgebildet wurden. Des Weiteren fanden wir deutliche Schwankungen in der Stärke und in der Ausprägung von Fernbeziehungen über Indien und über Zeitskalen. Zusammenfassend zeigen die Ergebnisse dieser Fallstudien, dass Multiskalen in Klimaprozessen entschieden berücksichtigt werden müssen und dass der entwickelte methodische Rahmen adäquat die charakteristischen Prozesse quantifizieren kann. KW - complex network KW - wavelet KW - climate global and local patterns KW - extreme events KW - multiscale network KW - event synchronization KW - komplexes Netzwerk KW - Wavelet KW - globale und lokale Muster des Klimas KW - extreme Ereignisse KW - Multiskalen Netzwerk KW - Ereignissynchronisation Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-423956 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 - 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 - 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 - Guntu, Ravikumar A1 - Banerjee, Abhirup A1 - Gadhawe, Mayuri Ashokrao A1 - Marwan, Norbert T1 - A complex network approach to study the extreme precipitation patterns in a river basin JF - Chaos : an interdisciplinary journal of nonlinear science N2 - The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes. Y1 - 2022 U6 - https://doi.org/10.1063/5.0072520 SN - 1054-1500 SN - 1089-7682 VL - 32 IS - 1 PB - American Institute of Physics CY - Woodbury, NY ER - TY - JOUR A1 - Vogel, Kristin A1 - Ozturk, Ugur A1 - Riemer, Adrian A1 - Laudan, Jonas A1 - Sieg, Tobias A1 - Wendi, Dadiyorto A1 - Agarwal, Ankit A1 - Roezer, Viktor A1 - Korup, Oliver A1 - Thieken, Annegret T1 - Die Sturzflut von Braunsbach am 29. Mai 2016 – Entstehung, Ablauf und Schäden eines „Jahrhundertereignisses“ T1 - The Braunsbach Flashflood of Mai 29th, 2016-Origin, Pathways and Impacts of an Extreme Hydro-Meteorological Event BT - Teil 2: Geomorphologische Prozesse und Schadensanalyse BT - Part 2: Geomorphological Processes and Damage Analysis JF - Hydrologie und Wasserbewirtschaftung N2 - Am Abend des 29. Mai 2016 wurde der Ort Braunsbach im Landkreis Schwäbisch-Hall (Baden-Württemberg) von einer Sturzflut getroffen, bei der mehrere Häuser stark beschädigt oder zerstört wurden. Die Sturzflut war eine der Unwetterfolgen, die im Frühsommer 2016 vom Tiefdruckgebiet Elvira ausgelöst wurden. Der vorliegende Bericht ist der zweite Teil einer Doppelveröffentlichung, welche die Ergebnisse zur Untersuchung des Sturzflutereignisses im Rahmen des DFG-Graduiertenkollegs “Naturgefahren und Risiken in einer sich verändernden Welt” (NatRiskChange, GRK 2043/1) der Universität Potsdam präsentiert. Während Teil 1 die meteorologischen und hydrologischen Ereignisse analysiert, fokussiert Teil 2 auf die geomorphologischen Prozesse und die verursachten Gebäudeschäden. Dazu wurden Ursprung und Ausmaß des während des Sturzflutereignisses mobilisierten und in den Ort getragenen Materials untersucht. Des Weiteren wurden zu 96 betroffenen Gebäuden Daten zum Schadensgrad sowie Prozess- und Gebäudecharakteristika aufgenommen und ausgewertet. Die Untersuchungen zeigen, dass bei der Betrachtung von Hochwassergefährdung die Berücksichtigung von Sturzfluten und ihrer speziellen Charakteristika, wie hoher Feststofftransport und sprunghaftes Verhalten insbesondere in bebautem Gelände, wesentlich ist, um effektive Schutzmaßnahmen ergreifen zu können. N2 - A severe flash flood event hit the town of Braunsbach (Baden-Wurttemberg, Germany) on the evening of May 29, 2016, heavily damaging and destroying several dozens of buildings. It was only one of several disastrous events in Central Europe caused by the low-pressure system "Elvira". The DFG Graduate School "Natural hazards and risks in a changing world" (NatRiskChange, GRK 2043/1) at the University of Potsdam investigated the Braunsbach flash flood as a recent showcase for catastrophic events triggered by severe weather. This contribution is part two of a back-to-back publication on the results of this storm event. While part 1 analyses the meteorological and hydrological situation, part 2 concentrates on the geomorphological aspects and damage to buildings. The study outlines the origin and amount of material that was mobilized and transported into the town by the flood, and analyses damage data collected for 96 affected buildings, describing the degree of impact, underlying processes, and building characteristics. Due to the potentially high sediment load of flash floods and their non-steady and non-uniform flow especially in built-up areas, the damaging processes differ from those of clear water floods. The results underline the need to consider flash floods and their specific behaviour in flood hazard assessments. KW - flash flood KW - flood risk KW - damaging processes KW - debris flow KW - erosion KW - landslides KW - Braunsbach KW - Sturzflut KW - Hochwassergefährdung KW - Schadensprozesse KW - Erosion KW - Hangrutschungen Y1 - 2017 U6 - https://doi.org/10.5675/HyWa_2017,3_2 SN - 1439-1783 VL - 61 IS - 3 SP - 163 EP - 175 PB - Bundesanst. für Gewässerkunde CY - Koblenz ER - TY - RPRT A1 - Agarwal, Ankit A1 - Boessenkool, Berry A1 - Fischer, Madlen A1 - Hahn, Irene A1 - Köhn, Lisei A1 - Laudan, Jonas A1 - Moran, Thomas A1 - Öztürk, Ugur A1 - Riemer, Adrian A1 - Rözer, Viktor A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Wendi, Dadiyorto A1 - Bronstert, Axel A1 - Thieken, Annegret T1 - Die Sturzflut in Braunsbach, Mai 2016 T1 - The flash flood of Braunsbach, May 2006 BT - eine Bestandsaufnahme und Ereignisbeschreibung BT - a hydrological survey and event analysis N2 - Im Graduiertenkolleg NatRiskChange der Universität Potsdam und anderen Forschungseinrichtungen werden beobachtete sowie zukünftig mögliche Veränderungen von Naturgefahren untersucht. Teil des strukturierten Doktorandenprogramms sind sogenannte Task-Force-Einsätze, bei denen die Promovierende zeitlich begrenzt ein aktuelles Ereignis auswerten. Im Zuge dieser Aktivität wurde die Sturzflut vom 29.05.2016 in Braunsbach (Baden-Württemberg) untersucht. In diesem Bericht werden erste Auswertungen zur Einordnung der Niederschläge, zu den hydrologischen und geomorphologischen Prozessen im Einzugsgebiet des Orlacher Bachs sowie zu den verursachten Schäden beleuchtet. Die Region war Zentrum extremer Regenfälle in der Größenordnung von 100 mm innerhalb von 2 Stunden. Das 6 km² kleine Einzugsgebiet hat eine sehr schnelle Reaktionszeit, zumal bei vorgesättigtem Boden. Im steilen Bachtal haben mehrere kleinere und größere Hangrutschungen über 8000 m³ Geröll, Schutt und Schwemmholz in das Gewässer eingetragen und möglicherweise kurzzeitige Aufstauungen und Durchbrüche verursacht. Neben den großen Wassermengen mit einer Abflussspitze in einer Größenordnung von 100 m³/s hat gerade die Geschiebefracht zu großen Schäden an den Gebäuden entlang des Bachlaufs in Braunsbach geführt. N2 - The DFG graduate school “Natural Hazards and Risks in a Changing World” (NatRiskChange), which is located at the University of Potsdam and its partner institutions, studies previous as well as ongoing and potential future changes in the risk posed by natural hazards. The education program includes so-called task force activities, where the PhD students conduct a rapid event assessment directly after the occurrence of a hazardous natural event. Within this context the flash flood that hit the village Braunsbach (Baden-Württemberg, Germany) at May 29th, 2016 was investigated. This report summarizes first results describing the rainfall amount and intensities as well as hydrological and geomorphological processes in the corresponding catchment area of the Orlacher Bach. Further, the damages caused in Braunsbach are investigated. Rainfall intensity measures documented extreme precipitation in the area of Braunsbach with a cumulative amount of about 100 mm within 2 hours. The small catchment area, with a size of 6 km², has a small response time, especially under pre-saturated soil conditions. Several landslides, that occurred at the steep slopes of the river valley, transported more than 8000 m³ of gravel, debris and organic material into the water runoff. They may have caused temporal blockades, that collapsed after a certain amount of water accumulated. In addition to the high discharge, with peak values in the order of 100 m³/s, the high sediment content of the flash flood is mainly responsible for the large damages caused to the buildings in Braunsbach. KW - Sturzflut KW - Naturgefahren KW - Extremniederschlag KW - Schadensabschätzung KW - Hangrutschungen KW - flash flood KW - natural hazards KW - extreme precipitation KW - damage assessment KW - landslides Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-394881 ER -