N. Marwan:
Recurrence analysis of complex systems,
Dynamics Days Europe 2024LXVII Congreso Nacional De Fisica, Mini symposium "The Recurrence Plot Applied to Physics",
Chihuahua (Mexico),
Oct 7, 2024,
Talk.
» Abstract
Recurrence is a fundamental feature in numerous real-world processes, observed across all temporal and spatial scales, such as in celestial mechanics, alternating sediment layers, thermoacoustic oscillation, and cardiac variability. Analysing recurrence properties (such as by frequency analysis), offers deeper insights into underlying dynamical processes. A rather novel approach to studying recurrences is the recurrence plot and its quantification, based on dynamical systems theory. This talk introduces the basic concepts and key extensions of this method, demonstrating its application to diverse research questions through selected examples.
M. Mannone, P. Fazio, N. Marwan:
An Operator Acting on the Brain Network and Provoking Disease: A Conceptual Model and a First Data-Based Application,
Dynamics Days Europe 2024,
Bremen (Germany),
Aug 2, 2024,
Talk.
» Abstract
The complexity of our brains can be described as a multilayer network, from neurons, to the neural agglomerates, to lobes. Neurological diseases are often related to malfunctions in the brain network. We propose a conceptual model of the brain, where the disease can be modeled as the result of an operator affecting and disrupting the brain-network organization, called “K-operator” (from “Krankheit,” German for “disease”).
In our approach, the network channel model is adapted from telecommunications, where the action of the K-operator corresponds to an alteration of the healthy communication-structure between neuronal agglomerates. The potential of this novel approach is tested by quantitatively modelling the operator with real-data considering the Parkinson disease. We use data from the dataset of Parkinson’s Progression Markers Initiative (PPMI) upon concession by the University of Southern California. The networks are reconstructed from fMRI analysis, resulting in a matrix acting on the healthy brain and giving as output the diseased brain. We finally decompose the K-operator into the tensor product of its submatrices and we are able to assess its action on each one of the regions of interest (ROI) characterizing the brain for the specific considered samples. More interestingly, this application confirms the feasibility of the proposed analytic technique. Further research development can compare operators for different patients and for different diseases, looking for commonalities and aiming to develop a comprehensive theoretical approach.
T. Braun, S. M. Vallejo-Bernal, N. Marwan, J. Kurths, A. Días-Guilera, L. Gimeno, S. Sippel, M. Mahecha:
Earth Surface Impacts of Hydrological Extremes along Global Atmospheric River Networks: The ARNETLAB project,
International Atmospheric Rivers Conference 2024,
UC San Diego (USA),
Jun 26, 2024,
Talk.
» Abstract
As the global water cycle intensifies, the Earth’s surface will experience more extreme weather and climate events. Increasingly intense and frequent hydrological extremes, such as heavy precipitation events (HPEs), will result in unprecedented alteration of terrestrial ecosystem processes and more severe societal impacts. Prior research has successfully catalogued weather phenomena that act as drivers of hydrological extremes, such as atmospheric rivers (ARs). Recent advances in the catalogization of ARs offer great predictive potential for hydrological extremes and their impacts on the Earth’s land surface. However, few approaches consider AR transport patterns at a global scale with a suitable methodological framework. Furthermore, our understanding of how controls of hydrological extremes propagate to changes in land-surface dynamics remains limited. I will introduce the new “ARNETLAB” project which aims to address these research gaps using tools from complexity science. We propose that the complex interplay between ARs, HPEs and ecosystem impacts can be disentangled using a complex network approach. Complex networks are a powerful paradigm that encodes interactions between the system’s units through interlinked nodes. Recent applications illustrate that complex networks reveal novel insights into climate teleconnection patterns, synchronization of extremes and vegetation-atmosphere feedbacks. I will showcase preliminary findings on a novel transport network method for global AR trajectories. The introduced framework will allow us to link AR transport patterns to synchronized HPEs along their tracks and, in turn, to their impacts on terrestrial surface processes. Moreover, longer-term past, present and projected future changes in the network characteristics and associated synchronised extremes will be analysed. Using the novel PIKART catalogue of global ARs, we will go beyond coastal AR impacts by devoting special attention to their inland penetration. This talk demonstrates how tools from complexity science open up exciting research avenues to study the dynamics and impacts of ARs.
S. M. Vallejo-Bernal, T. Braun, N. Marwan, J. Kurths:
The PIKART Catalog: A Global and Comprehensive Compilation of Atmospheric Rivers,
International Atmospheric Rivers Conference 2024,
UC San Diego (USA),
Jun 26, 2024,
» Poster (PDF, 0.00P)
.
» Abstract
Detection and tracking of atmospheric rivers (ARs) are fundamental tasks to study and understand their lifecycles, dynamics, and impacts. However, addressing these tasks globally comes along with substantial challenges caused by regionally and temporally varying climate conditions. Therefore, most available AR catalogs have regional extent. Yet, only AR catalogs with global extension record large-scale heterogeneities in AR transport. Building on previously published approaches, we designed a thorough detection-, tracking- and post-processing scheme from which we compile the novel PIKART catalog of ARs. Contrary to traditional methods that detect AR conditions by thresholding the atmospheric moisture transport, PIKART is based on the anomalous vapor transport characteristics of ARs. Furthermore, we extended previous tracking strategies to allow for physically-sound temporal gaps in AR trajectories, resulting in improved representation of long- lived ARs. PIKART is a global compilation of AR trajectories and AR conditions that covers 83 years (1940-2022) with 6-hourly resolution and a high spatial resolution of 0.5°. It extends the scope of previous catalogs by providing secondary AR properties, e.g., a novel index of inland penetration, land-intersection locations, and AR levels. Comparing PIKART with other global AR catalogs, we found overall consistency. However, we also discovered considerable differences in lifecycles and land-falling locations, especially accentuated for long-lived AR trajectories as well as tropical and polar AR conditions. Exploring the applicability of PIKART to study AR lifecycles, land-falling locations, impacts, and long-term trends, we revealed i) additional AR hotspots (particularly in the tropics), ii) inland penetration into less-studied regions (e.g., north-western Africa), iii) exposure to considerable AR impacts in less-studied continents (South/East Asia and Oceania), and iv) a poleward shift of southern hemispheric ARs. We are happy to introduce and share the PIKART catalog with the AR community and hope that it will provide a valuable and alternative resource for future studies in AR science.
S. M. Vallejo-Bernal, F. Wolf, L. Luna, N. Boers, T. Braun, N. Marwan, J. Kurths:
Using Complexity Science to Reveal the Dynamics and Impacts of Atmospheric Rivers in North America,
International Atmospheric Rivers Conference 2024,
UC San Diego (USA),
Jun 25, 2024,
Talk.
» Abstract
Recently, atmospheric rivers (ARs) have been identified as primary drivers of heavy precipitation events (HPEs) and precipitation-induced disasters in Western North America. Although it is undisputable that ARs trigger HPEs along the coastline when making landfall, the spatial and temporal extension of their lag-dependent impacts following landfall remains unresolved. Furthermore, while the association of ARs with floods, avalanches, and extreme winds has received substantial interest, the causal relation between ARs and precipitation-induced landslides is yet to be verified and quantified. Tools from complexity science provide great opportunities to contribute to these research gaps, where non-linear and time-delayed interactions need to be carefully considered. In this talk, we briefly introduce the concepts of event synchronization, climate networks, and probabilistic attribution, which are the building blocks of a powerful methodological framework to study AR dynamics and impacts. Our results reveal that inland-penetrating ARs are the drivers of cascading HPEs evolving in a temporally coherent manner from the Western Coast of North America to Canada. Moreover, synchronization concepts allow us to discover characteristic synoptic patterns and seasonality of these ARs. Using probabilistic attribution and non-linear time series analysis, we demonstrate that precipitation from land-falling ARs preceded more than 80% of days with precipitation-induced landslides in WNA between 1996 and 2018. With these two applications, extendable to broader regional and global analyses, we show that complexity science is a robust tool for exploring land-atmosphere couplings and precipitation-induced hazards. The complexity science machinery contributes crucial insights to enhance our understanding of ARs, improve forecasting accuracy and bolster mitigation strategies.
S. M. Vallejo-Bernal, F. Wolf, L. Luna, N. Boers, N. Marwan, J. Kurths:
Probabilistic Attribution and Time Series Anal- ysis to Investigate Atmospheric Drivers of Precipitation-Induced Disasters,
SIAM Conference on Mathematics of Planet Earth (MPE24),
Portland, Oregon (USA),
Jun 11, 2024,
Talk.
» Abstract
Mechanisms of atmospheric moisture transport, such as atmospheric rivers (ARs) and extratropical cyclones, are primary drivers of heavy precipitation in the mid-latitudes. While crucial for freshwater supply, they also trigger precipitation-induced disasters (PIDs) such as floods and landslides. Here, we introduce a methodological approach that combines stochastic climate theory and time series analysis to quantify the strength, directionality, and significance of the non-linear relation between atmospheric moisture transport events (AMTEs) and PIDs. Employing probabilistic attribution, we reveal the spatial extent over which AMTEs cause precipitation upon landfall. Subsequently, we use event coincidence analysis, a non-linear measure specially tailored for event time series, to quantify the precedence relation between precipitation released by AMTEs and PIDs. We determine the significance of our findings through Monte Carlo experiments, hypothesis testing, and sensitivity analysis. Applying our methodological approach, we demonstrate that precipitation from land-falling ARs was the primary trigger of precipitationinduced landslides in Western North America between 1996 and 2018. Our approach, extendable to broader regional and global analyses, is a robust tool for exploring landatmosphere couplings and precipitation-induced hazards, contributing crucial insights to improve forecasting accuracy and bolster mitigation strategies.
J. Wassmer, S. Bryant, N. Marwan, M. Pregnolato, B. Merz:
Hidden Vulnerabilities in Emergency Response Post-Flood Disasters,
3rd International Conference on Natural Hazards and Risks in a Changing World,
Amsterdam (The Netherlands),
Jun 12, 2024,
Talk.
» Abstract
In this study, we address the escalating risks to emergency response systems posed by flood disasters, exacerbated by anthropogenic climate change. We present a novel method for analysing the impact of natural hazards on transport networks, recognising the significant societal and environmental impacts these events can have, particularly in terms of disruption to transport infrastructure. The method, rooted in the gravity model of travel, provides a unique lens through which we examine the stability of transport networks following a disaster. Specifically, we apply this approach to understand the vulnerability of the emergency response system in Germany to flooding.
To simulate flood scenarios in Germany's major river basins, we use a comprehensive regional flood model. This model includes a weather generator for realistic rainfall prediction, a hydrological model for flow conversion and a hydrodynamic model to simulate channel dynamics and overtopping. This allows us to assess potential damage to road infrastructure, including the destruction of bridges and roads, which can lead to critical traffic congestion and hamper emergency response, even in areas far from the flood epicentre. Our findings reveal non-intuitive vulnerabilities for hospitals that are not in the immediate vicinity of the flood event.
N. Marwan:
Recurrence analysis of complex systems in geosciences,
Seminar Geophysics, Institute for Geosciences, Uni Potsdam,
Potsdam (Germany),
Jun 18, 2024,
Lecture.
S. M. Vallejo-Bernal, F. Wolf, N. Boers, N. Marwan, J. Kurths:
The role of atmospheric rivers in the spatio-temporal organization of heavy precipitation events over North America,
808th WE-Heraeus-Seminar on Extreme Events: Identification, Analysis and Prediction,
Bad Honnef (Germany),
Apr 26, 2024,
Talk.
» Abstract
Atmospheric rivers (ARs) are transient corridors of extensive water vapor transport in the lower atmosphere that play a crucial role in the distribution of freshwater but can also cause natural and economic damage by facilitating heavy precipitation events (HPEs). Recent studies have demonstrated that ARs trigger HPEs along the western coast of North America (NA) when making landfall. However, the spatial and temporal extension of their lag-dependent impacts following landfall remains unresolved. Here, we investigate the large-scale spatiotemporal synchronization patterns of HPEs driven by ARs in NA from 1979 to 2018. We employ daily time series of HPEs and land-falling ARs, and we use event synchronization and a complex network approach incorporating varying temporal delays to examine the evolution of spatial patterns of HPEs in the aftermath of land-falling ARs. Our analysis reveals a cascade of synchronized HPEs, triggered by strong ARs. On the first 3 days after an AR makes landfall, HPEs mostly occur and synchronize along the western coast of NA. In the subsequent days, moisture can be transported to central and eastern Canada and cause synchronized but delayed HPEs there. Analyzing the anomalies of integrated water vapor transport, geopotential height, upper-level meridional wind, and precipitation, we find atmospheric circulation patterns that are consistent with the spatiotemporal evolution of the synchronized HPEs. Revealing the role of ARs in the precipitation patterns over NA will lead to a better understanding and forecasting of inland HPEs and the effects that changing climate dynamics will have on precipitation occurrence and consequent impacts in the context of a warming atmosphere.
J. Wassmer, S. Bryant, N. Marwan, M. Pregnolato, B. Merz:
Hidden Vulnerabilities in Emergency Response Post-Flood Disasters,
808th WE-Heraeus-Seminar on Extreme Events: Identification, Analysis and Prediction,
Bad Honnef (Germany),
Apr 24, 2024,
Talk.
» Abstract
In this study, we address the escalating risks to emergency response systems posed by flood disasters, exacerbated by anthropogenic climate change. We present a novel method for analysing the impact of natural hazards on transport networks, recognising the significant societal and environmental impacts these events can have, particularly in terms of disruption to transport infrastructure. The method, rooted in the gravity model of travel, provides a unique lens through which to examine the stability of transport networks following a disaster. Specifically, we apply this approach to understand the vulnerability of the emergency response system in Germany to flooding.
To simulate flood scenarios in Germany's major river basins, we use a comprehensive regional flood model. This model includes a weather generator for realistic rainfall prediction, a hydrological model for flow conversion and a hydrodynamic model to simulate channel dynamics and overtopping. This allows us to assess potential damage to road infrastructure, including the destruction of bridges and roads, which can lead to critical traffic congestion and hamper emergency response, even in areas far from the flood epicentre. Our findings reveal non-intuitive vulnerabilities for hospitals that are not in the immediate vicinity of the flood event.
Our research highlights the need for targeted road repair and reinforcement strategies that focus on maintaining traffic flow for emergency response. By providing new insights into the resilience of transport networks, this study contributes to the wider discourse on mitigating the economic and social costs of future extreme weather events.
M. L. Fischer, N. Marwan, V. Foerster, F. Schaebitz, E. M. L. Scerri, W. Schwanghart, S. Kaboth-Bahr, M. H. Trauth:
Linear and non-linear Time Series Analysis of pan-African Hydroclimate spanning the past 1,200 kyr,
EGU General Assembly,
Vienna (Austria),
Apr 15, 2024,
DOI:10.5194/egusphere-egu24-12155,
Poster.
» Abstract
The time between 1,200 kyr BP and today includes the Mid-Pleistocene Transition, the Mid-Bruhnes Event, and the late Pleistocene. The Early-Mid Pleistocene Transition ( 920 kyrs BP) is one of the most dramatic shifts in high-latitude climate and marked by the onset of the strong 100 kyr glacial-interglacial cycles. The Mid-Bruhnes Event marks a significant increase in the amplitude of the glacial-interglacial cycles. It has been identified mostly in marine sediments and Antarctic ice cores, but it is currently discussed whether it was a globally synchronous phenomenon, including the African continent. Marine records suggest a shift towards increased aridity in parts of Africa, and terrestrial records from eastern Africa indicate a generally wet climate, possibly with a transition from stable to unstable, as suggested by the Olorgesailie record.
At this time, robust Australopithecines went extinct, and only the genus Homo survived as H. ergaster, which ultimately led to the emergence of our own species, H. sapiens. The time vector also includes the second major expansion wave of H. ergaster out of Africa (1.39–0.9 Ma, after the first wave at 1.9–1.4 Ma), possibly through the Sinai land bridge, but expansions through the Gibraltar strait and via the Bab el-Mandeb strait and into the southern Arabian Peninsula are also subject to lively discussed.
Here, we present the first insights into a comprehensive linear and non-linear analysis of five prominent records, which are (1) the dust record from ODP site 659 from western Africa, (2) the dust record from the Arabian Sea from ODP site 721/722, (3) the river runoff record from MD96-2048, (4) the combined dust and river runoff wetness index from ODP site 967, and (5) the south-western European ICDP record from Lake Ohrid. We use correlation metrics, such as the windowed Spearman correlation coefficient, to test for spatiotemporal synchronicity, asynchronicity, and possible interferences with the hominin fossil record. Furthermore, we use non-linear analysis, such as recurrence plots and recurrence quantification analysis, to test whether prominent climate transitions or spatiotemporal shifts in the fossil record are in temporal alignment with recurrence-based insights.
S. Gupta, A. Banerjee, N. Marwan, D. Richardson, L. Magnusson, J. Kurths, F. Pappenberger:
Spatially coherent structure of forecast errors – A complex network approach,
EGU General Assembly,
Vienna (Austria),
Apr 15, 2024,
DOI:10.5194/egusphere-egu24-12314,
Talk.
» Abstract
The quality of weather forecasts has improved considerably in recent decades as models can better represent the complexity of the Earth’s climate system, benefitting from assimilation of comprehensive Earth observation data and increased computational resources. Analysis of errors is an integral part of numerical weather prediction to produce better quality forecasts. The Earth’s climate, being a highly complex interacting system, often gives rise to significant statistical relationships between the states of the climate at distant geographical locations. Likewise, correlated errors in forecasting the state of the system can arise from predictable relationships between forecast errors at various regions resulting from an underlying systematic or random process. Estimation of error correlations is very important for producing quality forecasts and is a key issue for data assimilation. However, the size of the corresponding correlation matrix is larger than what is possible to represent on geographical maps in order to diagnose its full spatial variation.
In this work, we propose an approach based on complex network theory to quantitatively study the spatiotemporal coherent structures of medium-range forecast errors of different climate variables. We demonstrate that the spatial variation of the network measures computed from the error correlation matrix can provide insights into the origin of forecast errors in a climate variable by identifying spatially coherent patterns of regions having common sources of error. Notably, the network topology of forecast errors of a climate variable is significantly different from those of random networks corresponding to a deterministic phenomenon which the model fails to simulate adequately. This is especially important to reveal the spatial heterogeneity of the errors – for example, the forecast errors of outgoing long-wave radiation in tropical regions can be correlated across very long distances, indicating an underlying climate mechanism as the source of the error. Additionally, we highlight that these structures of forecast errors may not always be directly derivable from the spatiotemporal co-variability pattern of the corresponding climate variable, contrary to the expectations that the patterns should resemble each other. We further employ other common statistical tools such as, empirical orthogonal functions, to support these findings. Our results underline the potential of complex networks as a very promising diagnostic tool to gain better understanding of the spatial variation, origin, and propagation of forecast errors.
M. H. Trauth, M. L. Fischer, V. Foerster, N. Marwan, H. M. Roberts, F. Schaebitz:
Combining orbital tuning and direct dating approaches to age-depth model development for Chew Bahir, Ethiopia,
EGU General Assembly,
Vienna (Austria),
Apr 15, 2024,
DOI:10.5194/egusphere-egu24-5046,
Poster.
» Abstract
The directly dated RRMarch2021 age model (Roberts et al., Quaternary Science Reviews, 2021) for the 290 m long composite core from Chew Bahir, southern Ethiopia, has provided a valuable chronology for long-term climate changes in northeastern Africa. However, the age model has limitations on shorter time scales (less than 1–2 precession cycles), especially in the time range <20 kyr BP and between 155–428 kyr BP. To address those constraints we developed a partially orbitally tuned age model. A comparison with the ODP Site 967 record of the wetness index from the eastern Mediterranean, 3,200 km away but connected to the Ethiopian plateau via the River Nile, suggests that the partially orbitally tuned age model offers some advantages compared to the exclusively directly dated age model, with the limitation of the reduced significance of (cross)spectral analysis results of tuned age models in cause-effect studies. The availability of this more detailed age model is a prerequisite for further detailed spatiotemporal correlations of climate variability and its potential impact on the exchange of different populations of Homo sapiens in the region.
S. M. Vallejo-Bernal, L. Luna, N. Marwan, J. Kurths:
Forecasting of Precipitation-Induced Landslides Using Atmospheric Rivers: Opportunities and Challenges,
EGU General Assembly,
Vienna (Austria),
Apr 15, 2024,
DOI:10.5194/egusphere-egu24-17215,
Talk.
» Abstract
Landslides are particularly costly disasters, causing about 4,500 fatalities and US$20 billion in damages worldwide each year. In Western North America, where intense and frequent precipitation events interact with complex topography and steep slopes, precipitation-induced landslides (PILs) are a serious geological hazard. Recently, it has been revealed that the majority of PILs in the region are triggered by precipitation from atmospheric rivers (ARs), transient channels of intense water vapor flux in the troposphere. However, the synoptic conditions differentiating landslide-triggering and non-triggering ARs remain unknown. In this study, we explore opportunities for improved landslide forecasting in Western North America using catalogs of land-falling ARs and PILs, along with ERA5 climatological data, from 1996 to 2018. First, we employ event synchronization, a non-linear measure specially tailored for event series analysis, to identify landslide-triggering ARs. Based on the AR-strength scale, which ranks ARs in levels from 1 to 5, we further characterize landslide-triggering ARs in terms of intensity and persistence. Subsequently, we spatially resolve the conditional probability of PIL occurrence given the detection of AR-attributed precipitation in the antecedent week, revealing the contribution of each AR level. Lastly, using hourly estimates of integrated water vapour transport, geopotential height, and precipitation at 0.25° spatial resolution, we differentiate the spatio-temporal evolution of synoptic conditions preceding landslide-triggering and non-landslide triggering ARs. Our results constitute a first, fundamental, and necessary step toward AR-based landslide forecasts, contributing crucial insights to improve forecasting accuracy at the short and early medium-range (1–7 days).
N. Marwan, T. Braun:
New concepts on quantifying event data,
EGU General Assembly,
Vienna (Austria),
Apr 16, 2024,
DOI:10.5194/egusphere-egu24-10258,
Talk.
» Abstract
A wide range of geoprocesses manifest as observable events in a variety of contexts, including shifts in palaeoclimate regimes, evolutionary milestones, tectonic activities, and more. Many prominent research questions, such as synchronisation analysis or power spectrum estimation of discrete data, pose considerable challenges to linear tools. We present recent advances using a specific similarity measure for discrete data and the method of recurrence plots for different applications in the field of highly discrete event data. We illustrate their potential for palaeoclimate studies, particularly in detecting synchronisation between signals of discrete extreme events and continuous signals, estimating power spectra of spiky signals, and analysing data with irregular sampling.
N. Marwan:
Advances in Recurrence Analysis for Predictive Modeling and Dynamic Classification,
EGU General Assembly,
Vienna (Austria),
Apr 15, 2024,
DOI:10.5194/egusphere-egu24-21587,
Talk invited.
» Abstract
The recurrence of similar states is a fundamental property of the processes that shape and influence our living and non-living world. There are numerous examples of geological and climatic processes on both short and long time and spatial scales, such as the regular activity of geysers within minutes, the more irregular but still recurrent occurrence of earthquakes (on time scales between weeks and years), the El Niño climate phenomenon occurring every three to five years, the glacial cycles (thousands of years), or the Milanković cycles, which periodically force climate changes up to hundreds of thousands of years. The recurrence of states in such dynamic processes generates typical recurrence patterns that can be used to detect regime changes, to classify the dynamics, or even to predict future changes. I will report on recent achievements in recurrence analysis in recent years, including methodological developments tailored for challenging data in the geosciences, such as irregularly sampled data or extreme event data. The overview includes further important and innovative developments, such as conceptual recurrence plots, ideas for parameter selection, multiscale recurrences, correction schemes, and new perspectives by combining recurrence analysis with machine learning.
N. Marwan:
Recurrence analysis for studying environmental dynamics,
CEIGRAM Seminario de Investigación, Universidad Politécnica de Madrid,
Madrid (Spain),
Feb 26, 2024,
Talk.
» Abstract
Recurrence is a ubiquitous and fundamental feature of many real-world processes, manifesting itself at all temporal and spatial scales. Examples include repeating patterns in a landscape, cycles of glaciation, epochs of geomagnetic polarity, alternating sedimentary layers, seasonal vegetation changes, and predator-prey cycles. The study of recurrence properties (such as frequency analysis) can provide profound insights into environmental processes. A rather novel approach to the study of recurrence is the so-called recurrence plot and its quantification, which is rooted in the theory of dynamical systems. In this talk I will present the basic concept and the main extensions applicable to different research questions, covering the identification of regime shifts in environmental dynamics, spatio-temporal recurrences for classification of land-use dynamics, and bivariate extensions for synchronisation/coupling analysis of palaeoclimate observations. I will also cover innovative extensions for handling event-like data and address methodological and numerical challenges.
N. Marwan, T. Braun, K. H. Kraemer,
A. Banerjee, D. Eroglu:
New Concepts for Quantifying Extreme Events Data,
(Virtual) Workshop on Complex Networks and Application to Fluid Mechanics, IIT Madras,
Chennai (India)/ Online,
Feb 19, 2024,
Talk.
» Abstract
Many processes manifest as observable extreme events in a variety of contexts, such as sudden changes in fluid flow in pipes, abrupt pressure gradients in combustion, extreme wind events, or large-scale natural hazards (earthquakes, floods, etc). Many prominent research questions, such as correlation and synchronisation analysis, or power spectrum estimation of discrete data, pose considerable challenges to linear tools. In my talk I present approaches that utilise a specific similarity measure for discrete data and the method of recurrence plots for different applications in the field of highly discrete and extreme events data. I illustrate their potential for detecting synchronisation between signals of discrete extreme events and continuous signals and for estimating power spectra of spiky signals.
G. Chopra, V. R. Unni, P. Venkateshan, S. M. Vallejo-Bernal, N. Marwan, J. Kurths, R. I. Sujith:
Classification of Tropics Based on the Spatio-Temporal Dynamics of the Intertropical Convergence Zone from a Complex Networks Perspective,
American Meteorological Society’s 37th Conference on Climate Variability and Change/ 104th Annual Meeting of the American Meteorological Society,
Baltimore (USA),
Jan 30, 2024,
Talk.
» Abstract
Using complex network analysis, we present a novel classification of the tropics based on the distinct spatio-temporal characteristics of the intertropical convergence zone (ITCZ). The ITCZ is a narrow tropical belt of high convection driven by the differential solar heating and convergence of moisture-laden trade winds from the Northern and Southern hemispheres. The ITCZ is popularly referred to as the ascending branch of the Hadley cell. As the moisture-laden winds convect to higher altitudes, condensation leads to the formation of deep clouds, resulting in high cloudiness and precipitation. In a seasonal cycle, the ITCZ migrates in the meridional direction towards the warming hemisphere. The ITCZ is a critical feature in tropical meteorology since it contributes towards maintaining the Earth-Atmosphere energy balance, and its position and structure are closely linked to the equatorial energy balance. The ITCZ has a significant impact on the society since several monsoon systems are dependent on the precipitation in the ITCZ. However, cloudiness and precipitation exhibit high variability across the ITCZ because they are sensitive to the local geophysical and meteorological phenomena. Furthermore, the extent of migration of the ITCZ and its structure are not uniform across the tropics. Therefore, classifying tropics based on the spatio-temporal dynamics of the ITCZ is a challenging yet necessary task as it will not only further our understanding of the underlying physics but also provide a basis for improving the performance of reduced-order and weather forecast models. The ITCZ dynamics is sensitive to phenomena occurring in decadal temporal scales, which enhances the complexity of the problem at hand. Complex networks are an appropriate and efficient approach to address the problem of classifying such complex systems and analysing their behavior across multiple temporal scales.
We construct functional complex networks where geographical locations are nodes that are connected if the dynamics of ITCZ at these locations are correlated. We use outgoing longwave radiation (OLR), which is a good proxy for cloudiness, to quantify the ITCZ dynamics. We consider the spatio-temporal OLR data from fifth-generation ECMWF atmospheric reanalysis dataset. The spatial resolution of the data is 1o×1o, and the temporal resolution is three hours. The correlation is estimated using Pearson’s correlation coefficient, and links are established when the correlation is higher than a predefined threshold and is statistically significant. To classify the tropics we perform community detection on the network, where communities refer to a group of nodes that are densely connected. While connections between nodes of different communities are sparse.
Community detection on the network reveals seven dominant communities corresponding to distinct annual ITCZ dynamics primarily driven by local topography, air-land interactions, and air-sea interactions. We perform community detection using Louvain’s method, which is a modularity-optimizing algorithm. The two largest communities in the network represent regions affected by the ITCZ during the northern and southern hemisphere summer seasons. These communities have dense connections, which is indicative of coherent ITCZ dynamics. The central and eastern equatorial Pacific and equatorial Atlantic oceans emerge as a separate community since these regions are affected by equatorial upwelling that suppresses convection along the equator and pushes the ITCZ northward. The Indian ocean community is found to have relatively sparse connectivity revealing that the ITCZ dynamics is incoherent and inhomogeneous over this region.
Through our analysis, we provide a simple and concise representation of the complex spatio-temporal dynamics of the ITCZ. The community structure and long-range teleconnections resulting from the spatio-temporal dynamics of the ITCZ indicate that it plays a crucial role in stabilizing the climate system. Long-range connections and localized community structure imply that perturbations from local geophysical processes are not localized but rather dispersed swiftly and uniformly across the globe. These characteristics enable suppressing prolonged hazardous weather conditions and ensure stability in the climate system.
We construct the proposed network using thirty years of data from 1991-2021. Therefore, the network is a robust benchmark to study the effects of phenomena occurring in global scales such as El-Niño Southern oscillations and also in decadal time-scales such as anthropogenic climate change. We explore the evolution of the network structure in decadal time scales and observe that connectivity in the network improves with time especially in the past two decades. We observe that certain regions in tropics where connectivity has improved corresponds to those where the ITCZ has strengthened and spatially enlarged because of increase in the surface temperature possibly due to anthropogenic factors.
N. Marwan:
New Time-series Analysis Concepts for Analysing Event Data,
Paleoclimate research on the Telegrafenberg campus and within the Geo.X network, PIK Potsdam,
Potsdam (Germany),
Jan 29, 2024,
Talk.
» Abstract
A wide range of geoprocesses manifest as observable events in a variety of contexts, including shifts in palaeoclimate regimes, evolutionary milestones, tectonic activities, and more. Many prominent research questions, such as synchronisation analysis or power spectrum estimation of discrete data, pose considerable challenges to linear tools. We present recent advances using a specific similarity measure for discrete data and the method of recurrence plots for different applications in the field of highly discrete event data. We illustrate their potential for palaeoclimate studies, particularly in detecting synchronisation between signals of discrete extreme events and continuous signals, estimating power spectra of spiky signals, and analysing data with irregular sampling.
Challenges addressed: power spectra of highly discrete data, synchronisation analysis between different types of data (e.g., extreme events and continuous data)
Open challenges: sparsity of events, parameter selection, application for synchronisation analysis
C. E. Nava-Fernandez, T. Braun, C. Pederson, B. R. S. Fox, A. Hartland, O. Kwiecien, S. N. Höpker, S. M. Bernasconi, M. Jaggi, J. C. Hellstrom, F. Gázquez, A. French, N. Marwan, A. Immenhauser, S. F. M. Breitenbach:
Seasonally resolved stalagmite reveals ENSO variability during the Mid-Holocene,
AGU 2023 Fall Neeting,
San Francisco (USA),
Dec 12, 2023,
Poster.
» Abstract
Given the urgent need to develop action plans to mitigate the impacts of global climate change, robust and accurate climate forecast models are crucial. These models rely on time series of past climate variability, especially from key regions like the tropical Pacific, where El Niño-Southern Oscillation (ENSO) events originate. ENSO dynamics significantly impact global weather pattern and more detailed empirical information can improve understanding involved processes and teleconnections. Here we present a new seasonally to sub-decadally resolved multiproxy record of past ENSO dynamics covering the Mid-Holocene (6.4-5.4 ka BP). We interpret geochemical signals of a stalagmite from Niue Island in the tropical South Pacific where local infiltration is strongly modulated by seasonal shifts of the South Pacific Convergence Zone (SPCZ) and ENSO variations.
Stalagmite C-132 is predominantly calcitic and shows laminae couplets of ca. 400 µm thickness. Annual layer couplets are formed as dark dense and pale porous calcite layers during the dry and wet season respectively. The age model of the stalagmite is constrained with 8 U/Th dates and layer counting. The record covers 1019 years between 6.4 ka and 5.4 ka. Stable oxygen and carbon isotopes, LA-ICP-MS multi-element profiles and greyscale data reveal local infiltration and regional hydrological changes that are linked to seasonal SPCZ shifts and multi-annual ENSO dynamics. Principal component analyses supports the seasonal nature of the growth layers. Wavelet spectrum analyses shows significant periodicities between 2-8 years, indicating an active ENSO system during the Mid-Holocene. A seasonality record based on the greyscale data allows us to investigate the interactions of seasonal cycle and ENSO dynamics during the Mid-Holocene, and associated changes in dry and wet season intensity and storminess.
N. Marwan:
Recurrence Quantification Analysis
for Understanding Complex Systems,
CTCS Seminar series, IIT Madras,
Chennai (India)/ Online,
Sep 25, 2023,
Talk invited.
» Abstract
Recurrence is a ubiquitous and fundamental feature in many real world processes. It is present at many scales in time and space, such as in celestial mechanics, alternating sediment layers, thermoacoustic oscillation, cardiac variability, and numerous other contexts. The study of recurrence properties (such as frequency analysis) can provide deeper insights into the underlying dynamical processes in general. A rather novel approach for the study of recurrences is the recurrence plot and its quantification, rooted in the theory of dynamical systems. In this lecture, the basic concepts and the major extensions applicable to various research questions are introduced and demonstrated. Discussed examples include the temporal change of recurrence properties for identification of regime shifts, for classification, and bivariate extensions for synchronization/coupling analysis.
N. Marwan:
Palaeoclimate research in RD4,
PIK cross-RD Paleoclimate and Long-term Climate Evolution Seminar,
Potsdam (Germany),
Sep 18, 2023,
Talk.
J. Wassmer, B. Merz, N. Marwan:
Resilience of transportation networks to road failures,
Dynamics Days Europe 2023,
Naples (Italy),
Sep 6, 2023,
Talk.
» Abstract
Damages to road infrastructure can cause disruptions in transportation and obstruct access to emergency services. With anthropogenic climate change increasing the probability of extreme weather events, such as floods or storms, the necessity for a resilient road infrastructure gets even more important.
In our research, we identify roads that play a crucial role in maintaining the stability of the transportation network. To this end we develop a framework that is built on a traffic-based centrality measure that can be interpreted as individual vehicles traversing the network. We then apply methods from the field of energy system analysis to derive the significance of each road segment in the network. The benefit of this framework is that it exclusively depends on openly accessible data sources such as OpenStreetMap, hence making it straightforward to apply and extend to different geographic locations of varying scales. As a case study, we analyse the impacts of the Ahr valley flood in Germany in 2021.
Our findings indicate that the road damages caused by the flood event led to an increase in the severity and frequency of congestion, resulting in a deterioration of the accessibility to emergency services for a substantial portion of the population. We are further able to identify roads that are especially important for the resilience of the network. A broader application of our methodology can help decision makers to reduce costs by prioritising mitigation and reconstruction measures on important road sections.
M. Mannone, N. Marwan, A. Chella, V. Seidita, A. Giacometti, P. Fazio:
Entangled Gondolas. Design of Multi-Layer Networks of Quantum-Driven Robotic Swarms,
XVII International Workshop on Artificial Life and Evolutionary Computation (WIVACE 2023),
Venice (Italy),
Sep 6, 2023,
Talk.
» Abstract
Swarms of robots can be thought of as networks, using the tools from telecommunications and network theory. A recent study designed sets of aquatic swarms of robots to clean the canals of Venice, interacting with computers on gondolas. The interaction between gondolas is one level higher in the hierarchy of communication. In other studies, pairwise communications between the robots in robotic swarms have been modeled via quantum computing. Here, we first apply quantum computing to the telecommunication-based model of an aquatic robotic swarm. Then, we use multilayer networks to model interactions within the overall system. Finally, we apply quantum entanglement to formalize the interaction and synchronization between "heads" of the swarms, that is, between gondolas.
Our study can foster new strategies for search-and-rescue robotic-swarm missions, strengthening the connection between different areas of research in physics and engineering.
A. Syta, J. Czarnigowski, P. Jaklinski, N. Marwan:
Recurrence quantificators in misfire detection in a small aircraft engine,
10th International Symposium on Recurrence Plots,
Tsukuba (Japan),
Aug 28, 2023,
Talk.
» Abstract
Misfires in internal combustion engines are a frequent issue where one or more cylinders fail to ignite properly, leading to decreased engine performance, increased fuel consumption, and potential damage. A piston failure can be perceived as a disturbance in the repeatability of the engine operation, leading to changes in non-linearity. To study the dynamic behavior of the system over time, Recurrence Quantification Analysis (RQA) is employed in nonlinear time series analysis. The technique involves creating a recurrence plot (RP) from the time series data, which illustrates the temporal evolution of the system's states. RQA is capable of detecting changes in the system's behavior, such as transitions from regular to chaotic or from stable to unstable states. In the context of detecting piston failure, RQA can be used to identify patterns in the engine's vibration signals that are indicative of such failure. By placing sensors at different locations in the engine, vibrations can be recorded corresponding to separate engine states, including all cylinders working correctly and one of the cylinders being switched off, at various engine speeds. The RQA indices can then be used as non-linear features to classify the engine condition utilizing a linear model. Determining the RQA statistics on component signals with frequencies centered around the dominant ones increases the dimension of features and leads to higher accuracy in damage detection and identification of a cylinder with a misfire.
M. R. Sales, M. Mugnaine, J. D. Szezech Jr., R. L. Viana, I. L. Caldas, N. Marwan, J. Kurths:
Characterization of stickiness in quasi-integrable Hamiltonian systems by an entropy-based measure of the recurrence plots,
10th International Symposium on Recurrence Plots,
Tsukuba (Japan),
Aug 28, 2023,
Talk.
» Abstract
The stickiness effect is a fundamental feature of quasi-integrable Hamiltonian systems, characterized by the long time spend by a chaotic orbit when near enough a periodic island. We propose the use of an entropy-based measure of the recurrence plots (RPs), namely, the entropy of the distribution of the recurrence times (estimated from the RP), to characterize the dynamics of a typical quasi-integrable Hamiltonian system with coexisting regular and chaotic regions, the Chirikov-Taylor standard map. We show that the recurrence time entropy (RTE) is positively correlated to the largest Lyapunov exponent with a high correlation coefficient. We obtain a multi-modal distribution of the finite-time RTE and find that each mode corresponds to the motion around islands of different hierarchical levels.
B. G. Straiotto, N. Marwan, P. J. Seeley:
Exploring synchronisation in lower limb coordination in a rhythmic body movement: A quantitative analysis,
10th International Symposium on Recurrence Plots,
Tsukuba (Japan),
Aug 28, 2023,
Talk.
» Abstract
Studies of human movement often concern movement quality and that quality may be represented by the everyday term coordination. Research reports alternatively use terms such as correlation and synchronisation. We have developed a previous study of a martial arts movement pattern through study of synchronisation within and between the lower limbs. We explored synchronisation in taekwondo players who utilise repetitive backwards-forwards movements to mount attacks on their opponents and operate speedy retreats, movements that are developed in both training and competition. Eighteen players (nine elite and nine non-elite) performed backwards-forwards movements in a simulated training environment whilst their actions were recorded in detail via motion capture using multiple cameras. Recurrence analysis involved re-representing the time-dependent signals in multidimensional space and then characterising the revisits of a movement trajectory to different sub-regions of that space. The joint probability of recurrence index ($p_j$) was then calculated for centres of mass of limb segments (foot, shank, thigh) in relation to orthogonal movement coordinates (medio-lateral, anterior-posterior, vertical directions). Application of surrogation to the recurrence data indicated that derived $p_j$ values for elite and non-elite groups were deterministic in origin and not the result of data noise ($p < 0.01$). Interlimb pairwise segment relations yielded $p_j$ values in the range 0.23 to 0.29; intralimb relations in the range 0.24 to 0.40. Nonparametric statistical analysis combining Mann-Whitney and Kruskal-Wallis tests along with Bonferroni corrections directly indicated statistically significant differences between elite and non-elite groups for interlimb $p_j$ values and analogous differences for some comparisons for intralimb segment use ($0.05 > p > 0.01$). The potential of recurrence analysis for studies of limb segment synchronisation is revealed by this study. The method may be fruitfully extended in application not only to athletic movement but to transitions in coordination for general members of the public caused by ageing and pathology.
R. Pánis, K. Adámek, N. Marwan:
Averaged recurrence quantification analysis – Method omitting the recurrence threshold choice,
10th International Symposium on Recurrence Plots,
Tsukuba (Japan),
Aug 28, 2023,
Talk.
» Abstract
Recurrence quantification analysis (RQA) is a well established method of nonlinear data analysis. In this work we present a new strategy for an almost parameter-free RQA. The approach finally omits the choice of the threshold parameter by calculating the RQA measures for a range of thresholds (in fact recurrence rates). Specifically, we test the ability of the RQA measure determinism, to sort data with respect to their signal to noise ratios. We consider a periodic signal, simple chaotic logistic equation, and Lorenz system in thetested data set with different and even very small signal to noise ratios of lengths 102, 103, 104, and 105. To make the calculations possible a new effective algorithm was developed for streamlining of the numerical operations on Graphics Processing Unit (GPU).
N. Marwan, T. Braun, K. H. Kraemer, A. Banerjee, D. Eroglu:
Recurrence plots for analysing extreme events data,
10th International Symposium on Recurrence Plots,
Tsukuba (Japan),
Aug 28, 2023,
Talk.
» Abstract
The analysis of time series of extreme events is a challenging task. Many research questions, such as synchronisation analysis or power spectrum estimation, are challenging for linear tools. We demonstrate some recent extensions of the recurrence plot approach for various applications in the field of extreme events data. We demonstrate their potential for synchronisation analysis between signals of extreme events and signals with continuous and slower variations, for estimation of power spectra of spiky signals, and for analysing data with irregular sampling.
N. Marwan, T. Braun:
Power spectrum estimation for extreme events data,
10th International Congress on Industrial and Applied Mathematics (ICIAM),
Tokyo (Japan),
Aug 23, 2023,
» Talk (PDF, 5.27M)
.
» Abstract
The estimation of power spectral density (PSD) of time series is an important task in many quantitative scientific disciplines. However, the estimation of PSD from discrete data, such as extreme event series is challenging. We present a novel approach for the estimation of a PSD of discrete data. Combining the edit distance metric with the Wiener-Khinchin theorem provides a simple yet powerful PSD analysis for discrete time series (e.g., extreme events). This method works directly with the event time series without interpolation or transformation to continuous data. We demonstrate the method's potential on some prototypical examples and on event sequences of atmospheric rivers (AR), narrow filaments of extensive water vapor transport in the lower troposphere. Considering the spatial-temporal event series of ARs over Europe, we investigate the presence of a seasonal cycle as well as periodicities in the multi-annual range for specific regions, likely related to the North-Atlantic Oscillation (NAO).
M. L. Fischer, V. Foerster, F. Schaebitz, N. Marwan, S. Kaboth-Bahr, W. Schwanghart, M. H. Trauth:
A pan-African spatiotemporal framework of the past one million years using advanced multi-record time-series analysis,
XXI INQUA Conference,
Rome (Italy),
Jul 19, 2023,
Poster.
» Abstract
For several decades, eastern Africa was considered the origin ofH. sapiens, documented by the oldest fossil finds from Omo Kibish (233±22 ka BP) and Herto (160–154 ka BP), from where the species was thought to have spread across the rest of the continent and beyond. Recent finds of human fossils and related stone tools in several parts of Africa between roughly 315–75 ka ago, i.e. Jebel Irhoud, southern Africa, Arabia, and eastern Africa initiated a lively discussion of a multiregional model of the origin and development of H. sapiens. The chronology and diversity of human fossils and archaeological remains, associated with a pan-African cultural patchwork, are underpinned by the availability of suitable and connected environments offering enough resources for our species to survive and reproduce. As new paleoanthropological research expands into poorly understood regions of Africa, the key to understanding emerging patterns of mobility and dispersal within and out of Africa is strongly linked to accurately reconstructed climate and environmental conditions in time and space. Here, we aim to create a spatiotemporal paleoclimatic framework for testing current hypotheses about a multiregional origin of our species. To do so, we collect and review suitable climate archives that cover the time since the Mid-Pleistocene Transition, the Mid-Bruhnes Event, and the late Pleistocene. Prerequisites for site selection are: (1) an age model without major gaps, (2) proxy data with a sufficient temporal resolution, precision, and accuracy, (3) a good understanding of the mechanisms that are represented by the proxy data, and (4) together they offer good geographical coverage of Africa's most important climates. We compare records using correlation analysis, such as windowed Spearman correlation, principal component analysis, fast Fourier transformation, and wavelet-based cross-spectral analysis. Furthermore, we analyze long-term trends, shifts, and transition types, that may have provided a catalyst for evolutionary changes, cultural innovation, and expansion/ migration, using e.g. breakfit regression, running Mann-Whitney and Ansari-Bradley test, and recurrence-based transition tests, such as recurrence quantification and recurrence networks. Here, we show the first results of our experiments.
J. Klose, D. Scholz, M. Weber, H. Vonhof, B. Plessen, S. Breitenbach, N. Marwan:
Timing and progression of Dansgaard-Oeschger events in Central Europe based on three precisely dated speleothems from Bleßberg Cave, Germany,
XXI INQUA Conference,
Rome (Italy),
Jul 19, 2023,
Poster.
» Abstract
Speleothems can be dated with unprecedented precision using U-series disequilibrium methods and provide numerous climate proxies, such as stable oxygen (δ18O) and carbon isotopes (δ13C) or trace elements, resulting in long, sometimes continuous climate proxy records. Therefore, speleothems have great potential for reconstruction of past climate variability during Marine Isotope Stage (MIS) 3 and precise determination of the timing and duration of Dansgaard-Oeschger (D/O) events. While first discovered in Greenland ice cores, various speleothem records around the globe provided clear evidence for the supra-regional character of the D/O events. However, MIS 3 speleothem records from Central Europe are very limited. Here we present three spleothem (flowstone) MIS 3 records from Bleßberg Cave, Germany.
All flowstones show episodic growth with distinctive, partially very thin (<2 mm) growth phases, interrupted by visible hiatuses consisting of detrital material. Precise and accurate 230Th/U dating of the individual growth phases is challenging due to potential detrital contamination from these layers. Combining different sampling and analytical techniques, we were able to date even the thinnest growth layers with very high precision, i.e., 2σ-age uncertainties of at most a few hundred years.
The timing of the growth phases aligns with several D/O events, which have not been recorded in other Central European speleothems yet. The δ18O and δ13C records of all three flowstones are highly correlated which suggests a dominant process influencing both isotope systems. Comparison with the Sr and Mg records provides evidence for a strong influence of Prior Calcite Precipitation (PCP) in the aquifer above and inside the cave on the stable isotope and trace element signals. In addition, all proxy records are interpreted as evidence for past changes in precipitation and vegetation density and document a clear trend from more humid climate during early MIS 3 (ca. 57 – 50 ka) to less humid conditions during mid and late MIS 3 (ca. 45 – 30 ka).
Our multi-proxy approach thus allows us not only to precisely determine the timing, duration, and progression of several D/O events, but also to deepen our general understanding of climate variability during MIS 3 in Central Europe.
V. Skiba, C. Spötl, M. Trüssel, A. Schröder-Ritzrau, B. Plessen, N. Frank, R. Eichstädter, R. Tjallingii, N. Marwan, X. Zhang, J. Fohlmeister:
High-elevation speleothems suggest close coupling between North Atlantic millennial-scale variability and Alpine glacier dynamics during Marine Isotope Stage 8,
XXI INQUA Conference,
Rome (Italy),
Jul 18, 2023,
Poster.
» Abstract
Processes triggering abrupt climate transitions during glacial periods are still not fully understood. Most research has focused on the last glacial cycle, limiting our test bed for studying the occurrence and absence of millennial-scale variability and, thus, our understanding of these large-scale reorganisations of the climate system under different background conditions.
Here, we present new stalagmite oxygen and carbon data from high-elevation caves in central Switzerland covering the period from 300 to 200 ka. We demonstrate that millennial-scale variability recorded by these speleothems is representative of Northern Hemisphere interstadial-stadial variability. We use isotope-enabled fully-coupled ocean-atmosphere model simulations to show that the δ18O value of meteoric precipitation was higher by 1 ‰ during interstadials compared to stadials. This agrees with interstadial-stadial amplitudes of the last glacial cycle recorded by stalagmites from other caves in the Alps and is likely the result of North Atlantic seawater δ18O millennial-scale variability.
We find that the effect of prior carbonate precipitation (PCP) is superimposed on the meteoric δ18O signal, amplifying the isotope signal captured by Alpine speleothems on interstadial-stadial timescales. We propose that PCP variability provides a new proxy for milllennial-scale dynamics of warm-based paleoglaciers above these caves.
B. Keenan, J. Collins, B. Aichner, F. Schenk, S. Engels, C. Lane, W. Hoek, I. Neugebauer, T. Grunwald, F. Ott, M. Slowinski, S. Wulf, B. Goswami, N. Marwan, A. Brauer, D. Sachse:
Atmospheric blocking as a stabiliser during abrupt climate change in eastern Europe during the Last Deglaciation,
XXI INQUA Conference,
Rome (Italy),
Jul 14, 2023,
Talk.
» Abstract
Abrupt climate change has occurred frequently in Earth history, most notably during the termination of major glaciations in the Quaternary. Changes occurred over decadal timescales and destabilised or transformed landscapes and ecosystems. We use the Younger Dryas as a natural experiment to better understand the regional propagation of abrupt change. We applied hydrogen isotope analyses (δD) of plant wax lipid biomarkers as indicators of hydrological change and moisture origin from five lake records across Central Europe, namely lakes Meerfelder Maar, Steisslingen, Hämelsee, and Rehwiese palaeolake in Germany, and Lake Czechowskie (Trzechowskie palaeolake) in Poland. Using recurrence analysis, a method to detect and classify time-series and characterise dynamical regime shifts (tipping points), we identify the transition from warm to cold states, or from the relatively warm Allerød to the cold Younger Dryas, and return to the Holocene warm state. Further, isotopic gradients from the Allerød, Younger Dryas and early Holocene are compared with modern gradients, revealing spatial differences in the timing of the onset of the Younger Dryas event, in the magnitude and variability of change as well as the structure of the Younger Dryas event. We show that the pattern of δD responses during the YD were not consistent geographically, and that variation at different locations suggests greater climatic stability and smaller degree of change in the east. These spatiotemporal patterns are compared with modelling results and infer that atmospheric blocking over the Fennoscandian Ice Sheet (FIS) was likely the main driver of spatiotemporal patterns, creating a sustained high-pressure system over Fennoscandia deflecting the flow of westerly winds. This blocking effect only happens during summer as there are strong westerlies from September to April or May. Despite the abrupt climate change at the end of the Deglaciation, this resulted in a more stable climate during the YD event in eastern Europe, while western Europe was affected by major climate fluctuations during the second half of the YD because of weaker summer atmospheric blocking at the end of the YD meant more Atlantic inflow reaching MFM in the west but not in the east.
S. M. Vallejo-Bernal1, L. Luna, F. Wolf, N. Marwan, N. Boers, J. Kurths:
Atmospheric rivers are the drivers of precipitation-triggered landslides in western North America,
28th IUGG General Assembly,
Berlin (Germany),
Jul 14, 2023,
Talk.
» Abstract
Characterized by their specific geometry, atmospheric rivers (ARs) are narrow, long, and transient channels of intensive water vapor transport in the lower troposphere. They play an essential role in the water supply for precipitation in the mid-latitudes but can also trigger natural hazards such as floods and landslides by facilitating heavy precipitation events. In this study, we link the occurrence of landslides in western North America (NA) during the past decades to the precipitation triggered by land-falling ARs hitting the western coastline of the region. For this, we use a landslide inventory, rainfall estimates with a daily temporal resolution, and a catalog of land-falling ARs characterized in terms of strength and persistence based on the AR scale by Ralph et al., 2019. We employ two attribution models to relate rainfall to ARs and then landslides to AR-induced rainfall. Our results show that ARs precede between 60% and 100% of the landslides reported along the western coast of North America. Intense and persistent ARs are the most common precursors. As a further analysis, we study the synchronization pattern of landslides and ARs to determine if their association is unique and significant. In the coastal regions, the precedence relation of ARs leading to landslides is statistically significant. Further inland, landslides are less likely, but those that do occur are significantly correlated with very intense and persistent ARs. Understanding and revealing the impacts of ARs on landslides in western North America will lead to better forecasts and risk assessments of these natural hazards.
N. Marwan, K. H. Kraemer:
Recurrences of movement,
Workshop on Biomarkers arising from nonlinear analysis of movement variability,
Zurich (Switzerland),
July 5, 2023,
Lecture and workshop.
» Abstract
Hands-on workshop on recurrence analysis.
N. Marwan:
Recurrence analysis for complex systems,
Workshop on Biomarkers arising from nonlinear analysis of movement variability,
Zurich (Switzerland),
July 5, 2023,
Talk invited.
» Abstract
Recurrence is a ubiquitous and fundamental feature in many real-world processes. The study of recurrence properties (such as frequency analysis) can provide deeper insights into the dynamical processes in general. A rather novel approach for the study of recurrences is the framework based on recurrence plots and their quantification, rooted in the theory of dynamical systems. This talk will introduce the basic concepts and major extensions applicable to various research questions. Discussed examples include the temporal change of recurrence properties for identification of regime shifts; spatio-temporal recurrences for classification tasks; and bivariate extensions for synchronization/coupling analysis. Methodological and numerical challenges and pitfalls will also be discussed.
J. Zhang, J. Klose, M. Sierralta, S. Tsukamoto, D. Scholz, N. Marwan, S. Breitenbach:
Isothermal thermoluminescence (ITL) dating of a speleothem from Bleßberg Cave,
17th International Luminescence and Electron Spin Resonance Dating conference (LED2023),
Copenhagen (Denmark),
Jun 29, 2023,
Talk.
» Abstract
Their amenability to radiometric dating (U-series) makes speleothems (secondary cave carbonate deposits) a key archive of past climatic and environmental changes. However, incorporation of non-radiogenic thorium can hamper U-series dating, and samples older than ca. 600 ka remain out-of-reach for U-Th dating. Our aim is to develop isothermal thermoluminescence (ITL) dating as alternative approach for otherwise ‘undatable’ samples.
The calcite thermoluminescence (TL) signal (280 °C peak) saturates at much higher doses (saturation dose up to 5000 Gy) compared to quartz and feldspar, which shows great potential to extend the dating limit. However, spurious TL signal occurred at the high temperature range hindered its application. The conventional multiple-aliquot additive-dose (MAAD) protocol used for TL dating applies extrapolation for equivalent dose (De) estimation, which also has large error. Isothermal TL (ITL) dating with the single-aliquot regenerative-dose (SAR) protocol might be a promising way as it reduces the influence of the spurious TL signal, and it applies interpolation to obtain the De. However, this protocol has not been tested on samples with independent age control.
This study tests the ITL SAR dating protocol on a speleothem sample from Bleßberg cave, which has been accurately dated with 230Th/U (ca. 320–425 ka). ITL measurement at 235 °C for 200 °C can remove the 280 °C TL peak completely without TL contribution from higher temperature range. ITL De shows a plateau when the ITL temperature varies between 230 °C and 240 °C. Peak shifting and isothermal annealing tests indicate the 280 °C TL peak has a lifetime of tens of millions years at 10 °C, which is stable enough for the age range of this speleothem sample. The accurate alpha efficiency (α-value) and the U, Th distribution within the sample are measured to estimate the dose rate. The dose rate variation with time due to U-series disequilibrium is corrected for. The ITL ages are compared with the 230Th/U ages to evaluate the performance of the ITL dating protocol.
S. M. Vallejo-Bernal, T. Braun, N. Marwan, J. Kurths:
AR-tracks: A new comprehensive global catalog of atmospheric rivers,
EGU General Assembly,
Vienna (Austria),
Apr 25, 2023,
DOI:10.5194/egusphere-egu23-9251,
Talk.
» Abstract
Atmospheric rivers (ARs) are filaments of extensive water vapor transport in the lower troposphere. They play a crucial role in the global water cycle and are a main source of fresh water for the mid-latitudes. However, very intense and persistent ARs are important triggers of heavy rainfall events and have been associated with natural and economical damage. Further motivated by their high impacts, in the last decade occurrences of ARs have been intensively studied, detection algorithms have been developed, and multiple AR catalogs have been produced. As a common approach, the detection of ARs is based on localizing anomalous atmospheric transport of moisture, usually by setting an absolute threshold on vertically integrated vapor transport (IVT) and/or vertically integrated water vapor (IWV) fields. Behind this methodology, there is the implicit assumption of stationary atmospheric moisture levels, which is not necessarily true for long periods under the context of a warming atmosphere. Also, these thresholds have proven to vary regionally which results in often excluded low-level ARs.
Here, we introduce AR-tracks, a global, high-resolution catalog of atmospheric rivers that we have developed based on the Image-Processing-based Atmospheric River Tracking (IPART) algorithm, using IVT estimates of the ERA5 reanalysis data set. As opposed to conventional detection methods, IPART calculates anomalies of the IVT field at the synoptical spatiotemporal scale of ARs and is, therefore, free from magnitude thresholds and stationarity assumptions. The resulting catalog displays a list of AR events, with a spatial resolution of 0.75° x 0.75° and a temporal resolution of 6 hours, covering the period between 1979 and 2019. For each AR, we provide common parameters such as the time and location of the landfall, the respective IVT value, the area, the width, and the length of the AR. Moreover, we also track the contour and the axis of each AR, the position of the centroid, and the proportion of the AR that is located over ocean and land, and over the different continents.
To show the potential of this new catalog, we study the spatiotemporal variability of European ARs between 1979-2019, analyzing the robustness of our results for distinct parameter choices in the definition of AR-tracks. We also use a novel power spectral measure to identify periodic cycles in the occurrence of European ARs, revealing spatially heterogeneous seasonal and multi-annual periodicities. Finally, we discuss the role of land-falling ARs as a trigger of heavy precipitation events in the regional domain.
With the extensive data we provide in this new catalog, we aim at contributing to the further understanding of the role of ARs in global climate dynamics, as long-lived ARs having cross-continent tracks can be reliably traced through their tropical/subtropical origins to high-latitude landfall, and novel topics such as inland penetration of ARs can be studied.
M. H. Trauth, A. Asrat, M. L. Fischer, P. O. Hopcroft, V. Foerster, S. Kaboth-Bahr, H. F. Lamb, N. Marwan, M. A. Maslin, F. Schäbitz, P. J. Valdes:
Early Warning Signals for the Termination of the African Humid Period(s),
EGU General Assembly,
Vienna (Austria),
Apr 24, 2023,
DOI:10.5194/egusphere-egu23-5277,
Talk.
» Abstract
The study of the mid-Holocene climate tipping point in tropical and subtropical Africa is the subject of current research, not only because there is a comparatively simple but nonlinear relationship between the change in cause (orbital forcing) and the accelerated response of the monsoon system, but also because the African monsoon is an example of a potentially positive evolution of living conditions for humans: modeling results suggest that the Sahel is expanding northward in the wake of human-induced recent global warming, with green belts spreading northward. New literature distinguishes tipping elements such as the African monsoon according to the nature of the cause and the response of the climate system. Research here focuses primarily on tipping points of the type, which is characterized by a critical slowing down and a decreasing recovery from perturbations. The African monsoon, on the other hand, is an example of the tipping point of the type, which is characterized by flickering before the transition. The two types also differ in the nature of their early warning signals (EWS). These EWS are increasingly becoming the focus of research, as they are particularly important for predicting possible tipping of climate in the future of our planet. For the African monsoon system, flickering between two stable states near the transition has been predicted by modeling, but has not yet been demonstrated on paleoclimate time series.
The paleoenvironmental record from the Chew Bahir Basin in the southern Ethiopian Rift, which documents the climate history of eastern Africa of the past 620 ka with decadal resolution in some parts provides the possibility to examine the termination of the African Humid Period (AHP, 15–5 kyr BP) with regard to the possible occurrence of EWS. Thanks to six well-dated short sediment cores (<17 m, <47 kyr BP) and two long cores ( 290 m, <620 ka BP) we can not only study the last climate transition at 5.5 kyr BP in detail, but also similar transitions including possible EWS long before the first occurrence of Homo sapiens at 318 ka BP on the African continent. The analysis of the Chew Bahir record reveals a rapid ( 880 yr) change of climate at 5.5 kyr BP in response to a relatively modest change in orbital forcing that appears to be typical of climate tipping points. If this is the case then 14 dry events at the end of the AHP and 7 wet events after the transition, each of them 20–80 yrs long and recurring every 160±40 yrs, could indeed indicate a pronounced flickering between wet and dry conditions at the end of the AHP, providing significant EWS of an imminent tipping point. Compared to the low-frequency cyclicity of climate variability before and after the termination of the AHP, the flickering occurs on time scales equivalent to a few human generations and it is very likely (albeit speculative) that people were conscious of these changes and adapted their lifestyles to the rapid changes in water and food availability.
J. Wassmer, B. Merz, N. Marwan:
Resilience of emergency infrastructure networks after flooding events,
EGU General Assembly,
Vienna (Austria),
Apr 26, 2023,
DOI:10.5194/egusphere-egu23-1383,
Talk.
» Abstract
Extreme weather events can drastically influence the dynamics and stability of networked infrastructure systems like transportation networks or power grids. Climate change is increasing the frequency of such events, making their impact on human society and ecosystems increasingly relevant. Prominent examples include damage of critical infrastructure caused by heavy rainfalls and landslides. The devastating floods that struck Germany’s Ahr valley in 2021 are yet another reminder of the threat posed by such extreme events. Due to washed-out roads and further severe infrastructure damages, critical bottlenecks effectively cut off a substantial share of the population from assistance, hampering or even impeding their rescue.
In this study, we investigate the impact of flood events on transportation networks where stability is particularly important in order to ensure the accessibility of emergency services. Local changes in the underlying network dynamics can affect the whole road network and, in the worst case, cause a total collapse of the system through cascading failures. Because of the severe consequences of cascading events, we aim to recognise such spreading processes at an early stage and, in a further step, be able to prevent them. To this end, we set up a gravity model of travel to simulate the changes of the traffic load after flooding events to identify vulnerabilities in the system. We further analyse how the accessibility of emergency services is affected and if the population can be effectively reached in time.
N. Marwan, T. Braun:
Power Spectrum Estimation for (Extreme) Events Data,
EGU General Assembly,
Vienna (Austria),
Apr 25, 2023,
DOI:10.5194/egusphere-egu23-7730,
» Talk (PDF, 6.39M)
.
» Abstract
The estimation of power spectral density (PSD) of time series is an important task in many quantitative scientific disciplines. However, the estimation of PSD from discrete data, such as extreme event series is challenging. We present a novel approach for the estimation of a PSD of discrete data. Combining the edit distance metric with the Wiener-Khinchin theorem provides a simple yet powerful PSD analysis for discrete time series (e.g., extreme events). This method works directly with the event time series without interpolation. We demonstrate the method's potential on some prototypical examples and on event sequences of atmospheric rivers (AR), narrow filaments of extensive water vapor transport in the lower troposphere. Considering the spatial-temporal event series of ARs over Europe, we investigate the presence of a seasonal cycle as well as periodicities in the multi-annual range for specific regions, likely related to the North-Atlantic Oscillation (NAO).
N. Marwan, T. Braun:
Power Spectrum Estimation for (Extreme) Events Data,
PIK cross-RD Climate and weather extremes seminar,
Potsdam (Germany),
Apr 20, 2023,
Talk.
» Abstract
The estimation of power spectral density (PSD) of time series is an important task in many quantitative scientific disciplines. However, the estimation of PSD from discrete data, such as extreme event series is challenging. We present a novel approach for the estimation of a PSD of discrete data. Combining the edit distance metric with the Wiener-Khinchin theorem provides a simple yet powerful PSD analysis for discrete time series (e.g., extreme events). This method works directly with the event time series without interpolation or transformation to continuous data. We demonstrate the method's potential on some prototypical examples and on event sequences of atmospheric rivers (AR), narrow filaments of extensive water vapor transport in the lower troposphere. Considering the spatial-temporal event series of ARs over Europe, we investigate the presence of a seasonal cycle as well as periodicities in the multi-annual range for specific regions, likely related to the North-Atlantic Oscillation (NAO).
S. Gupta, Z. Su, A. Banerjee, N. Boers, N. Marwan, L. Magnusson, C. Lopez, E. Hernandez-Garcia, F. Pappenberger, J. Kurths:
Spatial synchronization patterns of extreme rainfall and convection in the Asian Summer Monsoon region,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
A deeper knowledge about the spatially coherent patterns of extreme rainfall events in the South and East Asian regions is of utmost importance for substantially improving the forecasts of extreme rainfall as their agro-based economies predominantly rely on the monsoon. In our work, we use a combination of a nonlinear synchronization measure and complex networks to investigate the spatial characteristics of extreme rainfall synchronicity in the Asian Summer Monsoon (ASM) region and gain a comprehensive understanding of the intricate relationship between its Indian and East Asian counterparts. We identify two modes of synchronization between the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM) – a southern mode between the Arabian Sea and south-eastern China in June which relates the onset of monsoon in the two locations, and a northern mode between the core ISM zone and northern China which occurs in July. Thereafter, we determine the specific times of high extreme rainfall synchronization, and identify the distinctively different large-scale atmospheric circulation, convection and moisture transport patterns associated with each mode. Furthermore, we discover that the intraseasonal variability of the ISM-EASM interconnection may be influenced by the different modes of the tropical intraseasonal oscillation (ISO). Our findings show that certain phases of the Madden-Julian oscillation and the boreal summer ISO favour the synchronization of extreme rainfall events in the June-July-August season between ISM and EASM. The impact of El Nino-Southern Oscillation on the convective sources of the two monsoon subsystems, and thus their interannual variability is investigated.
M. Gelbrecht, K. H. Krämer, N. Marwan:
TreeEmbedding: Optimal state space reconstruction via Monte Carlo decision tree search,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
TreeEmbedding is a novel method for an optimal time delay state space reconstruction from uni- and multivariate time series. The embedding process is considered as a decision tree, in which each leaf corresponds to an embedding cycle and is subject to an evaluation through an objective function. By using a Monte Carlo ansatz, the proposed algorithm populates the tree with many leafs by computing different possible embedding paths and the final embedding is chosen as that particular path that minimises the objective function. The Monte Carlo approach aims to prevent getting stuck in a local minimum of the objective function and can be used in a modular way: Practitioners can choose suitable statistics for delay-preselection and the objective function themselves. The proposed method guarantees the optimization of the chosen objective function over the parameter space of the delay embedding as long as the tree is sampled sufficiently. To showcase the method, we demonstrate its improvements over the classical time delay embedding methods on various application examples. We compare recurrence plot-based statistics inferred from reconstructions of a Lorenz-96 system and highlight an improved forecast accuracy for map-like model data as well as for palaeoclimate isotope time series. The method is ready to use in the form of an accompanying Julia package TreeEmbedding.jl.
S. M. Vallejo-Bernal, T. Braun, N. Marwan, J. Kurths:
Synchronized heavy rainfall events in Europe: the role of atmospheric rivers,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
Atmospheric rivers (ARs) are channels of enhanced water vapor transport in the lower troposphere. They play a crucial role in the fresh water supply of Europe, contributing to up to 30% of the rainfall budget in some regions along the western coast. However, very intense and persistent ARs are important triggers of heavy rainfall events and have been associated with natural and economical damage. Here, we investigate the large-scale spatio-temporal synchronization patterns between heavy rainfall events and landfalling ARs over Europe, during the period from 1979 to 2019. For that, we employ ARtracks, a novel global catalog of ARs, and select the AR events whose footprint intercept Europe. Then, we use an AR-intensity scale to rank the ARs in terms of strength and persistence. Based on ERA5 daily precipitation estimates, we obtain binary time series indicating the absence or presence of heavy rainfall by thresholding the daily precipitation intensity at the 95th percentile. Subsequently, we utilize event synchronization incorporating varying delays to reveal the temporal evolution of spatial patterns of heavy rainfall events in the aftermath of land-falling ARs. Finally, using composites of integrated water vapor transport, geopotential height, upper-level meridional wind, and rainfall, we attribute the formation of the synchronization patterns to well-known atmospheric circulation configurations, depending on the intensity level of the ARs. Our results reveal the role of ARs in the distribution of heavy rainfall events over Europe and advance the understanding of inland heavy precipitation by revealing the characteristic circulation patterns and the main climatic drivers associated to the synchronization patterns.
T. Braun, S. M. Vallejo-Bernal, D. Traxl, N. Marwan, J. Kurths:
A spatio-temporal analysis of global atmospheric rivers,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
Atmospheric rivers (ARs) are narrow, transient corridors of extensive water vapor transport in the lower troposphere. The role ARs play in the global water cycle can be regarded as a double-edged sword: while low-intensity ARs provide vital supply of freshwater and are rarely associated with heavy precipitation events (HPEs), high-level ARs can cause detrimental impacts when they land-fall. Detection of ARs is based on localizing anomalous atmospheric transport of moisture. Many approaches define a threshold to identify local anomalies in integrated vapor transport (IVT) in order to obtain catalogues of ARs, effectively assuming stationary atmospheric moisture levels and often excluding low-level ARs.
Here, we employ an AR-detection framework (`ARtracks') based on global ERA5 reanalysis data that utilizes image processing techniques (using the IPART algorithm). Our approach allows us to study the spatio-temporal variability of globally distributed AR tracks and potential changes due to increasing atmospheric moisture levels on a warming planet. We implement a scale that characterizes ARs based on their strength and persistence, distinguishing between ARs with potentially beneficial and detrimental impacts. A recent study has demonstrated the scope of this categorized AR catalogue for the analysis of synchronization of ARs and HPEs in North America. We analyse the robustness of our results for distinct parameter choices in the definition of AR tracks. A novel power spectral measure for the analysis of event-like time series enables us to identify significant cycles in AR occurrence. Finally, we discuss the role of land-falling ARs as a trigger of HPEs on a global scale.
T. Haselhoff, T. Braun, N. Marwan, S. Moebus:
Complex networks for the urban acoustic environment,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
The urban acoustic environment (AE) plays an underestimated role in the daily life of residents inhabiting metropolitan regions. The urban AE contains valuable information on complex sub-systems of urban areas, such as traffic, infrastructure and biodiversity. Associations between noise exposure and the mental or physical health of urban residents are an important subject of ongoing research. Despite the extensive information that is recorded by modern acoustic sensors, few approaches are designed to capture the rich complexity embedded in the time-frequency domain of the urban AE. The decreasing costs of acoustic sensors and rapid growth of storage space and computational power have led to an increase of acoustical data to be processed. Quantitative methods need to account for this complexity, while effectively reducing the high dimensionality of terabytes of audio data.
We take this as an opportunity to introduce complex networks to the field of urban acoustics. We use one of the world's most extensive longitudinal audio datasets from the SALVE study to systematically characterize the urban AE. SALVE is an ongoing study since 2019, in which 3-min acoustic recordings are made twice per hour at 23 locations in Bochum, Germany. The recorded acoustic samples exhibit a clear diel cycle and reveal site-dependent communities of interlinked frequencies. We demonstrate the utility of frequency-correlation matrices (FCMs) to effectively capture these communities. Based on these results, we construct (functional) networks of day time-specific 3-min audio recordings from 05.2019 to 03.2020 (n = 319,385 = 665 days). We show that the average shortest path length of an acoustic frequency network informs on site- and time-specific distinctiveness of frequency dynamics in the urban AE. To validate our findings, we use the land use mix around each site as a proxy for the AE, as the acoustic environment is heavily impacted by the built environment. The proposed method enables us to clearly identify 4-5 clusters of distinct urban AEs based on hourly variations in the distinctiveness of frequency dynamics. Our results indicate that complex networks represent a promising approach to analyse large-scale audio data and help to understand the time-frequency domain of the urban acoustic environment.
J. Wassmer, B. Merz, N. Marwan:
Resilience of emergency infrastructure networks after flooding events,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
Extreme weather events can drastically influence the dynamics and stability of networked infrastructure systems like transportation networks or power grids. Climate change is increasing the frequency of such events, making their impact on human society and ecosystems increasingly relevant. Prominent examples include damage of critical infrastructure caused by heavy rainfalls and landslides. The devastating floods that struck Germany’s Ahr valley in 2021 are yet another reminder of the threat posed by such extreme events. Due to washed-out roads and further severe infrastructure damages, critical bottlenecks effectively cut off a substantial share of the population from assistance, hampering or even impeding their rescue.
In this study, we investigate the impact of flood events on transportation networks where stability is particularly important in order to ensure the accessibility of emergency services. Local changes in the underlying network dynamics can affect the whole road network and, in the worst case, cause a total collapse of the system through cascading failures. Because of the severe consequences of cascading events, we aim to recognise such spreading processes at an early stage and, in a further step, be able to prevent them. To this end, we set up a gravity model of travel to simulate the changes of the traffic load after flooding events to identify vulnerabilities in the system. We further analyse how the accessibility of emergency services is affected and if the population can be effectively reached in time.
N. Antary, N. Marwan:
Interpolation effects an RQA measures,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
The recurrence plot and recurrence quantification analysis (RQA) are well established methods for the analysis of data from complex systems. They provide import insides about the nature of the dynamics, periodicity, regime changes, and many more. This method is used in different fields of research like finance, engineering, life and earth science. In order to use this method the data has usually to be uniformly sampled. This poses a difficulty for data, which is taken from palaeoclimate archives like sediment cores or stalagmite. One frequently used solution is interpolation to generate uniform time series. However, this prepossessing changes the RQA measures like DET, LAM, or the average line length. Using auto-regression processes, we systematically analyse how these measures increase when interpolating the data. For other systems which show a smoother behavior there is only an effect if the interpolation takes place on a time scale close to the characteristic timescale of the system, like the period lengths. For the Roessler system, the RQA measures decrease when approaching this timescale and show a very irregular behavior below. For real data, we show that the course of the DET measure strongly depends on the choice of interpolation.
M. R. Sales, M. Mugnaine, J. D. Szezech Jr., R. L. Viana, I. L. Caldas, N. Marwan, J. Kurths:
Characterizing stickiness using recurrence time entropy,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Poster.
» Abstract
The stickiness effect is a fundamental characteristic of quasi-integrable Hamiltonian systems. We propose the use of an entropy-based measure of recurrence plots (RP), namely, the entropy of the distribution of the recurrence times (estimated from the RP), to characterize the dynamics of a typical quasi-integrable Hamiltonian system with coexisting regular and chaotic regions. We show that the recurrence time entropy (RTE) is positively correlated to the largest Lyapunov exponent, with a high correlation coefficient. We obtain a multi-modal distribution of the finite-time RTE and show that each mode corresponds to the motion around islands of different hierarchical levels.
N. Marwan, G. Zamora-Lopez:
Juergen Kurths' world of publications,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
March 15-17, 2023,
Poster.
» Abstract
We present the co-authorship network of Juergen Kurth's publications.
C. Özdes, D. Eroglu, N. Marwan, T. Braun:
Multi-stable synchronization patterns and switching dynamics of paleoclimate networks,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Talk.
» Abstract
To improve our understanding of climate dynamics, we first need to deeply understand the climate’s past if we hope to mitigate and adapt to oncoming critical climate change. Understanding the past climate dynamics depends on the interpretation of paleo proxies. Blending dynamical systems theory, recurrence theorem, multi-stability, and synchronization with complex networks theory and machine learning techniques have become instrumental for a more profound understanding of climate dynamics in the last few decades. However, these techniques are not directly applicable to paleoclimate research since the proxy data is subject to different distortions. The paleoclimate proxy measurements carry uncertainty in nominal and temporal dimensions, and also the choice of proxy and varying effects of local and global interactions matter.
Paleoclimate proxies typically represent the climate dynamics of large spatial regions and long periods. Furthermore, the proxies contain many switching transitions between droughts and wet seasons, showing that paleoclimate dynamics have multi-stability. To mimic paleoclimate dynamics, we introduce a multi-layer network model of coupled chaotic maps where multiple chimera configurations of synchronized subsystems co-exist as stable states. This multi-stable system goes through a series of critical transitions into another stable state through noise induction. We collect only the mean field of the state variables from each layer to imitate the spatial sparsity of paleoclimate measurements. Using this limited information, we developed a methodology to reconstruct paleoclimate networks and identify the critical switching of dynamical patterns.
Our paleoclimate network approach pivots around the recurrent property of climate system states. After suitable transformations, recurrence quantification analyses (RQA) of proxy series are shown to be robust indicators of the dynamical properties of represented dynamics in the form of time series. We construct a functional network from these series with nodes representing proxy sources using the time evolution of individual series. This allows us to classify the system state with respect to the visible relational dynamics between nodes. We also extended our studies to real paleoclimate datasets around Northern Africa and found the dominant dynamical patterns associated with known periods.
N. Marwan, T. Braun, K. H. Kraemer, A. Banerjee, D. Eroglu:
Recurrence plots for analysing extreme events data,
Conference on Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives, PIK Potsdam,
Potsdam (Germany),
Mar 17, 2023,
Talk.
» Abstract
The analysis of time series of extreme events is a challenging task. Many research questions, such as synchronisation analysis or power spectrum estimation, are challenging for linear tools. We demonstrate some recent extensions of the recurrence plot approach for various applications in the field of extreme events data. We demonstrate their potential for synchronisation analysis between signals of extreme events and signals with continuous and slower variations, for estimation of power spectra of spiky signals, and for analysing data with irregular sampling.
S. De, S. Gupta, V. R. Unni, R. Ravindran, P. Kasthuri, N. Marwan, J. Kurths, R. I. Sujith:
Implications of a Complex Network-Based Approach to the Analysis of Cyclone Merger,
Conference on Nonlinear Systems & Dynamics, IISER Pune,
Pune (India),
Dec 17, 2022,
Talk.
» Abstract
When cyclones are formed in close proximity, they can interact. Such an interaction is termed as “Fujiwhara effect” [1]. Due to this effect, the mutual distance between the cyclones decreases, which triggers a variety of interactions such as elastic interaction, partial merger, and complete merger. However, the interaction between the cyclones leading to a completer merger is a rare event in nature. The complete merger between cyclones can result in a more intense, long-lived cyclone. However, understanding the dynamics of cyclonic interactions is presently challenging for weather forecasters, making the prediction of a cyclone merger more difficult. The main reason attributed to the prediction inaccuracy is that, to date, cyclone forecasting models have not completely incorporated the Fujiwhara effect due to a lack of knowledge [2,3]. As a consequence, inaccurate cyclone merger predictions may result in substantial economic losses and fatalities. Hence, we require a method that can enable us to obtain profound insights into the dynamics of cyclone interaction that leads to a complete cyclone merger.
S. Kulkarni, U. Öztürk, N. Marwan, J. Kurths, B. Merz, A. Agarwal:
Complex networks in hydrologic sciences,
AGU 2022 Fall Meeting,
New Orleans (USA),
December 12–16, 2022,
Talk.
» Abstract
Complex network science is a stemming interdisciplinary field of research spreading to diverse branches of sciences such as physics, engineering, social science, and Earth Sciences. The complex systems can be represented as graphs with individual components called nodes and the links representing the interaction between nodes. Regardless of their physical nature, complex networks of different systems exhibit common structural properties that distinguish them from purely random graphs. The application of complex networks in hydrology and water resources management is in its infancy but overgrowing. However, this innovative approach has already led to important insights in hydrology. In this review, we first provide a comprehensive overview of the multiple aspects of complex networks and their measures; further, we summarize applications of complex networks in water science to offer a current picture of state-of-the-art; and lastly, we highlight arising open problems and new directions. Our work, with the help of examples, advocates that complex network science can be a generic theory to understand different hydrologic systems.
A. Manapat, J. L. Oster, F. Lechleitner, H. Cheng, J. F. Adkins, S. M. Bernasconi, W. D. Sharp, N. Marwan, B. Plessen, S. F. M. Breitenbach:
Stalagmite record of Indian Summer Monsoon variability during Marine Isotope Stage 3,
AGU 2022 Fall Meeting,
New Orleans (USA),
December 12–16, 2022,
Poster.
» Abstract
Variation in the strength of the Indian Summer Monsoon (ISM) affects the food security and livelihood of around one-third of the world’s population. However, many of the causes of variation in ISM strength remain poorly understood. Variation in the stable oxygen and carbon isotope ratios (d18O and d13C) in speleothems have been used as proxies to understand pre-instrumental variation in ISM intensity with δ18O variation linked to changes in precipitation dynamics and δ13C reflecting changes in the local rainfall amounts.
We present a stable isotope record from MAW-3, a stalagmite from Mawmluh cave, northeast India. This site receives between 70-80% of its annual rainfall between June and September. Precipitation, cave drip monitoring, and studies of modern stalagmites from this site indicate that stalagmite d18O reflects changes in ISM strength linked to large-scale atmospheric dynamics. We discuss the interval of growth for stalagmite MAW-3 that occurred between 44 ka BP and 28 ka BP, corresponding to Marine Isotope Stage 3 (MIS3). The resultant δ18O record displays significant millennial-scale oscillations of between 1.5-3.0 ‰, possibly corresponding to Dansgaard-Oeschger (D-O) events 5-8. Continuous Wavelet Transform (CWT) indicates a 1350-year cycle in δ18O. Stalagmite δ13C also decreases by 2.0-4.0 ‰ during D-O interstadials, likely due to reduced prior carbonate precipitation (PCP) during periods of higher rainfall. The MAW3 δ18O shifts to more negative values during the D-O warmings (interstadials) noted in the North Greenland Ice Core Project (NGRIP) oxygen isotope record. However, the δ18O variation in MAW-3 is much more gradual than that of NGRIP, indicating differences in how these D-O events affect climate variation outside of the North Atlantic region. Variations in δ18O in MAW3 are also in phase with δ18O variations in the Hulu Cave record over this interval indicating synchronous variability between the ISM and East Asian Monsoon over D-O events 5-8. The MAW3 record further strengthens evidence for climate teleconnections between the North Atlantic and the Indian and East Asian monsoon systems. Reconstructing such variation is important in understanding how the monsoons may change in a warming planet.
N. Marwan:
Methods for Extreme Events Time Series,
PIK cross-RD Climate and weather extremes seminar,
Potsdam (Germany),
Dec 8, 2022,
Talk.
N. Marwan:
Investigating palaeoclimate conditions with nonlinear time series analysis,
MARUM research seminar, University of Bremen,
Bremen (Germany),
Dec 5, 2022,
Talk invited.
» Abstract
The study of palaeoclimate data is related with specific challenges, such as nonstationarities, nonlinear feedbacks, irregular sampling, or different kinds of uncertainties. Recurrence analysis and complex networks are concepts based on nonlinear dynamics and complex systems science that can help to identify regime transitions and couplings in palaeoclimate data. I demonstrate their potential for studying variations and couplings for selected palaeoclimate research questions.
N. Marwan:
Ways to Quantitative Recurrence Plot Analysis,
Complexity Lab Seminar, Rochester Institute of Technology,
Rochester (US),
Nov 15, 2022,
Lecture.
» Abstract
Recurrence is a ubiquitous and fundamental feature in many real world processes. Recurrence plots are versatile tools for studying such phenomena. The lecture introduces the basic concepts and major extensions of quantifying recurrence plots. Discussed examples include the temporal change of recurrence properties for identification of regime shifts, methodological and numerical challenges, as well as potential pitfalls.
V. Skiba, M. Trüssel, B. Plessen, C. Spötl, R. Eichstädter, A. Schröder-Ritzrau, T. Braun, T. Mitsui, N. Frank, N. Boers, N. Marwan, J. Fohlmeister, R. Tjallingii, X. Zhang:
On the forcing of glacial abrupt climate transitions of the last 300,000 years,
DEUQUA-Tagung 2022,
Potsdam (Germany),
Sep 26, 2022,
Talk.
» Abstract
Abrupt stadial-interstadial transitions, are a prominent feature of the last glacial as recorded in Greenland ice core records (Dansgaard-Oeschger events). Event abruptness and presence of statistical early warning signals before these transitions indicate that they involve crossing of a tipping point of the climate system. However, only little information is available for periods before the last glacial period as Greenland ice cores and many other high-resolution records do not extent beyond the last glacial cycle. Given the lack of understanding of the triggering mechanisms responsible for glacial abrupt climate transitions with palaeoclimate data from the last glacial, it is essential to investigate this phenomenon during earlier glacial periods.
Here, we present a new highly resolved, precisely U-Th-dated speleothem oxygen isotope record from the Northern European Alps for the penultimate glacial (MIS7-MIS8), a region which has been shown to record similar climate variability as Greenland ice core records. Together with previously obtained speleothem data from this cave site for MIS5-MIS7 and Greenland ice core data (NGRIP, MIS1-4), we investigate background climate conditions which favour occurrence of abrupt climate transitions using regression analysis. Besides intermediate background conditions (sea level, CO2 and CH4) and low precession, we find either relatively low or high obliquity to favour glacial abrupt climate transitions, perhaps depending on the initial mode of the Atlantic Meridional Overturning Circulation before these occurrences.
T. Braun, N. Marwan:
A recurrence flow based approach to state space reconstruction,
Dynamics Days Europe 2022,
University of Aberdeen (UK),
Aug 23, 2022,
Talk.
» Abstract
In the study of nonlinear observational time series, reconstructing the system’s state space via time-delay embedding represents the basis for many widely-used analyses. Recurrence plots indicate the appropriateness of the underlying embedding parameters by the presence of well-formed diagonal lines that represent the predictability of the system's evolution. However, an approach that systematically exploits this information for optimal state space reconstruction is so far missing. In this talk, we propose a recurrence based framework for state space reconstruction. The concept is based on a novel recurrence quantification measure that captures how well a fictive fluid can permeate an RP diagonally, the recurrence flow. The recurrence flow can be regarded as a nonlinear dependence measure that quantifies the relationship between multiple time series based on the predictability of their joint evolution. We demonstrate the effectiveness of the proposed method in detecting nonlinear multiscale relations and informing on the choice of optimal embedding parameters for complex real-world time series.
N. Marwan, K. H. Kraemer:
Recent Exciting Developments in Recurrence Plot Analysis,
Dynamics Days Europe 2022,
University of Aberdeen (UK),
Aug 23, 2022,
Talk.
» Abstract
The last decade has witnessed a number of important and exciting developments that had been achieved for improving recurrence plot based data analysis and to widen its application potential. I will give a brief overview about important and innovative developments, such as computational improvements, alternative recurrence definitions (event-like, multiscale, heterogeneous, and spatio-temporal recurrences) and ideas for parameter selection, theoretical considerations of recurrence quantification measures, new recurrence quantifiers (e.g., for transition detection and causality detection), and correction schemes. Moreover, new perspectives have recently been opened by combining recurrence plots with machine learning.
N. Marwan:
Reconstructing Complex Networks from Data,
(Virtual) Workshop on the Application of Complex Networks to Fluid Mechanics, IIT Madras,
Chennai (India)/ Online,
Aug 15, 2022,
Talk.
» Abstract
Complex networks provide an interesting tool to investigate spatio-temporal data. The first step is to reconstruct a (functional) network from data. I will show different reconstruction approaches depending on the research question and the nature of the data. The procedure is illustrated with applications on climate data.
S. Gupta, Z. Su, N. Boers, J. Kurths, N. Marwan, F. Pappenberger:
Spatial Synchronization Patterns of Extreme Rainfall Events in the Asian Summer Monsoon Region,
AOGS2022 Virtual 19th Annual Meeting,
(online meeting),
Aug 1, 2022,
Talk.
» Abstract
A deeper knowledge about the spatially coherent patterns of extreme rainfall events in the South and East Asian regions is of utmost importance for substantially improving the forecasts of extreme rainfall as their agro-based economies predominantly rely on the monsoon. In our work, we use a combination of a nonlinear synchronization measure and complex networks to investigate the spatial characteristics of extreme rainfall synchronicity in the Asian Summer Monsoon (ASM) region and gain a comprehensive understanding of the intricate relationship between its Indian and East Asian counterparts. We identify two modes of synchronization between the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM) – a southern mode between the Arabian Sea and south-eastern China in June which relates the onset of monsoon in the two locations, and a northern mode between the core ISM zone and northern China which occurs in July. Thereafter, we determine the specific times of high extreme rainfall synchronization, and identify the distinctively different large-scale atmospheric circulation, convection and moisture transport patterns associated with each mode. Furthermore, we discover that the intraseasonal variability of the ISM-EASM interconnection may be influenced by the different modes of the tropical intraseasonal oscillation (ISO). Our findings show that certain phases of the Madden-Julian oscillation and the boreal summer ISO favour the synchronization of extreme rainfall events in the June-July-August season between ISM and EASM. This work is funded by the CAFE project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.
J. Klose, M. Weber, H. Vonhof, B. Plessen, S. F. M. Breitenbach, N. Marwan, D. Scholz:
Timing of Dansgaard-Oeschger events in Central Europe based on three precisely dated speleothems from Bleßberg Cave, Germany,
Climate Change, The Karst Record IX (KR9),
Innsbruck (Austria),
July 18, 2022,
Talk.
» Abstract
The last glacial period and especially Marine Isotope stage 3 (MIS 3, ca. 57 - 27 ka) was characterized by various climate oscillations (i.e., rapid increases in temperature, followed by a gradual cooling, the Dansgaard-Oeschger (D/O) events), which were first discovered in Greenland ice cores. Although their causes are still not fully understood, clear evidence for their supra-regional character was found in various climate records around the globe. However, European speleothem samples, which grew during MIS 3, are limited and mainly restricted to alpine regions, where glacier meltwater enabled speleothem growth, and to south/south-western parts of Europe characterised by a generally warmer climate. This led to the opinion that it was too cold and/or too dry in central Europe for speleothem growth. Here we present three speleothem (flowstone) records from Bleßberg Cave, Germany, which grew during MIS 3.
All flowstones show episodical growth patterns with distinctive, thin growth phases. Potential contamination deriving form detrital material deposited during hiatuses between individual growth phases, open-system behaviour around the hiatuses and the limited thickness of the growth layers are the biggest challenges during sampling for 230Th/U dating. By combination of different sampling techniques (i.e., laser ablation and micro-milling) in addition to the common approach of handheld drilling and due to the relatively high 238U concentration of the samples (approx. 0.4 - 1 μg/g), we were able to date even the thinnest growth layers (< 2 mm) of the Bleßberg flowstones with a very high precision (i.e., with 2σ-age uncertainties of a few hundred years or even lower).
The timing of the growth phases of the Bleßberg flowstones correlates with several D/O events recorded in the Greenland ice cores. This proves that at least some phases of MIS 3 had favourable climate conditions for speleothem growth in Central Europe. In addition, the analysis of the stable oxygen and carbon isotopes (δ18O and δ13C) for all three flowstones revealed several D/O events, which have not been recorded in any other speleothem from central Europe so far. This will enhance our understanding of climate variability during MIS 3 and specific D/O events in central Europe.
N. Marwan:
Investigating palaeoclimate conditions with nonlinear time series analysis,
Colloquium on Complex and Biological Systems, University of Potsdam,
Potsdam (Germany),
Jun 24, 2022,
Talk.
» Abstract
The study of palaeoclimate data is related with specific challenges, such as irregular sampling or different kinds of uncertainties. Recurrence analysis and complex networks are concepts based on nonlinear dynamics and complex systems science that can help to identify regime transitions and couplings. I demonstrate their potential for studying variations and couplings in the palaeoclimate Monsoon system.
N. Marwan:
Das Sägistal - Alpines Karstgebiet im Berner Oberland,
60. Jahrestagung des VdHK,
Truckenthal (Germany),
Jun 17, 2022,
Talk.
N. Marwan:
Bleßberghöhle – Schatzkammer für die Wissenschaft,
VdHK-Symposium: Wissenschaft unter Tage – Höhlenforschung im Dialog,
Truckenthal (Germany),
Jun 15, 2022,
» Talk (PDF, 8.96M)
.
N. Marwan, J. F. Donges, R. V. Donner, D. Eroglu:
Integrative multivariate study of past African climate variability,
EGU General Assembly,
Vienna (Austria),
May 24, 2022,
DOI:10.5194/egusphere-egu22-6559,
» Talk (PDF, 7.01M)
.
» Abstract
Based on a set of various marine palaeoclimate proxy records, we investigate African climate variations during the past 5 million years. We use a collection of modern approaches from non-linear time series analysis to identify and characterise dynamical regime shifts as changes in signal predictability, regularity, complexity, and higher-order stochastic properties such as multi-stability. We observe notable nonlinear transitions and important climate events in the African palaeoclimate, which can be attributed to phases of intensified Walker circulation, marine isotope stage M2, the onset of northern hemisphere glaciation, and the mid-Pleistocene transition, and relate them to variations of the Earth's orbital parameters.
A. Giesche, D. A. Hodell, C. A. Petrie, G. H. Haug, J. F. Adkins, B. Plessen, N. Marwan, H. J. Bradbury, A. Hartland, A. D. French, S. F. M. Breitenbach:
Northwest Indian stalagmite shows evidence for recurring summer and winter droughts after 4.2 ka BP,
EGU General Assembly,
Vienna (Austria),
May 24, 2022,
DOI:10.5194/egusphere-egu22-396,
Talk.
» Abstract
We reconstructed changes in summer and winter precipitation using a well-dated (±18 years 2σ error) speleothem spanning 4.2-3.1 ka BP from Dharamjali Cave in the central Himalaya. The record was sampled at a sub-annual resolution for a suite of trace elements, as well oxygen and carbon stable isotopes. Calcium isotopes at decadal resolution provide additional hydroclimatic evidence. This DHAR-1 stalagmite records a 230-year period of increased drought frequency in both the summer and winter seasons after 4.2 ka BP, with aridity events centered on 4.19, 4.11 and 4.02 ka BP each lasting between 25 and 90 years. The data after 3.97 ka BP support a recovery in summer monsoon rainfall, peaking around 3.7 ka BP. The significance of this new record includes remarkable coherence between the moisture proxies over 4.2-3.97 ka BP in a well-dated record, which provides confidence in the duration of droughts and timing of monsoon recovery. It also places seasonal climate variability on a timescale relevant to human decision-making, which is particularly significant for this region nearby the Indus River Basin. The Indus Civilization reached its urban apex by 4.2 ka BP, and archaeologists have documented a shift in settlement locations, population, health, and agricultural strategies thereafter for a period of several centuries. This stalagmite record provides valuable insights into seasonal precipitation availability during a critical climatic and cultural transition phase.
J. Wassmer, N. Marwan, B. Merz:
Impact of extreme events on topological robustness of infrastructure networks,
EGU General Assembly,
Vienna (Austria),
May 26, 2022,
DOI:10.5194/egusphere-egu22-2705,
Talk.
» Abstract
Climate change is increasing the frequency of extreme weather events such as floods, making their impact on human society and ecosystems increasingly relevant. Extreme weather events can drastically influence the dynamics and stability of networked infrastructure systems like transportation networks or power grids. Local changes in the dynamics can affect the whole network and, in the worst case, cause a total collapse of the system through cascading failures. Hence, methods are needed to understand and prevent such collapses.
In this project, we analyse the influences of flooding events on transportation networks using the Ahr valley flood of July 2021 in Germany as a case study. To this end, we set up a gravity model for road networks to compute the traffic loads. We use satellite data provided by EU Copernicus programme to access information about the state of the road network right after the flooding event. By removing flooded roads from the model, we can estimate the effect on the traffic load and identify secondarily affected roads. This approach enables us to identify and optimise critical links to ensure that affected areas are not isolated after extreme weather events and can receive disaster assistance from surrounding areas.
F. Wolf, S. M. Vallejo-Bernal, N. Boers, N. Marwan, D. Traxl, J. Kurths:
Spatio-temporal synchronization of heavy rainfall events triggered by atmospheric rivers in North America,
EGU General Assembly,
Vienna (Austria),
May 24, 2022,
DOI:10.5194/egusphere-egu22-2993,
» Talk (PDF, 758.19K)
.
» Abstract
Atmospheric rivers (ARs) are filaments of extensive water vapor transport in the lower troposphere. They are important triggers of heavy rainfall events, contributing to more than 50% of the rainfall sums in some regions along the western coast of North America. ARs play a crucial role in the distribution of water, but can also cause natural and economical damage by facilitating heavy rainfall. Here, we investigate the large-scale spatio-temporal synchronization patterns of heavy rainfall triggered by ARs over the western coast and the continental regions of North America.
For our work, we employ daily ERA5 rainfall estimates at a spatial resolution of 0.25°x0.25° latitude and longitude which we threshold at the 95th percentile to obtain binary time series indicating the absence or presence of heavy rainfall. Subsequently, we separate periods with ARs and periods without ARs and investigate the differing spatial synchronization pattern of heavy rainfall. To establish that our results are not dependent on the chosen AR catalog, this is conducted in two different ways: first based on a recently published catalog by Gershunov et al. (2017) , and second based on a catalog constructed using the IPART algorithm (Xu et al, 2020). For both approaches, we subsequently utilize event synchronization and a complex network framework to reveal distinct spatial patterns of heavy rainfall events for periods with and without active ARs. Using composites of upper-level meridional wind, we attribute the formation of the rainfall synchronization patterns to well-known atmospheric circulation configurations, whose intensity scales with the strength of the ARs. Furthermore, we demonstrate that enhanced AR activity is going in hand with a suppressed seasonal shift of the characteristic meridional wind pattern. To verify and illustrate how small changes of the high-level meridional wind affect the distribution of heavy rainfall, we, additionally, perform a case study focusing on the boreal winter.
Our results indicate the strong sensitivity of the intensity, location, frequency, and pattern of synchronized heavy rainfall events related to ARs to small changes in the large-scale circulation.
S. M. Vallejo-Bernal, F. Wolf, L. Luna, N. Boers, N. Marwan, J. Kurths:
Relationship between atmospheric rivers and landslides in western North America,
EGU General Assembly,
Vienna (Austria),
May 25, 2022,
DOI:10.5194/egusphere-egu22-8096,
» Talk (PDF, 1.79M)
.
» Abstract
In this study, we investigate the relationship between land-falling atmospheric rivers (ARs) and landslides in western North America. ARs are channels of enhanced water vapor flux in the atmosphere and play an essential role in the water supply for precipitation in the midlatitudes. However, they can also trigger natural hazards such as floods and landslides. Our objective is to determine if the occurrence of landslides in western North America can be attributed to ARs hitting the western coastline and causing rainfall at the locations of the landslides and to characterize the strength and persistence of the ARs that lead to landslides. To that aim, we use landslide records with daily temporal resolution along with daily rainfall estimates from the ERA5 reanalysis, for the period between 1996 and 2018. We propose and run two attribution models to relate landslides to rainfall and rainfall to ARs and subsequently verify statistically if there is a unique and significant association between the landslides and the ARs. Our results show that the majority of the landslides reported along the western coast of North America are preceded by an AR. In the coastal regions, ARs and landslides are significantly correlated. Further inland, landslides are less likely, but those that do occur are significantly correlated with very intense ARs. Understanding and revealing the impacts of ARs on landslides in western North America will lead to better forecasts and risk assessments of these natural hazards.
S. Gupta, Z. Su, N. Boers, J. Kurths, N. Marwan, F. Pappenberger:
Interrelation between the Indian and East Asian Summer Monsoon: A complex network-based approach,
EGU General Assembly,
Vienna (Austria),
May 23, 2022,
DOI:10.5194/egusphere-egu22-8626,
» Talk (PDF, 1.96M)
.
» Abstract
The Indian Summer Monsoon (ISM) and the East Asian Summer monsoon (EASM) are two integral components of the Asian Summer Monsoon system, largely influencing the agro-based economy of the densely populated southern and eastern parts of Asia. In our study, we use a complex network based approach to investigate the spatial coherence of extreme precipitation in the Asian Summer Monsoon region and gain a deep insight into the complex nature of the interaction between the ISM and the EASM. We identify two dominant modes of ISM-EASM interaction – (a) a southern mode connecting onset of the ISM over the Arabian Sea and southern India in June to the onset of Meiyu over south-eastern China, i.e., lower and middle reaches of the Yangtze river valley, and (b) a northern mode relating the occurrence and intensity of rainfall over the northern and central parts of India to that in northern China during July. Through determination of specific times of high synchronization of extreme precipitation, we distinctly identify the particular large-scale atmospheric circulation and moisture transport patterns associated with each mode. Thereafter, we investigate the role of the different components of the tropical intraseasonal oscillations, such as the Madden-Julian Oscillation and the boreal summer intraseasonal oscillation, in the intraseasonal variability of the relationship between the ISM and the EASM.
This work is funded by the CAFE project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.
T. Braun, K. H. Kraemer, N. Marwan:
A Recurrence Flow based Approach to Attractor Reconstruction,
EGU General Assembly,
Vienna (Austria),
May 25, 2022,
DOI:10.5194/egusphere-egu22-9626,
Talk.
» Abstract
In the study of nonlinear observational time series, reconstructing the system’s state space represents the basis for many widely-used analyses. From the perspective of dynamical system’s theory, Taken’s theorem states that under benign conditions, the reconstructed state space preserves the most fundamental properties of the real, unknown system’s attractor. Through many applications, time delay embedding (TDE) has established itself as the most popular approach for state space reconstruction. However, standard TDE cannot account for multiscale properties of the system and many of the more sophisticated approaches either require heuristic choice for a high number of parameters, fail when the signals are corrupted by noise or obstruct analysis due to their very high complexity.
We present a novel semi-automated, recurrence based method for the problem of attractor reconstruction. The proposed method is based on recurrence plots (RPs), a computationally simple yet effective 2D-representation of a univariate time series. In a recent study, the quantification of RPs has been extended by transferring the well-known box-counting algorithm to recurrence analysis. We build on this novel formalism by introducing another box-counting measure that was originally put forward by B. Mandelbrot, namely succolarity. Succolarity quantifies how well a fluid can permeate a binary texture. We employ this measure by flooding a RP with a (fictional) fluid along its diagonals and computing succolarity as a measure of diagonal flow through the RP. Since a non-optimal choice of embedding parameters impedes the formation of diagonal lines in the RP and generally results in spurious patterns that block the fluid, the attractor reconstruction problem can be formulated as a maximization of diagonal recurrence flow.
The proposed state space reconstruction algorithm allows for non-uniform embedding delays to account for multiscale dynamics. It is conceptually and computationally simple and (nearly) parameter-free. Even in presence of moderate to high noise intensity, reliable results are obtained. We compare the method’s performance to existing techniques and showcase its effectiveness in applications to paradigmatic examples and nonlinear geoscientific time series.
V. Skiba, M. Trüssel, B. Plessen, C. Spötl, R. Eichstädter, A. Schröder-Ritzrau, T. Braun, T. Mitsui, N. Frank, N. Boers, N. Marwan, J. Fohlmeister:
Abrupt climate events recorded in speleothems from the ante penultimate glacial,
EGU General Assembly,
Vienna (Austria),
May 23, 2022,
DOI:10.5194/egusphere-egu22-11671,
» Talk (PDF, 1.04M)
.
» Abstract
Millennial-scale climate variability, especially abrupt stadial-interstadial transitions, are a prominent feature of the last glacial as recorded in Greenland ice core records (Dansgaard-Oeschger events). Event abruptness and presence of statistical early warning signals before these transitions indicate that they involve repeated crossing of a tipping point of the climate system. However, only little information is available for periods before the last glacial period as Greenland ice cores and many other high-resolution records do not extent beyond the last glacial cycle. Given the lack of understanding of the triggering mechanism responsible for glacial millennial-scale variability with palaeoclimate data from the last glacial, it is essential to investigate this phenomenon during earlier glacial periods.
Here, we present a new highly resolved, precisely U-Th-dated speleothem oxygen isotope record from the Northern European Alps, a region which has been previously shown to resemble the glacial millennial-scale climate variability obtained from Greenland ice core records very well. Our new data covers the time interval from the ante-penultimate glacial to the penultimate glacial (MIS8-MIS6) with a high degree of replication. For both glacial periods, we find phases of pronounced millennial-scale variability but also several, 10 ka long phases with the climate system being exclusively in stadial conditions. We compare our data with conceptual model results and investigate the occurrence and absence of abrupt climate transitions of the last 300,000 a.
T. Braun, C. N. Fernandez, D. Eroglu, A. Hartland, S. F. M. Breitenbach, N. Marwan:
Sampling rate-corrected time series analysis of irregularly sampled palaeoclimate proxy records,
6th PAGES Open Science Meeting,
(online meeting),
May 18, 2022,
Talk.
» Abstract
Irregular sampling remains a challenge in the analysis of time series from different palaeoclimate archives. Aside from rendering most standard time series analysis methods inapplicable, changes in the sampling rate of a record entail significant biases that can not be corrected by basic pre-processing procedures such as linear interpolation. Yet, sampling rates frequently show non-stationary characteristics, e.g. for speleothems, as they are coupled to environmental parameters via their growth rate.
Consequently, methods that account for continuous and abrupt changes of sampling resolution without introducing additional biases are required. In several applications, the edit–distance has proven to be an effective metric to quantitatively compare time series segments of unequal length by computing the cost of transforming one segment into the other. We demonstrate that transformation costs generally exhibit a non-trivial relationship with local sampling rate. If the sampling rate undergoes significant variations, this dependence rules out an unbiased comparison between different time episodes. We study the impact of this effect on recurrence quantification analysis, a framework that is well-suited for identifying regime shifts in nonlinear time series. A constrained randomization procedure is proposed as a bias correction for recurrence quantification analysis.
We demonstrate the effectiveness of the proposed approach in the analysis of an irregularly sampled speleothem proxy record with seasonal laminae from Niue island in the central tropical Pacific. Application of the proposed correction scheme identifies a spurious transition that is solely imposed by an abrupt shift in sampling rate and uncovers periods of reduced seasonal rainfall predictability associated with enhanced ENSO and tropical cyclone activity.
M. H. Trauth, A. Asrat, A. S. Cohen, W. Duesing, V. Foerster, S. Kaboth-Bahr, K. H. Kraemer, H. F. Lamb, N. Marwan, M. A. Maslin, F. Schäbitz:
Tipping points in the 620 kyr proxy record from Chew Bahir, S Ethiopia,
6th PAGES Open Science Meeting,
(online meeting),
May 18, 2022,
Talk.
» Abstract
We have used a change point analysis (CPA) and a recurrence plot/recurrence quantification analysis (RP/RQA) on a 300 m / 620 kyr lake-sediment record from the Chew Bahir basin in the southern Ethiopian Rift to determine the amplitude and duration of past climate transitions. In this record, there are numerous transitions from wet to dry conditions, as well as from dry to wet, which show the typical characteristics of a tipping point, where the change is always faster than the forcing and the actual transition is preceded by possible precursor events. One of the most interesting transition examined with the CPA and RP/RQA was the termination of the African Humid period (15–5 kyr BP). The rapid ( 880 yr) change of climate in response to a relatively modest change in orbital forcing appears to be typical of tipping points in complex systems such as the Chew Bahir basin. If this is the case then 14 dry events at the end of the AHP at 5.5 kyr BP, each of them 20–80 yrs long and recurring every 160±40 yrs as documented in the Chew Bahir cores could represent precursors of an imminent tipping point which, if properly interpreted, would allow predictions to be made of future climate change in the Chew Bahir basin. Compared to the low-frequency cyclicity of climate variability before and after the termination of the AHP, this type of cyclicity occurs on time scales equivalent to a few human generations. In other words, it is very likely (albeit speculative) that people were conscious of these changes and adapted their lifestyles to the consequent changes in water and food availability. A deeper analysis of our data is however required to understand whether the wet-dry climate transition in the area was due to a saddle-node bifurcation in the structural stability of the climate, or whether it was induced by a stochastic fluctuation.
N. Marwan:
Palaeoclimate variability in Central America in the last 2 millenia,
Thematic Einstein Semester "The Mathematics of Complex Social Systems: Past, Present, and Future",
Berlin (Germany),
April 25, 2022,
Talk.
» Abstract
Description: (i) Stable isotope (d18O) climate record derived from stalagmite YOK-I from Yok Balum Cave in Belize, representing regional palaeoclimate variation between 40 BC and 2006 AD. (ii) Reconstruction of tropical Atlantic sea surface temperatures (SSTs) spanning the last 2000 years using seasonally representative foraminifera from the Cariaco Basin.
Background: The stalagmite based stable isotope climate record from Belize represents variability in tropical rainfall over the last 2000 years. This variability is related to a displacement of the Intertropical Convergence Zone (ITCZ) which seems to be controlled by the North Atlantic Oscillation (NAO) or changes in the tropical Atlantic sea surface temperatures (SSTs)
Original Purpose: The stable isotope record of stalagmite YOK-I is a reference record of regional past rainfall variability, used to investigate, e.g., droughts and their impact on politics, war, and population fluctuations of the Mayans. Related studies: 10.1126/science.1226299, 10.1038/srep45809, 10.1002/2013GL058458.
Questions: Is there a relationship between the SST variability of the tropical Atlantic and the rainfall variability in Belize (including leads and lags)? Does this relationship change over time? Consider uncertainties in the dating procedure and include them in the analysis.
N. Marwan:
Nonlinear Data Analysis Concepts,
Graduate School NatRiskChange, University of Potsdam,
Potsdam (Germany),
March 28-29, 2022,
Lecture.
» Abstract
The lecture introduces the basic concepts of nonlinear dynamics and chaos and how they can be applied for the study of complex systems, spatiotemporal data, and nonlinear interrelationships in geosciences. The specific topics contain
- Basic terminology, dynamical systems, and simple prototypical models
- Dimensions, fractals
- Concept of symbolic dynamics
- Concept of phase space, phase space reconstruction, Lyapunov exponent and correlation sum
- Concept of recurrence in phase space, recurrence plots, recurrence quantification analysis
- Detection of regime transitions, statistical tests
- Concept of synchronization, coupling analysis
- Spatial and spatio-temporal data analysis using recurrence features
- Complex networks, network models, measures, network representations
- Functional networks, reconstruction of networks, climate networks
- Complex networks based time series analysis
R. Krishnan, M. Singh, T. P. Sabin, B. Goswami, A. D. Choudhury, P. Swapna, R. Vellore, A. G. Prajeesh, N. Sandeep, C. Venkataraman, R. V. Donner, N. Marwan, J. Kurths:
Implications of volcanic aerosols for seasonal forecasting of the Indian monsoon in a changing climate,
Seventh WMO International Workshop on Monsoons (IWM-7),
New Delhi (India),
March 22-26, 2022,
Talk invited.
» Abstract
There is unequivocal evidence that human-induced climate change, in particular greenhouse gas (GHG) emissions, has been the main driver of the observed intensification of heavy precipitation over the land regions across the globe, and has also contributed to increases in agricultural droughts in some regions, which are further projected to enhance with additional warming during the 21st century (IPCC AR6 WG1, 2021). In addition to GHG forcing, anthropogenic aerosol emissions from the Northern Hemisphere (NH) are recognized to have influenced monsoon precipitation changes over the West African, South Asian and East Asian monsoon regions, since the second half of the 20th century (IPCC AR6 WG1, 2021). In particular, the expected enhancement of the South Asian monsoon precipitation by GHG forcing since 1950s has been offset by precipitation reduction caused by the NH anthropogenic aerosols (IPCC AR6 WG1, 2021).
Near-term climate projections for the period 2021-2040 indicate that the South Asian monsoon will be dominated by the effects of internal variability, but will increase in the long-term (IPCC AR6 WG1, 2021). In this context, it must be highlighted that uncertainties due to unpredictable natural forcings such as large volcanic eruptions can lower the degree of confidence in projecting near-term monsoonal changes. This talk is aimed to provide some insights into the role of large volcanic eruptions on the tropical atmosphere-ocean coupled system and the Indian monsoon, with implications for monsoon seasonal forecasting.
N. Marwan:
Transparent and efficient data storage,
Graduate School NatRiskChange University of Potsdam,
Potsdam (Germany),
March 14-15, 2022,
Lecture.
» Abstract
The lecture provides an overview of the need for sustainable storage of scientific data, various concepts of data storage and archiving, their planning and practical implementation, both at the personal, institutional, and public levels in publicly accessible data archives. Specific topics discussed include reproducibility and transparency, important data formats, data integrity, standards, encryption, backup, coding conventions, documentation/meta-data, and version control.
M. Gadhawe, R. Guntu, A. Banerjee, N. Marwan, A. Agarwal:
A complex network approach to study the extreme precipitation patterns in a river basin,
AGU 2021 Fall Meeting,
New Orleans (USA),
December 13–17, 2021,
DOI:10.1002/essoar.10509273.1,
Poster.
» Abstract
The spatiotemporal patterns of precipitation are critical for understanding the underlying mechanism of many hydrological and climate phenomena. Over the last decade, applications of the complex network theory as a data-driven technique has contributed significantly to study the intricate relationship between many variable in a compact way. In our work, we conduct a study to compare an extreme precipitation pattern in Ganga River Basin, by constructing the networks using two nonlinear methods - event synchronization (ES) and edit distance (ED). Event synchronization has been frequently used to measure the synchronicity between the climate extremes like extreme precipitation by calculating the number of synchronized events between two events like time series. Edit distance measures the similarity/dissimilarity between the events by reducing the number of operations required to convert one segment to another, that consider the events’ occurrence and amplitude. Here, we compare the extreme precipitation patterns obtained from both network construction methods based on different network’s characteristics. We used degree to understand network topology and identify important nodes in the networks. We also attempted to quantify the impact of precipitation seasonality and topography on extreme events. The study outcomes suggested that the degree is decreased in the southwest to the northwest direction and the timing of peak precipitation influences it. We also found an inverse relationship between elevation and timing of peak precipitation exists and the lower elevation greatly influences the connectivity of the stations. The study highlights that Edit distance better captures the network’s topology without getting affected by artificial boundaries.
T. Braun, S. Breitenbach, E. Ray, J. U. L. Baldini, L. M. Baldini, F. Lechleitner, Y. Asmerom, K. M. Prufer, N. Marwan:
Two millennia of seasonal rainfall predictability in the neotropics with repercussions for agricultural societies,
AGU 2021 Fall Meeting,
New Orleans (USA),
December 13–21, 2021,
Talk.
» Abstract
The reconstruction and analysis of palaeoseasonality from speleothem records remains a notoriously challenging task. Although the seasonal cycle is obscured by noise, dating uncertainties and irregular sampling, its extraction can identify regime transitions and enhance the understanding of long-term climate variability. Shifts in seasonal predictability of hydroclimatic conditions have immediate and serious repercussions for agricultural societies. We present a highly resolved speleothem record (ca. 0.22 years temporal resolution with episodes twice as high) of palaeoseasonality from Yok Balum cave in Belize covering the Common Era (400-2006 CE) and demonstrate how seasonal-scale hydrological variability can be extracted from δ13C and δ18O isotope records. We employ a Monte-Carlo based framework in which dating uncertainties are transferred into magnitude uncertainty and propagated. Regional historical proxy data enable us to relate climate variability to agricultural disasters throughout the Little Ice Age and population size variability during the Terminal Classic Maya collapse.
Spectral analysis reveals the seasonal cycle as well as nonstationary ENSO- and multi-decadal-scale variability. The degree to which farmers can reliably predict crop yield is both affected by long-term hydroclimate conditions and short-term variations in the subannual distribution of rainfall. A recurrence analysis reveals transitions in seasonal-scale predictability and links them to the mean hydroclimate. Predictability of seasonal rainfall variations was rendered progressively less predictable during the classic Maya collapse. These results are discussed in the context of their implications for rainfall dependent agricultural societies.
N. Marwan:
Nonlinear Time Series Analysis in Geosciences,
Kolloquium of Institute of Geoscience, University of Potsdam,
Potsdam (Germany),
December 13, 2021,
Lecture.
N. Marwan, H. Kraemer:
Hands-on workshop on complex systems,
GFZ Potsdam,
Potsdam (Germany),
November 4–5, 2021,
Lecture and workshop.
M. Kemter, N. Marwan, G. Villarini, B. Merz:
United States Flood Trends and Their Drivers,
Second International Conference on Natural Hazards and Risks in a Changing World,
Potsdam (Germany),
October 5-6, 2021,
Poster.
» Abstract
Climate change has already altered the magnitude and frequency of river floods around the world and if these trends persist in the future, our flood risk management will have to adapt to the changing conditions. However, to predict future changes, we must first understand how floods have changed in the past. Here we present a study of more than 4000 river gauges across the USA with time series of annual maximum streamflow between 1960–2010. We use a novel clustering approach to find 12 hydro-meteorologically and spatially distinct clusters of catchments with similar flood behavior. Based on re-analysis data we calculate more than 30 hydro-climatological and land-use variables to use them as predictors for 12 separate Random Forest models, one for each cluster. With these we search for the drivers of past trends in flood magnitudes, differences between common and rare floods as well as in the synchrony of floods in different catchments. We use Accumulated Local Effect plots to understand how each of the predictors affected the different trends. We find that in many regions changes in precipitation (e.g. annual precipitation sum, flood generating precipitation) translated to similar changes in flood magnitudes. Furthermore, we show that static land use conditions were of unexpected importance for flood trends, especially in the form of canopy cover, reservoirs, and impervious surfaces. We show that forests and reservoirs have mitigated some of the effects of a changing climate on floods, while urbanization has amplified them. We find varying importance and occasionally opposing effects of the same predictors in different clusters, showing that flood trends are highly dependent on the hydro-climatological circumstances of the catchments. Our results highlight the importance of a holistic approach to the analysis of flood trends and their drivers, considering a wide and consistent range of variables while taking into account the regional variability in flood generation.
A. Banerjee, B. Goswami, N. Marwan, B. Merz, B., J. Kurths:
Complex network approach to study the impacts of ENSO over the United States,
Second International Conference on Natural Hazards and Risks in a Changing World,
Potsdam (Germany),
October 5-6, 2021,
Poster.
» Abstract
Complex network analysis is a powerful tool that encodes the intricate relationship between the many components of a complex system. Functional climate network analysis is particularly designed to study the complex interactions between the different components of the Earth’s climate system. As the weather changes, the dynamical interaction between the grid points or the nodes should also change. We have used an evolving climate network approach to study this evolution of interaction between the nodes over time. In our work, we study temperature and precipitation patterns in the United States using this framework. El Niño–Southern Oscillation (ENSO) is one of the most important sources of annual global climate variability, associated with characteristic patterns of rainfall and temperature, includinng extreme events such as floods and droughts. The United States is one of the most susceptible regions to severe weather outbreaks due to the ENSO. We use Pearson correlation and edit-distance methods as similarity measures to construct temperature and extreme precipitation networks respectively.
We study the course of evolution of the link patterns using network measures such as robust links, link density, and transitivity during the different phases of the ENSO. Through our analysis, we are able to distinguish between the different phases of the ENSO, and hence, identify the different large-scale atmospheric circulation patterns associated with them.
S. M. Vallejo-Bernal, F. Wolf, N. Boers, N. Marwan, J. Kurths:
Synchronicity of heavy rainfall induced by atmospheric rivers over North America,
Second International Conference on Natural Hazards and Risks in a Changing World,
Potsdam (Germany),
October 5-6, 2021,
Poster.
» Abstract
Atmospheric rivers (ARs) are dynamical features of the low atmosphere, responsible for much of the moisture transport in the midlatitudes, that can produce copious amounts of precipitation as long as an external uplifting mechanism is available. In particular, land-falling ARs are strongly linked to heavy precipitation over the orographically complex western coast of the United States. Recently, complex network approaches have proven to effectively extract spatiotemporal variability patterns from climate data and have contributed to significant advances in the understanding and prediction of extreme weather events. In this study, we investigate the synchrony and interdependency of heavy rainfall occurrences related to ARs along the west coast of North America and the underlying physical mechanisms. We use the SIO R1 catalog of land-falling ARs and the daily rainfall estimates of the ERA5 reanalysis project during the period 1980–2018 to construct complex climate networks by applying the nonlinear Event Synchronization measure to the rainfall events above the 95th percentile. Our results reveal substantially different spatiotemporal rainfall patterns depending on the presence (or absence) of ARs. On the one hand, we find that ARs are linked with highly interconnected regions of synchronous heavy rainfall along the coastline and the adjacent Pacific Ocean. On the other hand, weaker but significant connections are observed over the continental North America in the absence of land-falling ARs. Also, the underlying atmospheric conditions differ visibly and exhibit a robust decadal pattern that is, however, highly variable for seasonal means. Resolving the typical synchrony structures of heavy rainfall related to the land-falling ARs, should lead to improved understanding of hydroclimate variability, likely leading to improved seasonal predictability of extreme precipitation.
N. Marwan:
Recent exciting developments in recurrence plot analysis,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
Talk.
» Abstract
I reported on recent achievements in recurrence plot research ten years ago. It is time to look back at the last ten years of exciting developments that had been achieved for improving recurrence plot analysis and to widen its application potential. I will give a brief overview about important and innovative developments, such as conceptual recurrence plots, ideas for parameter selection, recurrence grammars, event-like, multiscale, and heterogeneous recurrences, and correction schemes. New perspectives have recently been opened by combining recurrence plots with machine learning.
A. Das, A. P. Nandan, N. Marwan, A. Koseska:
Identifying transient metastable states from live-cell imaging data,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
Talk.
» Abstract
The current models of cellular information processing are formulated with the assumption that the relevant dynamics occur near or at the steady-state. One of the advantages when focusing on the asymptotic behavior at or near a steady-state is that it simplifies the analysis of the system. Recently, however, we proposed theoretical and practical reasons that steady-state analysis misses essential behavior of living systems, especially when describing how single cells process non-stationary signals. Using fluorescence measurements of real-time protein activities in single cells, we demonstrate that protein networks utilize transient dynamics away from steady-state to maintain a memory of previously encountered signals and thereby navigate in complex environments. To identify such out-of-equilibrium transients from experimental data in general, we develop a recurrence-based method that can be applied to a broad class of systems, without prior knowledge of the underlying dynamics of the system.
I. Pavithran, V. R. Unni, R. I. Sujith, J. Kurths, N. Marwan:
Recurrence condensation during critical transitions in complex systems,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
Talk.
» Abstract
Many dynamical systems exhibit critical transitions, which can result in catastrophic changes to the state of the system. Spontaneous emergence of an ordered dynamics from disorder is common among several systems. Even inherently turbulent systems can undergo such transition to ordered periodic dynamics. A recent discovery shows that the emergence of self-sustained periodic oscillations from an initially disordered state in various systems is accompanied by the phenomenon of spectral condensation. It is the sharpening of the peak in the amplitude spectrum accompanied by the growth of amplitude of the dominant oscillatory mode.
In the present work, we identify an analogous phenomenon known as recurrence condensation in recurrence plots (RPs) of the system variables during the transition to self-sustained periodic oscillations. We construct RPs from the time series of state variables by fixing the recurrence rate to be constant. During the transition from a chaotic state to periodic oscillations via intermittency, the RP changes from a disordered arrangement of short, broken diagonal lines to patches of ordered short diagonal lines and then to a pattern with long diagonal lines. Here, the scattered RP changes to diagonal lines, and their spacing corresponds to the dominant time scale in the system.
We aim to quantify recurrence condensation using recurrence quantification measures, an appropriate method for analyzing nonlinear, high-dimensional complex systems. Here, we use these measures to study the emergence of periodicity, which is reflected as long diagonal lines in RPs. The recurrence measures such as determinism, entropy, laminarity, and trapping time exhibit a gradual variation during recurrence condensation. Further, these recurrence measures follow a power-law scaling with the control parameter on approaching the transition. These scaling relations hold only till a critical point during the transition.
The best power-law fit with minimum scatter is observed when considering the measures only up to a particular control parameter. The fitting error increases afterwards, indicating a deviation from the scaling. Utilizing this property, we find a critical value of the control parameter up to which the recurrence measures follow scalings. Further, we construct RPs of synthetic data from a noisy Hopf bifurcation model and uncover that the value of the critical point detected is the same as the Hopf point. Our analysis indicates that the finding of the optimal power law can be used to define critical points in noisy systems with gradual transitions, where the transition point is not easily identifiable.
T. Braun, V. R. Unni, R. I. Sujith, J. Kurths, N. Marwan:
Multiscale recurrence quantification with recurrence lacunarity,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
Talk.
» Abstract
We propose Recurrence Lacunarity (RL) as a novel recurrence quantification measure. Lacunarity, as originally introduced by B.Mandelbrot (1983), is usually interpreted as a measure of heterogeneity or translational invariance of some spatial pattern. Compared to traditional recurrence quantifiers, RL offers the advantage that it is sensitive to more general geometric features beyond line structures of a recurrence plot. It is demonstrated how RL can be used to characterize the recurrence between dynamical states at all relevant time scales of a complex system. An application to time series of acoustic pressure fluctuations from a turbulent combustor showcases the great potential of RL in detecting abrupt regime shifts of different origin in nonlinear dynamical systems. Finally, potential future applications and conceptual extensions of RL are discussed.
K. H. Kraemer, F. Hellmann, J. Kurths, N. Marwan:
Recurrence powerspectra,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
Talk.
» Abstract
A novel kind of powerspectrum is constructed, the textitspike powerspectrum, which transforms spike-train-like signals into their frequency domain. This method clearly shows the apparent cycles in the data and overcomes the problems when using the obvious idea of Fourier-transforming it. We invent this instructive approach with the idea of transforming the $\tau$-recurrence rate of a recurrence plot (RP), which often has a spiky appearance. The $\tau$-recurrence rate is the density of recurrence points along diagonals of the RP, which are parallel to the main diagonal with a distance of $\tau$. In this context the spike powerspectrum can be interpreted as a nonlinear power spectrum of a potentially high dimensional system which constitutes the RP. The proposed measure is simple to compute, robust to noise and is able to detect bifurcations inducing regular-regular, regular-chaos as well as chaos-chaos transitions.
C. Ozdes, S. Breitenbach, D. Eroglu, N. Marwan, N:
Revealing past climate networks from data,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
Talk.
» Abstract
Real-world complex systems such as the climate system of interacting spatially-diverse weather patterns or ecological communities are essential parts of our everyday lives. Such systems are composed of a large number of units represented by the nodes of a network enacting an intricate interaction structure. These structures are the topic of network science, a very active research field significantly improving the quality of living standards by forecasting the dynamical behavior of complex systems. These interaction structures are also very hard to detect in climate networks, where a reconstruction procedure requires dealing with sparse and noisy data coming from multi-scale spatiotemporal dynamics. Paleoclimate data sets are also not regularly sampled, and the measurements are not precise. To model this error process, we fit a trained transformation-cost time series to paleoclimate data using the metric of segment similarity, which maximizes prior normality. This transformation-cost series can act as a regularly sampled proxy to be used in detecting the dynamical properties of data sets using recurrence quantification methods. This procedure reveals interactions that are often not detectable in the original data. We then use sliding windows analyses of these recurrence measures to obtain the temporal correlation networks that define interaction between our data sources. We use this method to reconstruct the evolution of the climate interaction network for Asia to reveal its transient and stable interaction patterns in the past.
B. G. Straiotto, N. Marwan, D. C. James, P. J. Seeley:
A combination of principal component and recurrence analyses discriminates between closely similar movement patterns,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
Talk.
» Abstract
Investigation of the movement of body segments and their coordination can provide insight into underpinning motor control strategies. We aimed to determine whether combined application of principal component and recurrence quantification analyses might discriminate between spatial and temporal aspects of apparently similar movement patterns. Backwards-forwards movements of elite (n = 9) and non-elite (n = 9) taekwondo players employed in both defensive and attacking actions were recorded using motion capture techniques, and features of whole-body movement defined at segment level were investigated by principal component analysis. For both groups of players, four movement components explained > 90% of the variability in the data.
The time series derived from scores for each of the principal components were subsequently subjected to recurrence quantification analysis, player by player. For the first component, statistically significant differences between groups were detected for the recurrence measurement determinism (p < 0.05). For the third component, statistically significant differences were detected for the recurrence measurements laminarity and maxline (p < 0.01). Application of surrogation to recurrence data indicated that differences between elite and non-elite groups were deterministic in origin and not the result of data noise ( p < 0.01).
Contrasting operation of taekwondo movements within and between our player groups were revealed qualitatively in the coefficients derived from principal component analysis and quantitatively through combined principal component and recurrence techniques. Variations in TKD player execution of this apparently simple movement pattern may represent more skilled motor control in elite players that is related to the functional importance of backwards-forwards movements in sparring and competition.
N. Marwan:
Co-authorship network of the recurrence plot domain,
9th International Symposium on Recurrence Plots,
Lublin (Poland),
September 22–24, 2021,
» Poster (PDF, 58.87M)
.
N. Marwan, T. Braun:
Module 5 – Complex Systems, Recurrence and Networks in Climate,
Summer school on Trends, rhythms and events in the Earth's climate system,
Online/ Potsdam (Germany),
August 30 – September 3, 2021,
Lecture.
» Abstract
Many processes in the Earth's climate system are complex, behave in an unpredictable way, and are nonlinearly coupled, which is why linear methods of time series analysis fail to characterize them or to uncover their complex interrelationships. This module will teach fundamental properties of complex systems and the basics of dynamical systems theory. Examples from atmospheric science and paleoclimate variability will be used to demonstrate the challenges in investigating such systems. Modern methods from nonlinear dynamics will be introduced, such as recurrence-based methods and complex networks. The students will learn in which applications these methods will provide complimentary information, how to reliably apply these methods, and how to develop corresponding statistical tests. Moreover, concepts to address common challenges in (paleo-)climate data analysis (such as heavy-tailed and event-like data, dating uncertainties, and irregular sampling) will be introduced. A focus will be on detecting subtle regime changes and complex interrelationships, where linear methods fail.
M. Kemter, N. Marwan, G. Villarini, B. Merz:
Drivers of Flood Trends in the United States,
Tag der Hydrologie,
Potsdam (Germany),
August 30 – September 1, 2021,
Poster.
I. Pavithran, V. R. Unni, A. Saha, A. J. Varghese, R. I. Sujith, J. Kurths, N. Marwan:
Predicting the Amplitude of Thermoacoustic Instability Using Universal Scaling Behaviour,
ASME Turbo Expo 2022,
Rotterdam (The Netherlands),
June 9, 2021,
Talk.
» Abstract
The complex interaction between the turbulent flow, combustion and the acoustic field in gas turbine engines often results in thermoacoustic instability that produces ruinously high-amplitude pressure oscillations. These self-sustained periodic oscillations may result in a sudden failure of engine components and associated electronics, and increased thermal and vibrational loads. Estimating the amplitude of the limit cycle oscillations that are expected during thermoacoustic instability helps in devising strategies to mitigate and to limit the possible damages due to thermoacoustic instability. We propose two methodologies to estimate the amplitude using only the pressure measurements acquired during stable operation. First, we use the universal scaling relation of the amplitude of the dominant mode of oscillations with the Hurst exponent to predict the amplitude of the limit cycle oscillations. We also present a methodology to estimate the amplitudes of different modes of oscillations separately using “spectral measures,” which quantify the sharpening of peaks in the amplitude spectrum. The scaling relation enables us to predict the peak amplitude at thermoacoustic instability, given the data during the safe operating condition. The accuracy of prediction is tested for both methods, using the data acquired from a laboratory-scale turbulent combustor. The estimates are in good agreement with the actual amplitudes.
A. Banerjee, B. Goswami, N. Marwan, B. Merz, J. Kurths:
Recurrence based coupling analysis between event-like data and continuous data,
(Virtual) EGU General Assembly,
Vienna (Austria),
April 19–30, 2021,
DOI:10.5194/egusphere-egu21-14831,
Talk.
» Abstract
Extreme events such as earthquakes, tsunamis, heat weaves, droughts, floods, heavy precipitation, or tornados – affect the human communities and cause tremendous loss of property and wealth, but can be related to multiple and complex sources. For example, a flood is a natural event caused by many drivers such as extreme precipitation, soil moisture, or temperature. We are interested in understanding the direct and indirect coupling between flood events with different climatological and hydrological drivers such as soil moisture and temperature.
We use multivariate recurrence plot and recurrence quantification analysis as a powerful framework to study the couplings between the different systems, especially the direction of coupling. The standard delay-embedding method is not a suitable for the recurrence analysis of event-like data. Therefore, we apply the novel edit-distance method to compute recurrence plots of time series of flood events and use the standard recurrence plot method for the continuous varying time series such as soil moisture and temperature. The coupling analysis is performed using the mean conditional probabilities of recurrence derived from the different recurrence plots. We demonstrate this approach on a prototype system and apply it on the hydrological data. Using this approach we are able to indicate the coupling direction and lag between the different coupled systems.
T. Braun, S. Breitenbach, E. Ray, J. U. L. Baldini, L. M. Baldini, F. Lechleitner, Y. Asmerom, K. M. Prufer, N. Marwan:
Two millennia of seasonal rainfall predictability in the neotropics with repercussions for agricultural societies,
(Virtual) EGU General Assembly,
Vienna (Austria),
April 19–30, 2021,
DOI:10.5194/egusphere-egu21-11012,
Talk.
» Abstract
The reconstruction and analysis of palaeoseasonality from speleothem records remains a notoriously challenging task. Although the seasonal cycle is obscured by noise, dating uncertainties and irregular sampling, its extraction can identify regime transitions and enhance the understanding of long-term climate variability. Shifts in seasonal predictability of hydroclimatic conditions have immediate and serious repercussions for agricultural societies.
We present a highly resolved speleothem record (ca. 0.22 years temporal resolution with episodes twice as high) of palaeoseasonality from Yok Balum cave in Belize covering the Common Era (400-2006 CE) and demonstrate how seasonal-scale hydrological variability can be extracted from δ13C and δ18O isotope records. We employ a Monte-Carlo based framework in which dating uncertainties are transferred into magnitude uncertainty and propagated. Regional historical proxy data enable us to relate climate variability to agricultural disasters throughout the Little Ice Age and population size variability during the Terminal Classic Maya collapse.
Spectral analysis reveals the seasonal cycle as well as nonstationary ENSO- and multi-decadal-scale variability. Variations in both the subannual distribution of rainfall and mean average hydroclimate pose limitations on how reliably farmers can predict crop yield. A characterization of year-to-year predictability as well as the complexity of seasonal patterns unconver shifts in the seasonal-scale variability. These are discussed in the context of their implications for rainfall dependent agricultural societies.
Z. Su, S. Gupta, N. Marwan, N. Boers, J. Kurths:
A comparative study of extreme precipitation patterns using complex networks,
(Virtual) EGU General Assembly,
Vienna (Austria),
April 19–30, 2021,
DOI:10.5194/egusphere-egu21-8740,
Talk.
» Abstract
The spatio-temporal patterns of precipitation are of considerable relevance in the context of understanding the underlying mechanism of climate phenomena. The application of the complex network paradigm as a data-driven technique for the investigation of the climate system has contributed significantly to identifying the key regions influencing the climate variability of a target region of interest and, in particular, to improving the predictability of extreme events. In our work, we conduct a comparative study of precipitation patterns by constructing functional climate networks using two nonlinear event similarity measures – event synchronization (ES) and edit-distance (ED). Event synchronization has been widely applied to identify interactions between occurrences of different climate phenomena by counting the number of synchronized events between two event series. Edit-distance measures the similarity between sequences by minimizing the number of operations required to transform one sequence to another. We suggest edit-distance as an alternative approach for network reconstruction that can measure similarity between two event series by incorporating not only event occurrences but also event amplitudes. Here, we compare the global extreme precipitation patterns obtained from both reconstruction methods based on the topological characteristics of the resulting networks. As a case study, we compare selected features of network representations of East Asian heavy precipitation events obtained using both ES and ED. Our results reveal the complex nature of the interaction between the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM) systems. Through a systematic comparison, we explore the limitations of both measures and show the robustness of the network structures.
H. Kraemer, G. Datseris, J. Kurths, I. Kiss, J. L. Ocampo-Espindola, N. Marwan:
A unified and automated approach to attractor reconstruction,
(Virtual) EGU General Assembly,
Vienna (Austria),
April 19–30, 2021,
DOI:10.5194/egusphere-egu21-1495,
Talk.
» Abstract
Since acquisition costs for sensors and data collection decrease rapidly especially in the geo-scientific fields, researchers often have to deal with a large amount of multivariable data, which they would need to automatically analyze in an appropriate way. In nonlinear time series analysis, phase space reconstruction often makes the very first step of any sophisticated analysis, but the established methods are either unable to reliably automate the process or they can not handle multivariate time series input. Here we present a fully automated method for the optimal state space reconstruction from univariate and multivariate time series. The proposed methodology generalizes the time delay embedding procedure by unifying two promising ideas in a symbiotic fashion. Using non-uniform delays allows the successful reconstruction of systems inheriting different time scales. In contrast to the established methods, the minimization of an appropriate cost function determines the embedding dimension without using a threshold parameter. Moreover, the method is capable of detecting stochastic time series and, thus, can handle noise contaminated input without adjusting parameters. The superiority of the proposed method is shown on some paradigmatic models and experimental data.
J. Fohlmeister, N. Sekhon, A. Columbu, K. Rehfeld, L. Sime, C. Veige-Pires, N. Marwan, N. Boers:
Global reorganization of atmospheric circulation during Dansgaard-Oschger cycles,
(Virtual) EGU General Assembly,
Vienna (Austria),
April 19–30, 2021,
DOI:10.5194/egusphere-egu21-9433,
Talk.
» Abstract
Ice core records from Greenland provide evidence for multiple abrupt warming events recurring at millennial time scales during the last glacial interval. Although climate transitions strongly resembling these Dansgaard-Oeschger (DO) transitions have been identified in several speleothem records, our understanding of the climate and ecosystem impacts of the Greenland warming events in lower latitudes remains incomplete.
Here, we investigate the influence of DO transitions on the global atmospheric circulation pattern. We comprehensively analyse d18O changes during DO transitions in a globally distributed dataset of speleothems (SISALv2; Comas-Bru et al., 2020). Speleothem d18O signals mostly reflect changes in precipitation amount and moisture source. Thereby this proxy allows us to infer spatially resolved changes in global atmospheric dynamics that are characteristically linked to DO transitions. We confirm the previously proposed shift of the Intertropical Convergence Zone towards more northerly positions. In addition, we find evidence for a similar northward shift of the westerly winds of the Northern Hemisphere. Furthermore, we identify a decreasing trend in the transition amplitudes with increasing distances from the North Atlantic region. This confirms previous suggestions of this region being the core and origin of these past abrupt climate changes.
M. Singh, R. Krishnan, B. Goswami, A. Dey Choudhury, S. Panickal, R. Vellore, P. A. Gopinathan, S. Narayanasetti, C. Venkataraman, R. Donner, N. Marwan, J. Kurths:
Fingerprint of volcanic forcing on the ENSO–Indian monsoon coupling,
(Virtual) EGU General Assembly,
Vienna (Austria),
April 19–30, 2021,
DOI:10.5194/egusphere-egu21-9059,
Talk.
» Abstract
The coupling between the El Niño–Southern Oscillation (ENSO) and Indian Monsoon (IM) plays a significant role in the summer rainfall over the Indian subcontinent. In this study, we provide insights into the IM variability with regard to the degree of ENSO variability and radiative forcing from large volcanic eruptions (LVEs). Volcanic dust and gas injected into the stratosphere during major eruptions influence the ENSO from seasonal to interannual timescales. However, the effects of LVEs on the ENSO-IM coupling remain unclear. The relationship between ENSO and IM systems in the context of LVEs is examined using a panoply of datasets and advanced statistical analysis techniques in this study. We find that there is a significant enhancement of the phase-synchronization between ENSO and IM oscillations due to increase in angular frequency of ENSO in the last millennium. Twin surrogates-based statistical significance testing is also used to affirm this result and similar evidence is found in the combinations of 14 ENSO and 11 IM paleoclimate proxy records in the last millennium. Bayesian probabilities conditioned with and without LVEs show LVEs lead to a strong ENSO-IM phase-coupling, with the probabilities remaining higher till the fourth year from the eruption. A large-ensemble climate model experiment with and without the 1883 Krakatoa eruption is conducted using the IITM-ESM, and also with varied volcanic radiative forcing (VRF) depending on the evolved state of ENSO. The simulations show that LVEs force the ENSO-IM systems into a coupled state, and increase (decrease) in the VRF leads to an enhanced (decreased) probability of the phase synchronisation of ENSO-IM systems with a high chance of El Niño-IM drought in the year following the LVE. Our results promisingly pave a way not only for improving the seasonal monsoon prediction improvements but also for the regional impact assessment from the proposed geo-engineering activities over the South Asian region.
W. Duesing, A. Asrat, A. S. Cohen, V. S. Foerster, S. Kaboth-Bahr, K. H. Kraemer, H. F. Lamb, N. Marwan, H. M. Roberts, F. Schaebitz:
Climate beats from Africa: a statistical analysis of the 620 kyr Chew Bahir climate record, eastern Africa,
IODP/ICDP Kolloquium,
Hamburg (Germany),
March 9-11, 2020, postponed to March 16, 2021,
Talk.
» Abstract
The sediment cores of the Chew Bahir drilling project, part of the Hominin Sites and Paleolakes Drilling Project (HSPDP), from southern Ethiopia, were used to reconstruct climatic changes by analyzing the sediment geochemistry with high-resolution XRF scanning. To interpret the multidimensional XRF dataset we computed a principal component analysis. We used the first principal component (PC1) to detect changes in variability by running a windowed standard deviation analysis and additionally a change point analysis to detect the exact timing of variability changes.
Additionally we used the established Chew Bahir log(K/Zr) aridity proxy, representing clay mineral chemistry-detrital input ratio and compared it to a new Chew Bahir climate indicator, the log(Ca/Ti) proxy, an evaporation signal that is probably inversely related to lake level stands. We find that the log(Ca/Ti) record is also an exceptionally good climate indicator because, compared to the established log(K/Zr) proxy, it reacts with greater amplitude to insolation-controlled signals such as orbital precession. This is confirmed by the log (Ca/Ti) record showing a very clear signal during the African Humid Period, which is however less pronounced in the log(K/Zr) record.
To gain a deeper understanding of the climate cycles and their temporal evolution, we computed a continuous wavelet transformation (CWT) for each of the climate proxies, and studied temporal changes in their cyclicity. Our results indicate that in addition to the precession cycle ( 20 kyr), the Chew Bahir climate record contains earth eccentricity cycles ( 100 kyr), as well as half-precession cycles during high eccentricity. During low eccentricity (450-350 kyr ago), we find reduced variability, three of five changes in standard deviation, damped precession and half precession cycles, and an abrupt transition from dry to wet climate, possibly due to climatic change in high latitudes which may be related to the Mid-Bruhnes event (MBE).
The results confirm that during high eccentricity the tropics are insolation controlled, largely independent of the high latitudes, whereas during low eccentricity the climate of tropical eastern Africa is sensitive to climatic drivers other than precession, possibly originating from high latitudes. Such a period occurring 450 to 350 kyr ago could have led to large regional differences in moisture availability and may have affected early humans by habitat separation, which by isolating populations, resulted in technological diversification. This possible scenario may help to explain the technological transition from Middle Stone Age (MSA) to Acheulean technology that was documented in the Olorgesailie basin during the same time period.
N. Marwan:
Reconstructing Complex Networks from Data,
Seminar Networks Unit, IMT School For Advanced Studies,
Lucca (Italy),
February 4, 2021,
Talk invited.
» Abstract
Complex networks provide an interesting tool to investigate spatio-temporal data. The first step is to reconstruct a (functional) network from data. I will show different reconstruction approaches depending on the research question and the nature of the data. The procedure is illustrated with applications on climate data.
M. Kemter, B. Merz, N. Marwan:
Trends in flood magnitudes, flood extents and their drivers,
AGU Fall Meeting,
online,
December 1–17, 2020,
Talk.
» Abstract
When rivers flood, they often do so simultaneously with surrounding rivers. We call the area across which this happens the flood extent. We study trends in flood extents in Europe and the US, and analyze how they are linked to trends in flood magnitude. For the time period 1960-2010 we analyze the annual maximum floods of 5000 US- and 4000 European hydrometric stations and investigate generating processes of all floods based on climate re-analysis data. We use event synchronization and complex networks to find groups of stations that have similar flood behavior. For both regions, we find a positive correlation between extents and magnitudes for 93% of the stations. While the trends of both variables are well aligned in Europe (increasing in the west, decreasing in the south), the same is not true for the US. The station groups help us to understand these differences. We show that the changing influence of snowmelt on flood generation is crucial for the relationship of magnitude and extent trends.
A. Agarwal, N. Marwan, R. Maheswaran, U. Ozturk, J. Kurths, B. Merz:
Optimal design of hydrometric station networks based on complex network analysis,
AGU Fall Meeting,
online,
December 1–17, 2020,
Talk.
» Abstract
Hydrometric networks play a vital role in providing information for decision-making in water resources management. They should be set up optimally to provide as much and as accurate information 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, yet there is 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 in the last 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), to evaluate the importance of nodes in a network. It is compared to previously proposed measures 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 network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefit of the method needs to be investigated in more detail.
T. Westerhold, N. Marwan, A. Joy Drury, D. Liebrand, C. Agnini, E. Anagnostou, J. Barnet, S. M. Bohaty, D. De Vleeschouwer, F. Florindo, T. Frederichs, D. A. Hodell, A. Holbourn, D. Kroon, V. Lauretano, K. Littler, L. J. Lourens, M. W. Lyle, H. Paelike, U. Roehl, J. Tian, R. Wilkens, Paul. A. Wilson, J. C. Zachos:
Changing state of Earth’s climate for the last 66 million years,
AGU Fall Meeting,
online,
December 1–17, 2020,
Talk.
» Abstract
We combined the best available high-resolution ocean drilling records with newly generated data to produce a continuous, astronomically tuned 66-million-year record of global climate that can serve as a new Cenozoic global reference benthic foraminiferal carbon and oxygen isotope dataset (CENOGRID). The CENOGRID represents the first community effort to systematically assemble a high-fidelity deep-sea isotope record that captures the high and low frequency variations of the climate system on a global scale, providing the framework required for understanding the nature of the major climate states, transitions and events. Within the constraints imposed by temporal resolution in older segments and potential artefacts related to differences in the regional response to orbital forcing, (e.g., obliquity), this singly unique record reveals how long-term gradual shifts in boundary conditions, principally paleogeography, ice-volume, and the mean level of greenhouse gases create state dependent shifts in the sensitivity of the climate system to periodic oscillations in solar forcing. We believe that this phenomenon is related to feedbacks associated with the carbon cycle supporting the critical role of GHG in enhancing climate sensitivity to solar radiative forcing.
N. Marwan:
Measuring complexity of recurrence plots,
GMT Morning Workshop on Nonlinear Dynamics and Statistics,
virtual,
December 3, 2020,
Talk.
N. Marwan:
Investigation of Recurrence Phenomena in the Earth System,
Seminar "Big Data Platform" at DLR Institute of Data Science,
Jena (Germany),
August 6, 2020,
Lecture.
» Abstract
Recurrence is a ubiquitous and fundamental feature in many real world processes. Here, I will focus on recurrence in the system Earth, where it is present at many scales in time and space, such as the rock cycle, activity of an active geyser, celestial mechanics, repeating patterns in a landscape, cycles of glaciation, epochs of geomagnetic polarity, or alternating sediment layers. The study of recurrence properties (such as frequency analysis) can provide deeper insights into the dynamical processes in general. A rather novel approach for the study of recurrences is the so-called recurrence plot and its quantification, rooted in the theory of dynamical systems. In this talk, I will present the basic concept and the major extensions applicable to various research questions. Discussed examples include the temporal change of recurrence properties for identification of regime shifts in climate; spatio-temporal recurrences for classification of landuse dynamics; and bivariate extensions for synchronization/coupling analysis for time scale alignment of palaeoclimate observations. Methodological and numerical Challenges and pitfalls will also be discussed.
N. Marwan:
Investigation of Recurrence Phenomena in the Earth System,
HEIBRIDS Lecture Series,
Berlin (Germany),
July 1, 2020,
Lecture.
» Abstract
Recurrence is a ubiquitous and fundamental feature in many real world processes. Here, I will focus on recurrence in the system Earth, where it is present at many scales in time and space, such as the rock cycle, activity of an active geyser, celestial mechanics, repeating patterns in a landscape, cycles of glaciation, epochs of geomagnetic polarity, or alternating sediment layers. The study of recurrence properties (such as frequency analysis) can provide deeper insights into the dynamical processes in general. A rather novel approach for the study of recurrences is the so-called recurrence plot and its quantification, rooted in the theory of dynamical systems. In this talk, I will present the basic concept and the major extensions applicable to various research questions. Discussed examples include the temporal change of recurrence properties for identification of regime shifts in climate; spatio-temporal recurrences for classification of landuse dynamics; and bivariate extensions for synchronization/coupling analysis for time scale alignment of palaeoclimate observations. Methodological and numerical Challenges and pitfalls will also be discussed.
B. Goswami, A. Hartland, C. Hu, S. Hoepker, B. R. S Fox, N. Marwan, S. F. M. Breitenbach:
Paleo-drip rates from trace metal concentrations in stalagmites: An inverse modeling problem with data uncertainties,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-19959,
Talk.
» Abstract
The concentration of trace elements such as Ni, Co, and Cu in a stalagmite is determined by (i) the amount of these elements present in so-called organic-metal complexes (OMCs) that trap the ionic forms of such elements in the dripwater, and (ii) the amount that is able to decay from the OMCs into the aqueous phase, from where the elements can adsorb to the growing stalagmite surface (and remain captured within the stalagmite crystal structure). A statistical treatment of the decay of a population of trace element ions from OMCs allow us to model the rates at which the dripwater dropped from the roof of the cave on to the stalagmite's surface. The problem is however made challenging due to: (i) the lack of reliable monitoring data that quantifies the relationship between OMC trace metal ion concentration and stalagmite trace metal ion concentration, and (ii) the presence of chronological uncertainties in our estimates of trace element concentrations at past time points from the depth-based measurements along the stalagmite. We present here a semi-heuristic, semi-theoretical approach that estimates dripwater rates using a theoretical model based on the population-level chemical kinetics of trace element decay from OMCs, and a heuristic choice of calibration data sets based on precipitation and temperature from nearby weather station data. Our approach is applied to trace metal data from the Heshang Cave in southeastern China, and we are able to reconstruct a driprate proxy time series – a first quantitative hydrological proxy record presented along with well-defined estimates of uncertainty.
T. Braun, N. Marwan, V. R. Unni, R. I. Sujith, J. Kurths:
Detection of dynamical regime transitions with lacunarity as a multiscale recurrence quantification measure,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-3475,
Talk.
» Abstract
We propose Lacunarity as a novel recurrence quantification measure and apply it in the context of dynamical regime transitions. Many complex real-world systems exhibit abrupt regime shifts. We carry out a recurrence plot based analysis for different paradigmatic systems and thermoacoustic combustion time series in order to demonstrate the ability of our method to detect dynamical transitions on variable temporal scales. Lacunarity is usually interpreted as a measure of "gappiness" of an arbitrary spatial pattern. In application to recurrence plots, it quantifies the degree of heterogenity in the temporal recurrent patterns. Our method succeeds to distinguish states of varying dynamical complexity in presence of noise and short time series length. In contrast to traditional recurrence quantifiers, no specification of minimal line lengths is required and features beyond the scope of line structures can be accounted for. Applied to acoustic pressure fluctuation time series, it captures both the rich variability in dynamical complexity and detects shifts of characteristic time scales.
K. Prufer, S. F. M. Breitenbach, J. Baldini, T. Braun, E. Ray, L. Baldini, V. Polyak, F. Lechleitner, N. Marwan, D. Kennett, Y. Asmerom:
A 1,600 year record of paleoseasonality from the neotropics of Central America and its implications for rainfall predictability in agricultural societies,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-18100,
Talk.
» Abstract
For millions of people living in the humid neotropics seasonally predictable rainfall is crucial for agricultural success and food security. Understanding long-term stability and volatility of seasonal rainfall distributions should be of concern to researchers and policy makers. However, reconstructions of paleorainfall seasonality in the neotropics have been constrained by a lack of precisely dated and sub-annually resolved records. We present a 1,600-year rainfall paleoseasonality reconstruction from speleothem sample Yok G, from Yok Balum Cave located in southern Belize, Central America. Yok G grew continuously from 400 C.E. to 2,006 C.E. and its age is constrained by 52 U-series dates with a mean error of 7 years. The isotope record consists of 7,151 δ18O and δ13C measurements at 0.22-year resolution allowing us to detect the presence and amplitude of annual wet-dry cycles. In Belize rainfall distribution and seasonality controls are currently dominated by the annual migration of the intertropical convergence zone (ITCZ) with marked meridional contrast. The Yok G record suggest distinct changes in seasonality at multi-centennial intervals. The earliest portion of the record (400- 850 C.E.) shows little intra-annual seasonal variation, the period from 850-1400 C.E. has highly variable annual oscillations and periods of low seasonality, while the period from 1,400-2,006 C.E. shows well developed seasonal signals. Element ratios (Mg/Ca, Sr/Ca, and U/Ca) are used to assess Prior Carbonate Precipitation in the epikarst system. We review these changes and the isotopic record from Yok G and discuss tools for interpreting the stability and volatility in seasonal rainfall distributions and possible implications for past and modern agricultural societies.
A. Giesche, S. F. M. Breitenbach, N. Marwan, A. Hartland, B. Plessen, J. F. Adkins, H. H. Haug, A. French, C. A. Petrie, D. A. Hodell:
Rainfall seasonality changes in northern India across the 4.2 ka event,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-16898,
Talk.
» Abstract
For millions of people living in the humid neotropics seasonally predictable rainfall is crucial for agricultural success and food security. Understanding long-term stability and volatility of seasonal rainfall distributions should be of concern to researchers and policy makers. However, reconstructions of paleorainfall seasonality in the neotropics have been constrained by a lack of precisely dated and sub-annually resolved records. We present a 1,600-year rainfall paleoseasonality reconstruction from speleothem sample Yok G, from Yok Balum Cave located in southern Belize, Central America. Yok G grew continuously from 400 C.E. to 2,006 C.E. and its age is constrained by 52 U-series dates with a mean error of 7 years. The isotope record consists of 7,151 δ18O and δ13C measurements at 0.22-year resolution allowing us to detect the presence and amplitude of annual wet-dry cycles. In Belize rainfall distribution and seasonality controls are currently dominated by the annual migration of the intertropical convergence zone (ITCZ) with marked meridional contrast. The Yok G record suggest distinct changes in seasonality at multi-centennial intervals. The earliest portion of the record (400- 850 C.E.) shows little intra-annual seasonal variation, the period from 850-1400 C.E. has highly variable annual oscillations and periods of low seasonality, while the period from 1,400-2,006 C.E. shows well developed seasonal signals. Element ratios (Mg/Ca, Sr/Ca, and U/Ca) are used to assess Prior Carbonate Precipitation in the epikarst system. We review these changes and the isotopic record from Yok G and discuss tools for interpreting the stability and volatility in seasonal rainfall distributions and possible implications for past and modern agricultural societies.
K. Riechers, N. Boers, J. Fohlmeister, N. Marwan:
Hypothesis testing and uncertainty propagation in paleo climate proxy data evidencing abrupt climate shifts,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-15148,
Talk.
» Abstract
Reconstruction of ancient climate variability relies on inference from paleoclimate proxy data. However, such data often suffers from large uncertainties in particular concerning the age assigned to measured proxy values, which makes the derivation of clear conclusions challenging. Especially in the study of abrupt climatic shifts, dating uncertainties in the proxy archives merit increased attention, since they frequently happen to be of the same order of magnitude as the dynamics of interest. Yet, analyses of paleoclimate proxy reconstructions tend to focus on mean values and thereby conceal the full range of uncertainty. In addition, the statistical significance of the reported results is sometimes not or at least not accurately tested. Here we discuss both, methods for rigorous propagation of uncertainties and for hypothesis testing with applications to the Dansgaard-Oeschger (DO) events of the last glacial interval and their varying timings in different proxy variables and archives. We scrutinized the mathematical analysis of different paleoclimate records evidencing the DO events and provide results that take into account the full range of uncertainties. We discuss several possibilities of testing the significance of apparent leads and lags between transitions found in proxy data evidencing DO events within and across different ice core archives from Greenland and Antarctica.
D.-D. Rousseau, S. Barbosa, W. Bagniewski, N. Boers, E. Cook, J. Fohlmeister, B. Goswami, N. Marwan, S. O. Rasmussen, L. Sime, A. Svensson:
Data quality in different paleo archives and covering different time scales: A key issue in studying tipping elements,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-14267,
Talk.
» Abstract
Although the Earth system is described to react relatively abruptly to present anthropogenic forcings, the notion of abruptness remains questionable as it refers to a time scale that is difficult to constrain properly. Recognizing this issue, the tipping elements as listed in Lenton et al. (2008) rely on long-term observations under controlled conditions, which enabled the associated tipping points to be identified. For example, there is evidence nowadays that if the rate of deforestation from forest fires and the climate change does not decrease, the Amazonian forest will reach a tipping point towards savanna (Nobre, 2019), which would impact the regional and global climate systems as well as various other ecosystems, directly or indirectly. However, if the present tipping elements, which are now evidenced, are mostly related to the present climate change and thus directly or indirectly related to anthropogenic forcing, their interpretation must still rely on former cases detected in the past, and especially from studies of abrupt climatic transitions evidenced in paleoclimate proxy records. Moreover, recent studies of past changes have shown that addressing abrupt transitions in the past raises the issue of data quality of individual records, including the precision of the time scale and the quantification of associated uncertainties. Investigating past abrupt transitions and the mechanisms involved requires the best data quality possible. This can be a serious limitation when considering the sparse spatial coverage of high resolution paleo-records where dating is critical and corresponding errors often challenging to control. In theory, this would therefore almost limit our investigations to ice-core records of the last climate cycle, because they offer the best possible time resolution. However, evidence shows that abrupt transitions can also be identified in deeper time with lower resolution records, but still revealing changes or transitions that have impacted the dynamics of the Earth system globally. TiPES Work Package 1 will address these issues and collect paleorecords permitting to evidence the temporal behavior of tipping elements in past climates, including several examples.
K. H. Kraemer, N. Marwan, K. Wiesner, J. Kurths:
Recurrence Plot based entropies and their ability to detect transitions,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-10861,
Talk.
» Abstract
Many dynamical processes in Earth Sciences are the product of many interacting components and have often limited predictability, not least because they can exhibit regime transitions (e.g. tipping points).To quantify complexity, entropy measures such as the Shannon entropy of the value distribution are widely used. Amongst other more sophisticated ideas, a number of entropy measures based on recurrence plots have been suggested. Because different structures, e.g. diagonal lines, of the recurrence plot are used for the estimation of probabilities, these entropy measures represent different aspects of the analyzed system and, thus, behave differently. In the past, this fact has led to difficulties in interpreting and understanding those measures. We review the definitions, the motivation and interpretation of these entropy measures, compare their differences and discuss some of the pitfalls when using them.
Finally, we illustrate their potential in an application on paleoclimate time series. Using the presented entropy measures, changes and transitions in the climate dynamics in the past can be identified and interpreted.
J. Fohlmeister, N. Bores, N. Marwan, A. Columbu, K. Rehfeld, N. Sekhon, L. Sime, C. Veiga-Pires:
Composite data set of last glacial Dansgaard/Oeschger events obtained from stable oxygen isotopes in speleothems,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-6894,
Talk.
» Abstract
Millennial scale climate variations called Dansgaard-Oeschger cycles occurred frequently during the last glacial, with their central impact on climate in the North Atlantic region. These events are, for example, well captured by the stable oxygen isotope composition in continental ice from Greenland, but also in records from other regions. Recently, it has been shown that a water isotope enabled general circulation model is able to reproduce those millennial-scale oxygen isotope changes from Greenland (Sime et al., 2019). On a global scale, this isotope-enabled model has not been tested in its performance, as stable oxygen isotope records covering those millennial scale variability were so far missing or not systematically compiled.
In the continental realm, speleothems provide an excellent archive to store the oxygen isotope composition in precipitation during those rapid events. Here, we use a newly established speleothem data base (SISAL, Atsawawaranunt et al., 2018) from which we extracted 126 speleothems, growing in some interval during the last glacial period. We established an automated method for identification of the rapid onsets of interstadials. While the applied method seems to be not sensitive enough to capture all warming events due to the diverse characteristics of speleothem data (temporal resolution, growth stops and dating uncertainties) and low signal-to-noise-ratio, we are confident that our method is not detecting variations in stable oxygen isotopes that do not reflect stadial-interstadial transitions. Finally, all found transitions were stacked for individual speleothem records in order to provide a mean stadial-interstadial transition for various continental locations. This data set could be useful for future comparison of isotope enabled model simulations and corresponding observations, and to test their ability in modelling millennial scale variability.
R. van Dongen, D. Scherler, D. Wendi, E. Deal, C. Meier, N. Marwan, L. Mao:
El Niño-Southern Oscillation (ENSO) controls on mean streamflow and streamflow variability in Central Chile,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-14011,
Talk.
» Abstract
Understanding hydrological extremes is becoming increasingly important for future adaptation strategies to global warming. Hydrologic extremes affect food security, water resources, natural hazards, and play an important role in the context of erosional processes and landscape evolution. The Pacific region is strongly affected by large-scale climatic anomalies induced by the El Niño-Southern Oscillation (ENSO). How these climatic anomalies translate into hydrological extremes is complex, because both temperature and precipitation deviate from normal conditions and the effect of this simultaneous change on hydrological processes in river catchments (e.g., snowmelt, evapotranspiration) is challenging to understand.
In this study, we investigate the effect of ENSO on mean precipitation, mean temperature, mean stream flow, and streamflow variability in Chile. We have applied extensive quality control on a large hydrological dataset from the Dirección General de Aguas in Chile, resulting in 200 good quality streamflow stations. The dataset envelopes the extent from semi-arid climate in the north ( 28°S) to humid climate in the south ( 42°S). Additionally, the dataset includes low elevation catchments located in the Coastal Cordillera and high elevation catchments in the Andes. We used the monthly Multivariate ENSO Index (MEI) to classify the 5 strongest El Niño and La Niña years, and 5 non-ENSO years after 1975. Changes in mean streamflow and streamflow variability were calculated based on the monitored data from the streamflow stations. For each river catchment, we calculated mean seasonal precipitation using the 0.25°-resolution gridded dataset from the Global Precipitation Climatology Centre (GPCC) and mean seasonal temperature using the 0.5°-resolution global temperature dataset from the Climatology Prediction Centre (CPC).
The precipitation, temperature, and discharge patterns show seasonal variation, varying in strength over the north-south gradient and between low and high elevation catchments. Mean annual precipitation generally increases significantly during El Niño events, and slightly decreases during La Niña events. For both El Niño and La Niña events the mean temperature predominantly changes between 28°S and 35°S and shows increasing temperatures in the Andes and decreasing temperatures in the low elevation Coastal Cordillera. The mean annual streamflow increases during El Niño events, and shows similarities to the pattern of increased mean annual precipitation. However, at the seasonal level, there is a time-lag between precipitation and streamflow, which is regulated by slower snowmelt processes. During La Niña events, the mean annual streamflow increases in the north (28°S-34°S) and decreases in the south (34°S-42°S). Interestingly, the mean annual precipitation and mean annual streamflow patterns behave inversely in the northern Andes. Mean streamflow increases, whereas mean precipitation decreases. This possibly results from enhanced snowmelt because of increased temperatures, but this needs to be further investigated. Finally, the magnitude and frequency of extreme floods predominantly increases in the northern Andean catchments and decreases towards the south for both El Niño and La Niña events. This study shows that large-scale climatic phenomena like ENSO affect catchment hydrology through both anomalies in precipitation and temperature.
W. Duesing, A. Asrat, A. S. Cohen, V. S. Foerster, S. Kaboth-Bahr, K. H. Kraemer, H. F. Lamb, N. Marwan, H. M. Roberts, F. Schaebitz:
Climate beats from Africa: a statistical analysis of the 620 kyr Chew Bahir climate record, eastern Africa,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-13026,
Talk.
» Abstract
The sediment cores of the Chew Bahir drilling project, part of the Hominin Sites and Paleolakes Drilling Project (HSPDP), from southern Ethiopia, were used to reconstruct climatic changes by analyzing the sediment geochemistry with high-resolution XRF scanning. To interpret the multidimensional XRF dataset we computed a principal component analysis. We used the first principal component (PC1) to detect changes in variability by running a windowed standard deviation analysis and additionally a change point analysis to detect the exact timing of variability changes.
Additionally we used the established Chew Bahir log(K/Zr) aridity proxy, representing clay mineral chemistry-detrital input ratio and compared it to a new Chew Bahir climate indicator, the log(Ca/Ti) proxy, an evaporation signal that is probably inversely related to lake level stands. We find that the log(Ca/Ti) record is also an exceptionally good climate indicator because, compared to the established log(K/Zr) proxy, it reacts with greater amplitude to insolation-controlled signals such as orbital precession. This is confirmed by the log (Ca/Ti) record showing a very clear signal during the African Humid Period, which is however less pronounced in the log(K/Zr) record.
To gain a deeper understanding of the climate cycles and their temporal evolution, we computed a continuous wavelet transformation (CWT) for each of the climate proxies, and studied temporal changes in their cyclicity. Our results indicate that in addition to the precession cycle ( 20 kyr), the Chew Bahir climate record contains earth eccentricity cycles ( 100 kyr), as well as half-precession cycles during high eccentricity. During low eccentricity (450-350 kyr ago), we find reduced variability, three of five changes in standard deviation, damped precession and half precession cycles, and an abrupt transition from dry to wet climate, possibly due to climatic change in high latitudes which may be related to the Mid-Bruhnes event (MBE).
The results confirm that during high eccentricity the tropics are insolation controlled, largely independent of the high latitudes, whereas during low eccentricity the climate of tropical eastern Africa is sensitive to climatic drivers other than precession, possibly originating from high latitudes. Such a period occurring 450 to 350 kyr ago could have led to large regional differences in moisture availability and may have affected early humans by habitat separation, which by isolating populations, resulted in technological diversification. This possible scenario may help to explain the technological transition from Middle Stone Age (MSA) to Acheulean technology that was documented in the Olorgesailie basin during the same time period.
M. H. Trauth, A. Asrat, A. S. Cohen, W. Duesing, V. Foerster, S. Kaboth-Bahr, K. H. Kraemer, H. Lamb, N. Marwan, M. A. Maslin, F. Schaebitz:
Recurrence quantification analysis of the \sim 620 kyr record of climate change from the Chew Bahir basin, southern Ethiopia,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-4660,
Talk.
» Abstract
The Chew Bahir Drilling Project (CBDP) aims to test possible linkages between climate and evolution in Africa through the analysis of sediment cores that record Quaternary environmental changes in the Chew Bahir basin. In this statistical project we used recurrence plots (PRs) together with a recurrence quantification analysis (RQA) to distinguish two types of variability and transitions in Chew Bahir and compare them with the ODP 967 wetness index from the eastern Mediterranean. The first type of variability are slow variations with cycles of 20 kyr and subharmonics of this cycle. In addition to the these cyclical wet-dry fluctuations in the area, extreme events often occur, i.e. short wet or dry episodes, lasting for several centuries or even millennia, with rapid transitions between wet and dry episodes. The second type of variability is characterized by relatively low variation on orbital time scales, but significant century-to-millennium-scale variations with increasing frequency in the course of an episode of type 2 variability. Within this type of variability there are extremely fast transitions between dry and wet, and vice versa, within a few decades or years, in contrast to those within type 1 which have transitions lasting several hundred years. Type 1 variability probably reflects the influence of precessional forcing in the lower latitudes at times of increased eccentricity, with the tendency towards extreme events, whereas type 2 variability seems to be linked with minimum values of the long (400 kyr) eccentricity cycle, and there does not seem to be a link with atmospheric CO2 levels. The different types of variability and transitions certainly had a completely different influence on the availability of water, food and shelter, and hence eastern Africa's biotic environment, including the habitat of H. sapiens.
M. Kemter, B. Merz, N. Marwan, S. Vorogushyn, G. Blöschl:
Mutual increases in flood extents and magnitudes intensify flood hazard in Central and Western Europe,
(Virtual) EGU General Assembly,
Vienna (Austria),
May 4-8, 2020,
DOI:10.5194/egusphere-egu2020-4731,
Talk.
» Abstract
Climate change has led to changing flood synchrony scales (extents) and flood magnitudes across Europe. We discovered a tight alignment between extents and magnitudes and found the drivers of their joint trends. We analyzed the annual maximum floods of 3872 hydrometric stations across Europe from 1960-2010 and classified all floods in terms of their generating processes based on antecedent weather conditions. There is a positive correlation between flood extents and magnitudes for 95% of the stations. While both parameters increased in Central and Western Europe, they jointly decreased in the East. This widespread magnitude extent correlation is caused by similar correlations for precipitation, soil moisture and snowmelt. We found trends in the relevance of the different flood generation processes, which explain the regional flood trends. The aligned increases of flood extents and magnitudes emphasize the growing importance of transnational flood risk management.
A. Krishnan, R. Manikandan, P. R. Midhun, K. V. Reeja, V. R. Unni, R. I. Sujith, N. Marwan, J. Kurths:
Suppression of oscillatory instability in turbulent reactive flows using network theory,
Complex Dynamical Systems and Applications 2020 (CDSA 2020), Central University of Rajasthan,
Ajmer (India),
February 22, 2020,
Talk.
A. Hartland, B. Goswami, C. Hu, B. Fox, N. Marwan, S. F. M. Breitenbach:
Stalactite flow rates in a central Chinese cave over the last 9000 years,
AGU Fall Meeting,
San Francisco (USA),
December 9–13, 2019,
Talk.
» Abstract
Chinese stalagmites represent unparalleled archives of past East Asian monsoon dynamics. However, the so-called 'amount effect' which links stalagmite oxygen isotope (δ18O) values to monsoon intensity is increasingly questioned. This study introduces a new method to quantitatively reconstruct stalactite discharge (drip rates) to stalagmites, representing a direct hydrological proxy that measures karst aquifer recharge, and by extension effective rainfall. Heshang Cave stalagmite HS4, from central China, grew under a perennial drip point which fluctuates in direct response to annual effective rainfall. The cave system is among the best studied and monitored in the world, providing a strong foundation for calibrating and testing this new proxy. Our analysis shows that drip discharge is highly correlated with stalagmite δ18O, broadly following insolation throughout the Holocene, with centennial-scale variability mainly in phase with δ18O. Flow rates had peak values between 8000-6000 years BP, subsequently declining to minimum flow around 300 years BP. Drip discharge decoupled from δ18O at important intervals in the early, mid and late Holocene. While fluctuations in monsoon rains are clearly coupled to previously identified forcings, we suggest that paleoclimatic drip rates have the potential to redefine our understanding of 'monsoon failure' and to test the drivers embedded in traditional but ambiguous proxies.
N. Marwan:
Datenmanagement in den Geowissenschaften,
Institute of Geoscience, University of Potsdam,
Potsdam (Germany),
November 27, 2019,
Lecture.
» Abstract
Die Vorlesung gibt einen Überblick über die Notwendigkeit nachhaltiger Aufbewahrung wissenschaftlicher Daten, über verschiedene Konzepte zur Datenaufbewahrung, deren Planung und praktischen Umsetzung, sowohl auf persönlicher, institutioneller, als auch auf öffentlicher Ebene in öffentlich zugänglichen Datenarchiven. Konkret werden u. a. Reproduzierbarkeit und Transparenz, wichtige Datenformate, Datenintegrität, Standards, Verschlüsselung, Backup, Coding-Konventionen, Dokumentation/ Meta-Daten und Versionskontrolle besprochen
N. Marwan:
Recurrence Plot Techniques for the Investigation of Recurring Phenomena in the System Earth,
GFZ Earth Surface Seminar Series "Nonlinear Dynamics Workshop",
Potsdam (Germany),
November 11, 2019,
Talk.
N. Marwan:
Recurrence Plot Techniques for the Investigation of Recurring Phenomena in the System Earth,
Habilitation Kolloquium Institute of Geoscience, University of Potsdam,
Potsdam (Germany),
October 16, 2019,
Talk.
» Abstract
Das immer wiederkehrende Auftreten von ähnlichen Zuständen ist eine grundlegende Eigenschaft von Prozessen, die unsere belebte und unbelebte Welt formen und beeinflussen. So gibt es auch zahlreiche Beispiele geologischer und klimatischer Vorgänge sowohl auf kurzen als auch langen Zeit- und Raumskalen, wie dem El Niño-Klimaphänomen, das alle drei bis fünf Jahre auftritt, den Milanković-Zyklen, die in regelmäßigen Abständen zu Eiszeiten führen, die regelmäßige Aktivität von Geysiren, oder das mehr unregelmäßige aber trotzdem wiederkehrende Auftreten von Erdbeben. Die Wiederkehr von Zuständen solch eines dynamischen Prozesses erzeugt ein typisches Wiederkehrmuster, das mit einem Verfahren aus der nichtlinearen Zeitreihenanalyse untersucht werden kann, den sogenannten recurrence plots. In der Habilitation werden fortgeschrittene Aspekte dieser Methodik besprochen. Diese beinhalten
- die Bedeutung der Strukturen und Informationen in recurrence plots,
- die Erweiterung zur Beschreibung räumlich und raumzeitlich wiederkehrender Muster, deren Anwendung zur Identifizierung von
- abrupten Änderungen in der Dynamik und
- äußeren Einflüssen auf die Dynamik eines Systems als auch
- Kopplungen zwischen verschiedenen Systemen,
- eine Kombination mit der Methodik der komplexen Netzwerke,
- Modifikationen zur Behandlung typischer Probleme mit geowissenschaftlichen Daten, wie unregelmäßiges Datensampling und Unsicherheiten in den Daten,
- die Entwicklung eines Signifikanztests und schließlich
- einen Überblick typischer Fehler, die im Zusammenhang mit dieser Methode auftreten können und wie man diese vermeidet.
Neben den methodischen Aspekten werden Anwendungsmöglichkeiten vor allem für geowissenschaftliche Fragestellungen vorgestellt, wie die Analyse von Klimaänderungen, von externen Einflußfaktoren auf ökologische oder klimatische Systeme, oder der Landnutzungsdynamik anhand von Fernerkundungsdaten.
H. Kraemer, N. Marwan:
Border effect corrections for diagonal line based Recurrence Quantification Analysis measures,
16th International Workshop on Complex Systems and Networks,
Berlin (Germany),
September 16, 2019,
Talk.
» Abstract
Recurrence quantification analysis (RQA) is a powerful tool for the identification of characteristic dynamics and of regime changes. This approach is successfully applied in many scientific disciplines. Several measures of complexity are defined on features (such as diagonal and vertical lines) in the recurrence plot (RP) and the corresponding recurrence network (RN). These line structures represent typical dynamical behavior and can be related to certain properties of the dynamical system, e.g., chaotic or periodic dynamics. Therefore, their quantitative study by the RQA measures within sliding windows is a frequently used task for the detection of regime changes. However, as some RQA measures rely on the probability distribution of the lengths of the diagonal lines in an RP, the artificial alteration of these lines due to border effects, insufficient embedding, or a certain sampling setting can have a significant impact on these measures. A few ideas have been suggested to overcome problems. Here we review these ideas, propose novel correction schemes, and systematically compare them. Specifically, we investigate the proper estimation of the diagonal line length entropy for exemplary systems (discrete and continuous). We propose corrections schemes, which yield less biased estimates, especially under noise.
N. Marwan, H. Kraemer, B. Goswami, D. Eroglu, S. Breitenbach, J. Leonhardt:
Quantifiers from Recurrence Plots,
Quantitative paleoenvironments from speleothems workshop, Waikato University,
Cambridge (New Zealand),
September 10, 2019,
Talk.
N. Marwan:
Entropies from Recurrence Plots,
Seminar, Fudan University,
Shanghai (China),
August 26, 2019,
Talk.
N. Marwan, H. Kraemer, K. Wiesner, S. Breitenbach, J. Leonhardt:
Recurrence based entropies,
8th International Symposium on Recurrence Plots,
Zhenjiang (China),
August 21-23, 2019,
Talk.
» Abstract
Dynamical processes in Earth Sciences are generally considered to be of complex nature. The term complexity is frequently used for processes that are either unpredictable (e.g. nonlinear dynamics), consist of many different components, or exhibit regime transitions (e.g. tipping points). To measure complexity, the Shannon entropy is mainly used.
Here we present various entropy measures that have been defined on the base of the recurrence plot. Because of the different features used, these entropy measures represent different aspects of the analysed system and, thus, behave differently. In the past, this fact has lead to difficulties in interpreting and understanding those measures. We summarize the definitions, the motivation and interpretation of these entropy measures, compare their differences and discuss some of the pitfalls when using them.
Finally, we illustrate their potential by applying them on a speleotheme-based palaeoclimate record from Blessberg Cave (Germany). Using entropy measures, the alternating influence of continental versus maritime climate in past central Europe can be identified.
H. Kraemer, N. Marwan:
Border effect corrections for diagonal line based recurrence quantification analysis measures,
8th International Symposium on Recurrence Plots,
Zhenjiang (China),
August 21-23, 2019,
Talk.
» Abstract
Recurrence quantification analysis (RQA) is a powerful tool for the identification of characteristic dynamics and of regime changes. This approach is successfully applied in many scientific disciplines. Several measures of complexity are defined on features (such as diagonal and vertical lines) in the recurrence plot (RP), which represents time points $j$ when a state $\vec{x}_i$ at time $i$ recurs. These line structures represent typical dynamical behavior and can be related to certain properties of the dynamical system, e.g., chaotic or periodic dynamics. Therefore, their quantitative study by the RQA measures within sliding windows is a frequently used task for the detection of regime changes. However, as some RQA measures rely on the probability distribution of the lengths of the diagonal lines in an RP, the artificial alteration of these lines due to border effects, insufficient embedding, or a certain sampling setting can have a significant impact on these measures. A few ideas have been suggested to overcome the mentioned problems. Here we review these ideas, propose novel correction schemes, and systematically compare them.
Specifically, we investigate the proper estimation of the diagonal line length entropy for exemplary systems (discrete and continuous). We propose corrections schemes, which yield less biased estimates, especially under noise.
I. Pavithran, P. Kasthuri, A. Krishnan, S. A. Pawar, R. I. Sujith, R. Gejji, W. E. Anderson, N. Marwan, J. Kurths:
Recurrence networks of spiky signals,
8th International Symposium on Recurrence Plots,
Zhenjiang (China),
August 21-23, 2019,
Talk.
» Abstract
Thermoacoustic instability is a challenging problem faced in gas turbines and rockets. It is a state of self-sustained large amplitude periodic oscillations arising due to the positive feedback between the unsteady heat release rate oscillations and the acoustic field in a confinement. The large amplitude oscillations occurring during thermoacoustic instability are detrimental and their presence can lead to increased heat transfer, violent vibrations causing fatigue failure of the components and even mission failure in rockets. Thermoacoustic system involves interaction between processes at different timescales and length scales leading to complex spatio-temporal dynamics.
In order to study the transitions to such oscillatory instabilities in a complex system, we use a complex networks approach. Complex network is an efficient tool to study systems composed of different interacting entities. Various types of networks have been used in literature such as correlation networks, visibility graphs, recurrence networks, cycle networks, etc. Among these networks, recurrence-based complex networks (RNs) provide information about the topology of the attractor in high dimensional phase space. We can interpret the characteristics of the networks in terms of geometric properties of the phase space.
In the present work, we construct recurrence networks from the time series of acoustic pressure fluctuations obtained during different dynamical regimes from a liquid rocket combustor. We notice that the dynamics of acoustic pressure during thermoacoustic instability is akin to a spiky periodic signal. Such behaviour of the pressure signal is in contrary to the sinusoidal variation observed during thermoacoustic instability in gas turbine combustors. Previous studies have shown that the RN during thermoacoustic instability in gas turbines display a ring-like structure. We unravel a different pattern in RN for a rocket combustor which shows protrusions at different locations on the ring-like structure. These extra patterns are found to be exhibited due to the spiky nature of the time series. We create synthetic time series similar to the experimental data to explain this particular topology. The reconstructed phase space of such largely unexplored signals allows us to get deeper insights about the underlying dynamics of the system. Further, complex networks based on recurrences are an appropriate method for analysing highly nonlinear, high dimensional complex systems.
A. Banerjee, B. Goswami, N. Marwan, B. Merz, J. Kurths:
Recurrence analysis of flood events,
8th International Symposium on Recurrence Plots,
Zhenjiang (China),
August 21-23, 2019,
Poster.
» Abstract
Extreme hydrological events such as floods severely affect the communities living in the corresponding river basins and result in tremendous loss of property and wealth.
The aim of this work is to investigate flood behavior with respect to local effects, e.g. implementation of flood retention basins, and external controls by using recurrence analysis. Flood events occur at irregular time intervals and have a heavy tailed distribution, hence, such data often require data preprocessing and special methods able to analyze data with heavy tailed distribution. In this study, we use the edit distance approach in combination with recurrence plots and recurrence quantification analysis to investigate flood events.
The edit distance approach allows us to use the recurrence-based characteristics to quantify how the dynamics of the flood occurrence has changed over time. We apply our approach to the river discharge data from the river Elbe and study the dynamical interactions of different variables such as precipitation, temperature and catchment wetness.
H. Kraemer, R. Donner, J. Heitzig, N. Marwan:
Recurrence threshold selection for obtaining robust recurrence characteristics in different embedding dimensions,
8th International Symposium on Recurrence Plots,
Zhenjiang (China),
August 21-23, 2019,
Poster.
» 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.
N. Marwan:
Co-authorship network of the recurrence plot domain,
8th International Symposium on Recurrence Plots,
Zhenjiang (China),
August 21-23, 2019,
Poster.
» Abstract
A presentation of the co-authorship network of publications on recurrence plots, recurrence networks and recurrence quantification analysis.
N. Marwan:
Karstgebiet Sägistal,
14. Nationaler Höhlenforscher-Kongress Sinterlaken19,
Interlaken (Switzerland),
August 9-11, 2019,
Talk.
» Abstract
Das Sägistal ist ein abgelegenes Hochtal der Berner Voralpen mit typischen Karsterscheinungen. Die Erforschung der Höhlen begann in den 1970er Jahren durch die SGH Interlaken und wird seit 1988 durch die Internationale Speläologische Arbeitsgruppe Alpiner Karst (ISAAK) unter Beteiligung zahlreicher Höhlenforschergruppen aus verschiedenen Ländern organisiert. Mittlerweile wurden über 400 Höhlen gefunden mit dem "Oberländer-Chessiloch"-System als größtem Objekt (2346 m Länge, -488 m Tiefe).
D. Wendi, B. Merz, N. Marwan:
Novel quantification method for hydrograph similarity,
SimHydro 2019,
Sophia Antipolis (France),
June 12, 2019,
Talk.
» Abstract
We propose an additional elaborate hydrological signature index to quantify similarity (and dissimilarity) between recurring flood dynamics and between observation and model simulation as implied by their phase space trajectories. These phase space trajectories are reconstructed from their corresponding hydrographs (i.e., event time series) using Taken's time delay embedding method. This reconstructed phase space allows multi-dimensional relationship between observation points (i.e., at different time of the event) to be analyzed. Such approach considers the relationships of set of magnitude points in their unique time sequence that are relevant to the complex temporal cascading processes in flood. In a simpler terms, the new index considers the characteristics shape dynamics of a hydrograph and optionally the antecedent discharge conditions that may implicitly cascade to the subsequent rainfall-runoff event and cause an extreme or unusual hydrograph shape. This new similarity index can be used to comprehensively assess the recurrence of extreme event characteristics, change of flood dynamics, shift of seasonality, and as additional metric or objective function to evaluate and calibrate hydrological and hydraulics models.
N. Marwan:
Recurrence Plots for Time Series Analysis,
Geological Remote Sensing Seminar, University of Potsdam,
Potsdam (Germany),
June 4, 2019,
Lecture.
U. Ozturk, N. Malik, K. Cheung, N. Marwan, J. Kurths:
Tracking tropical and frontal storms driven extreme rainfalls over Japan using complex networks,
SIAM Workshop on Network Science 2019,
Snowbird (USA),
May 22-23, 2019,
Talk.
» Abstract
Predicting extreme rainfall is a challenging but a necessary task due to the concomitant natural hazards, such as flash floods or landslides. Theory of network science offers alternative tools to explore the spatiotemporal properties of extreme rainfall, which might reveal the predictive behavior of those extremes. In this case study, we use complex network metrics in conjunction with a nonlinear correlation measures of event synchronization to study extreme rainfall generated by the tropical and frontal (Baiu) storms over Japan. These two weather systems trigger extreme events in two discrete seasons; the Baiu front dominates the rainfall events from June to July, whereas tropical storms activity peak at August, and are active until November. We found that the spatial scales involved in the Baiu driven rainfall extremes are consistently more extensive than the extremes due to tropical storms. We further delineate an east-west extending horizontal region of coherent rainfall during Baiu season based on network communities, whereas nearly all Japan fall in one single coherent rainfall community during tropical storm season.
N. Marwan, H. Kraemer, K. Wiesner, S. Breitenbach, J. Leonhardt:
Recurrence based entropies,
Fourth International Conference on Recent Advances in Nonlinear Mechanics,
Łódz (Poland),
May 7-10, 2019,
Talk.
N. Marwan, H. Kraemer, K. Wiesner, S. Breitenbach, J. Leonhardt:
Recurrence based entropies,
EGU General Assembly,
Vienna (Austria),
April 7-12, 2019,
» Poster (PDF, 6.42M)
.
» Abstract
Dynamical processes in Earth sciences are often considered to be of complex nature. The term complexity is often used for processes that are either unpredictable (e.g. nonlinear dynamics), consist of many different components, or exhibit regime transitions (e.g. tipping points). To measure complexity, the Shannon entropy is often used. Here we present various entropy measures that have been defined on the base of the recurrence plot. Because of the different features that are used, these entropy measures represent different aspects of the analysed system and, thus, behave differently. In the past, this fact has lead to difficulties in interpreting and understanding those measures. We summarize the definitions, the motivation and interpretation of these entropy measures, compare their differences and discuss some of the pitfalls when using them.
Finally, we illustrate their potential in an application on palaeoclimate time series. Using entropy measures, changes and transitions in the climate dynamics in the past can be identified and interpreted.
W. Düsing, H. Kraemer, A. Asrat, M. Chapot, A. Cohen, A. Deino, V. Foerster, H. Lamb, N. Marwan, C. Lane, M. Maslin, C. Ramsey, H. Roberts, F. Schaebitz, M. Trauth, C. Vidal:
Differentiating local from regional climate signals using the 600 ka Chew Bahir paleoclimate record from South Ethiopia,
EGU General Assembly,
Vienna (Austria),
April 7-12, 2019,
Talk.
» Abstract
Cores from terrestrial archives, such as the lacustrine sediments from the Chew Bahir basin in southern Ethiopia, which cover the last 600 ka, often reflect both local, regional and global climate influences. In our analysis we were able to identify several time windows in which the Chew Bahir climate is in resonance with regional and global climate change.
As a contribution to understanding and differentiating these connections recorded in the Chew Bahir sediments, we have correlated the 2nd principal component of the MSCL based color reflectance values representing wet conditions in the Chew Bahir basin, with the wetness index from ocean core ODP 967 from the eastern Mediterranean Sea. The correlation between these two time series was calculated using the Spearman correlation coefficient in a sliding window. Episodes with high correlation between the two records of wetness could indicate a strong link between both regions, possibly through an increased outflow of the river Nile into the eastern Mediterranean Sea due to higher precipitation values on the Ethiopian plateau.
Our preliminary results show that when correlating the two records, two distinct temporal units can be distinguished. Between 570 ka and 350 ka the correlation is dominated by cycles that correspond with orbital precession whereas the second unit (after 350 ka) reveals a strong influence of atmospheric CO2. This observation suggests that both orbital precession and atmospheric CO2. may cause a synchronization of different regions in the African climate system, possibly depending on boundary conditions which are still to be identified.
As a next step we'll investigate the nonlinear relationships between the two records by focusing on the transition between the two main observed phases. The transition around 350 kyrs however, is not only highly interesting from a climatic perspective, but it is also a noteworthy period for human cultural evolution as a transition from Acheulean to Middle Stone Age (MSA) technologies takes place at this time. So far our results outline that during this climatically and evolutionary relevant episode a relatively stable, long-lasting, pan-African wet phase may have existed, with possible green corridors connecting the habitats of hominins, and ample resources supporting large population sizes.
A. Banerjee, B. Goswami, N. Marwan, B. Merz, J. Kurths:
Recurrence Analysis of Flood Events,
EGU General Assembly,
Vienna (Austria),
April 7-12, 2019,
Poster.
» Abstract
Extreme hydrological events such as floods severely affect the communities living in the corresponding river basins and result in tremendous loss of property and wealth.
The aim of this work is to investigate flood behavior with respect to local effects, e.g. implementation of flood retention basins, and external controls by using recurrence analysis. Flood events occur at irregular time intervals and hence such data often requires data preprocessing. In this study, we use the TACTS approach in combination with recurrence plot and recurrence quantification analysis to investigate flood events, which occur on irregular time scales.
The TACTS approach allows us to construct a recurrence plot from the irregularly spaced flood event series, and the recurrence-based characteristics help to quantify how the dynamics of the flood occurrence have changed over time. We apply our approach to the 150-year river discharge data from the river Elbe and study the dynamic interactions of different variables such as precipitation, temperature and catchment wetness.
A. Agarwal, L. Caesar, N. Marwan, R. Maheswaran, B. Merz, J. Kurths:
Detection of short- and long-range teleconnections in SST patterns on different time scales,
EGU General Assembly,
Vienna (Austria),
April 7-12, 2019,
Poster.
» Abstract
Sea surface temperature (SST) anomaly patterns can - as surface climate forcing -affect the weather at large distances. This is why following an El Niño event major global climate anomalies occur. This paper characterizes the links between the cells of a global SST grid data set at different temporal and spatial scales with the help of climate networks. These networks are constructed using wavelet multi-scale correlation. This way we identify and visualise the SST patterns that develop very similarly over time and distinguish them from those that have long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like El Niño Southern Oscillation and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections.
M. Kemter, B. Merz, N. Marwan:
Using multi-layer complex networks to understand interrelationships and changes in extreme flood generation,
EGU General Assembly,
Vienna (Austria),
April 7-12, 2019,
Poster.
» Abstract
The generation of extreme flood events is influenced by a multitude of parameters that interact in complex ways. To understand their temporal and spatial relationships as well as changes in this system we need adequate tools. We therefore use multilayer complex networks and extreme event statistics to discover and interpret relationships between flood influencing parameters (e.g. precipitation, catchment wetness, discharge). Complex networks have formerly been successfully used for climatic and hydrological representations. A multilayer approach enables us to find inter-relationships between the different influences. We use non-linear similarity measures to generate the network connections. By analysis of variations of the network appearance and metrics with time, we can reconstruct temporal changes in the underlying processes.We are investigating several hundred river gauges across Europe over a timeframe of 70 years.
M. Trauth, A. Asrat, C. Bronk Ramsey, M. Chapot, A. Cohen, A. Deino, W. Duesing, V. Foerster, H. Kraemer, H. Lamb, C. Lane, N. Marwan, M. Maslin, H. Roberts, F. Schaebitz, C. Vidal:
Recurring types of variability and transitions in the \~280 m long (\~600 kyr) sediment core from the Chew Bahir basin, southern Ethiopia,
EGU General Assembly,
Vienna (Austria),
April 7-12, 2019,
Poster.
» Abstract
The Chew Bahir Drilling Project (CBDP) aims to test hypothesized linkages between climate and human evolution, dispersal and technological innovation by the acquisition and analysis of long (280 m) sediment cores that have recorded environmental change in the Chew Bahir basin, southern Ethiopia. In this time-series analysis project, we consider the Chew Bahir palaeolake to be a dynamical system consisting of interactions between its different components, such as the waterbody, the sediment beneath lake, and the organisms living within and around the lake, and humans within the lake catchment. Recurrence is a common feature of such dynamical systems, with recurring patterns in the state of the system reflecting typical influences. Identifying and defining these influences contributes significantly to our understanding of the dynamics of the system.
We use methods of linear and nonlinear time series analysis, such as change point detection, semblance analysis and recurrence plots, to identify and classify recurring types of variability and transitions on the time scales of human life spans. For example, we investigate the rapidness of transitions, possible precursor events, and tipping points in our palaeoenvironmental data and discuss their possible impact on the living conditions of humans in the region. First results of the analysis show that we indeed find, as an example, recurring threshold-type transitions, when the Chew Bahir system switched from one stable mode to another, such as from stable wet to dry conditions. Such a rapid change of climate in response to a relatively modest change in forcing appears to be typical of tipping points in complex systems such as the Chew Bahir. If this is the case then the 14 dry events idenfified at the end of the African Humid Period (15-5 kyr BP) could represent precursors of an imminent tipping point that, if properly interpreted, would allow predictions to be made of future climate change in the Chew Bahir basin.
N. Marwan:
Recurrence Plots for Time Series Analysis,
Seminar at MPI Molecular Physiology,
Dortmund (Germany),
March 18, 2019,
Talk.
N. Marwan:
Transparent and efficient data storage,
Graduate School NatRiskChange University of Potsdam,
Potsdam (Germany),
March 13-14, 2019,
Lecture.
» Abstract
The lecture provides an overview of the need for sustainable storage of scientific data, various concepts of data storage and archiving, their planning and practical implementation, both at the personal, institutional, and public levels in publicly accessible data archives. Specific topics discussed include reproducibility and transparency, important data formats, data integrity, standards, encryption, backup, coding conventions, documentation/meta-data, and version control.
W. Duesing, J. Thom, A. Deino, A. Asrat, V. Foerster, H. Kraemer, N. Marwan, H. Lamb, F. Schaebitz, M. H. Trauth:
Human evolution and climate change: What can we learn from the 0-630 kyrs BP paleoclimate record from the Chew Bahir basin in eastern Africa?,
AGU Fall Meeting,
Washington DC (USA),
December 10-14, 2018,
Talk.
» Abstract
Numerous authors have developed hypotheses linking climate, the environment and human evolution, expansion and technological innovation in eastern Africa (e.g., Potts, 2013, Potts et al. 2018; Maslin et al., 2015). The Chew Bahir Drilling Project (CBDP) as part of the Hominin Sites Paleolakes Drilling Project (HSPDP) aims to test some of these hypotheses by providing a long, continuous and high-resolution paleoclimate records of climatic and environmental change through critical intervals of human evolution.
Testing such hypothesis requires a very accurate age model both for the paleoclimate record, but also for the archeological/anthropological evidence. We therefore developed a MATLAB-based Multiband Wavelet Based Age Modeling Technique (mubawa), which generates an orbital tuned age model that comprises uncertainties. Next, we use a piecewise correlation using a set of different sliding windows to compare the Chew Bahir paleo records on different time scales with Indian Ocean SSTs, Terrestrial Dust and Nile-Outflow records. To classify variability and transitions we use recurrence plots/recurrence quantification analysis. Application of this method detects nonlinear features such as tipping points, which are often coherent with changes in variability and strong precursor events. The recurrences of such precursor events often lie within the life span of hominins. For individuals living during that time these drastic climate shift were perceptive and probably provoked new survival strategies that may have preserved in the archeological record.
In a last step we evaluate if these detected climate and environmental shifts can be related to archeological sights, human evolution, technological innovation, migration and dispersal events.
E. Macau, A. M. Ramos, J. Kurths, N. Marwan:
Detecting causal relations from real data experiments by using recurrence,
Dynamics Days Latin America and the Caribbean 2018,
Punta del Este (Uruguay),
November 26-30, 2018,
Talk.
» Abstract
In this work, we present the Recurrence Measure of Conditional Dependence (RMCD), a recent data-driven causality inference method using the framework of recurrence plots. The RMCD incorporates the recurrence behavior into the transfer entropy theory. We apply this methodology to some paradigmatic models and to investigate the possible influence of the Pacific Ocean temperatures on the South West Amazon for the 2010 and 2005 droughts. The results reveal that for the 2005 drought there is not a significant signal of dependence from the Pacific Ocean and that for 2010 there is a signal of dependence of around 200 days. These outcomes are confirmed by the traditional climatological analysis of these episodes available in the literature and show the accuracy of RMCD inferring causal relations in climate systems.
T. Vantuch, I. Zelinka, A. Adamatzky, N. Marwan:
Detecting causal relations from real data experiments by using recurrence,
17th International Conference on Unconventional Computation and Natural Computation,
Fontainebleau (France),
June 26, 2018,
Talk.
» Abstract
Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that swarms optimisation algorithms also exhibit transitions from chaos, analogous to motion of gas molecules, when particles explore solution space disorderly, to order, when particles follow a leader, similar to molecules propagating along diffusion gradients in liquid solutions of reagents. We analyse these ‘phase-like’ transitions in swarm optimization algorithms using recurrence quantification analysis and Lempel-Ziv complexity estimation. We demonstrate that converging and non-converging iterations of the optimization algorithms are statistically different in a view of applied chaos, complexity and predictability estimating indicators.
W. Duesing, A. Asrat, V. E. Foerster, H. Kraemer, H. F. Lamb, N. Marwan, F. Schaebitz, M. H. Trauth:
Trends, rhythms and transitions during the Late Quaternary in southern Ethiopia,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
Poster.
» Abstract
This project aims at statistically analyzing the long ( 278 m) sediment record of the Chew Bahir basin, as part of the ICDP-funded Hominin Sites and Paleolakes Drilling Project (HSPDP). The aim of the project is (1) to establish a robust age-depth model for the sediment cores, (2) to correlate the Chew Bahir record with other records within and outside HSPDP, (3) to detect trends, rhythms and events in the environmental record of the basin, and (4) identify recurrent, characteristic types of climate transitions in the time series, as compared with the ones of the other HSPDP sites and climate records outside HSPDP. The work presented here will provide first results of age-depth modelling, including cyclostratigraphy, of the long Chew Bahir cores. Second, it gives an overview of the first results from evolutionary spectral analysis to detect changes in the response of the Chew Bahir to orbital forcing during the last 550 kyr. Third, the results of a change point analysis will be presented to define the amplitude and duration of past climate transitions and their possible influence on the development of early modern human cultures.
M. H. Trauth, A. Asrat, W. Duesing, V. Foerster, H. Kraemer, H. Lamb, N. Marwan, M. A. Maslin, F. Schaebitz::
Classifying past climate variation in the Chew Bahir basin, southern Ethiopia, using recurrence quantification analysis,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
Poster.
» Abstract
The Chew Bahir Drilling Project (CBDP) aims to test hypothesized linkages between climate and mammalian (including hominin) evolution in tropical-subtropical eastern Africa by the acquisition and analysis of long ( 280 m) sediment cores that have recorded environmental change in the Chew Bahir basin. In our statistical project, we describe the Chew Bahir paleolake as a dynamical system composed of interacting components, such as the water body, the sediment below the bottom of the (paleo-)lake, and the organisms living in the lake and its surroundings. A common feature of dynamical systems is the property of recurrence, where patterns of recurring states reflect typical system characteristics whose description contribute significantly to understanding its dynamics. In our example it could be a recurrence of changes in the state variables precipitation, evaporation and wind speed, which lead to similar (but not identical) conditions in the lake (e.g., depth and size of the lake, alkalinity and salinity of the lake water, species assemblage in the water body, diagenesis in the sediment). A recurrence plot (RP), first introduced by J.P. Eckmann in 1987, is a graphical display of such recurring states of the system, calculated from the distance (e.g. Euclidean) between all pairs of observations x(t), within a cutoff limit. To complement the visual inspection of recurrence plots, measures of complexity were introduced for their quantitative description to perform the recurrence quantification analysis (RQA). Here we present and discuss preliminary results of a RQA of the 550 kyr long environmental record from the Chew Bahir basin.
A. Agarwal, N. Marwan, M. Rathinasamy, U. Ozturk, B. Merz, J. Kurths:
Complex network-based approach for identification of influential and expandable station across rainfall network,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
Poster.
» Abstract
The complex network has gained significant momentum in last decades and has found application wide areas ranging from biological networks to climate networks. In analysing physical complex networks, identification of key influential nodes is l an important field of research. In this study, we propose a new effective node ranking method based on network measure degree and betweenness values. The proposed method is tested and compared to previously proposed node ranking methods on synthetic sample networks and then applied to a real-world raingauge network of 1229 stations from Germany to check its replicability and applicability. Raingauge networks play a vital role in providing information for making crucial decisions in water resources management and resources estimation. The network of operating raingauges should be set up optimally to provide as much and as accurate information as possible and at the same time cost-effective. The proposed method is evaluated using decline rate efficiency and kriging error. The results of the study show that the proposed method based on complex network theory for ranking the raingauges is robust and can be used for design and redesign the raingauge network. The method is very useful in identifying the highly influential station which needs high attention and expendable stations which either can be relocated, uninstalled or removed without much effect on the overall accuracy of the observations provided by the raingauge network.
D. Wendi, N. Marwan, B. Merz:
The recurrence of unseasonable and rare flood dynamics,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
» Poster (PDF, 2.26M)
.
» Abstract
The question whether a certain flood is rare/ unusual or not is often evaluated from the frequency curve analysis (also called growth curve) of flood discharge peaks and their corresponding recurrence interval (return period). Flood discharge peak and maximum depth are some of the hydrological signatures (i.e. an element of hydrograph) and are popular choice for flood risk assessment due to their close relationship with socio-economic impact of flood and often used for damage modeling. However what if our question now is whether the flood process dynamics is rare (influenced by unusual or more driving mechanism, e.g. ice jam, dam break, clogged drain, etc) and especially if hydrological boundary condition is no longer the same as before.
The confinement of flood peaks reduces the information about the flood dynamics inferred by the shape of hydrograph, especially should one be interested to evaluate a rarity/ extremity of a flood process dynamics since flood peak is just one element of a flood hydrograph. Although other indices derived from hydrological signature (e.g. volume, slopes, base flow index, etc) are useful descriptors of a process dynamics, most of them are still either just a part of hydrograph, or derived as an aggregate (e.g. slopes and volume) and therefore unable to provide bigger picture of the flood dynamics and suffer from statistical uncertainty. Furthermore, with singular descriptor from the mentioned, different flood dynamics (i.e. resulted from different processes/ boundary conditions) could be mistaken as the same and might lead to misinterpretation (e.g. snow melt and rainfall triggered runoff may easily share similar flood peak and volume). Moreover, stationarity in season is often assumed in flood frequency analysis, that different flood processes are classified to follow strict calendar month seasons. Such practice could fail to analyze the occurrence of unusual climatic event such as early or late snow melt and unseasonably heavy rainfall in winter.
In this study, we focus on the utilization of hydrological signature to characterize temporal flood event dynamics with the objective to analyze their recurrences and to be able to evaluate if a process dynamic of a certain flood is rare or perhaps unprecedented. We propose using the analysis of phase space trajectories reconstructed through time delay embedding of a time series to characterize different flood events. To allow the visualization and analysis of high embedding dimension (i.e. above 3), we suggest the use of recurrence plot (RP) and quantification (RQA) as similarity measures between the flood dynamics of one event to another and allow non-stationarity occurrence of their typology.
B. Goswami, S. Breitenbach, F. Lechleitner, J. Baldini, H. Cheng, N. Marwan:
Is this an event? – Detecting abrupt changes in palaeoclimate records,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
» Poster (PDF, 772.16K)
.
» Abstract
Abrupt shifts in a certain climate state is a pertinent question in palaeoclimate studies and is crucial for determining leads or lags between spatially disperse observations. Such events have also a direct bearing on the vulnerability of society to drastic – and possibly difficult to mitigate – changes. Determining whether or not, and when exactly, abrupt changes in climate occurred is made challenging by temporal resolution and uncertainties associated with determining the age of climate proxy measurements.
In this study, we present a robust, ‘uncertainty-aware’ approach to determine periods of abrupt change from palaeoclimate proxy records. Our method is based on a new representation of time series and it utilises the recurrence properties of the proxy record to distinguish time points of abrupt climate change. We first validate our approach with a synthetic example, and thereafter, we apply our approach to speleothem records from China and India. Our results reveal a highly non-trivial spatio-temporal pattern of the detected events in the Asian monsoon domain.
U. Öztürk, N. Malik, N. Marwan, J. Kurths:
Comparison of tropical and frontal storms using complex networks,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
Poster.
» Abstract
Complex network analysis supports exploring spatiotemporal dynamics of significant climate phenomena, such as heavy precipitation. Complex networks are able to capture the spreading and concentration of extreme rainfall by using event-synchronization, such as rainfall propagation patterns of the Indian Summer Monsoon by parameterizing the delay from precipitation time-series. Despite much advancement in monitoring extreme rainfall, capturing spatiotemporal dynamics of the fast-evolving atmospheric events (e.g., tropical storms) is still a challenge. Quantifying spatial scales of extreme rainfall will aid mitigating concomitant flood and landslide hazards.
We use network analysis to compare spatial features of extreme rainfall over Japan using satellite-derived rainfall data (TRMM-3B42V7). We first divide the time series into two subsets: June to July (JJ) and August to November (ASON) to concentrate on the Baiu front season (JJ) and the tropical storms season (ASON). We assess the spatial scales involved in the two distinct mechanisms and define regions of coherent rainfall during the two seasons. We additionally propose using radial statistics to trace the network flux over long distances, which allows us to observe the general pattern of extreme rainfall tracks. Extreme rainfall associated with tropical storms show smaller spatial scales (in the range of 100 km) compared to Baiu linked extremes. We also discovered a consistent deviation of the extreme rainfall from the eye of the tropical storm tracks.
H. Kraemer, R. V. Donner, N. Marwan, M. H. Trauth:
Detecting abrupt transitions during the Late Quaternary in southern Ethiopia using Recurrence Quantification Analyses,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
Poster.
» Abstract
In many data driven fields of research, categorizing abrupt transitions / regime changes is of high interest. The different aspects of temporal recurrence patterns of previous states can help to identify and characterize subtle changes in systems dynamics. Besides the identification of transitions, recurrence methods can provide a better understanding of the process underlying these transitions by statistically describing the dynamical characteristics, e.g. the predictability, determinism and complexity of the dynamical system. For example, the characteristic block structures in the recurrence plot can be used to identify different types of intermittency. In general, changes between different dynamical regimes are visually well expressed in recurrence plots. The introduction of selected recurrence quantifiers (such as recurrence rate, determinism, or laminarity) together with a running window approach has paved the way for a quantitative recurrence analysis of transitions and therefore should be able to provide a classification of different transition types.
In order to achieve such a classification there is necessity for developing a method which is capable to statistically analyze the behavior of recurrence quantifiers at transitions. In this work, we show how to make statements about the significance of estimated values of recurrence quantifiers using a bootstrap approach. We also highlight the specific technical problems related to that task. The presented method also allows gaining information about the duration of a transition. Here we demonstrate potentials of the proposed approach to detect abrupt transitions in (1) prototypical models of transitions as well as in (2) real data of past climate variations in the Chew Bahir basin (South Ethiopia), investigated within the Hominin Sites and Paleolakes Drilling Project (HSPDP).
B. Goswami, N. Boers, A. Rheinwalt, N. Marwan, J. Heitzig, S. Breitenbach, J. Kurths:
Identifying sudden dynamical shifts in time series with uncertainties,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
Poster.
S. Breitenbach, B. Plessen, S. Waltgenbach, R. Tjallingii, J. Leonhardt, K.-P. Jochum, H. Meyer, N. Marwan, D. Scholz:
Tracing past shifts of the boundary between maritime and continental climate over Central Europe,
EGU General Assembly,
Vienna (Austria),
April 8-13, 2018,
Poster.
» Abstract
European climate is characterized by heterogeneous climate conditions, with distinct boundaries between zones that can be classified according to the Köppen classification (Peel et al. 2007), and detected using climate network techniques (Rheinwalt et al. 2016). These boundaries are not stationary, but shift geographically, depending on large scale atmospheric conditions.
Central European climate is strongly influenced by intricately linked North Atlantic Oscillation and Siberian High (SH), which govern precipitation and temperature over Europe. Shifts of these climatic boundaries in response to global warming and circulation changes might lead to more frequent extreme weather patterns like heat waves, with significant repercussions for society (Cohen et al. 2014).
Speleothem-based palaeoclimate reconstructions enable us to understand underlying forcing mechanisms and speed of climatic reorganizations. Here we present a first reconstruction of multi-centennial shifts of the boundary between western European maritime Cfb climate and continental Dfb climate through the last ca. 5,000 years using speleothems from Bleßberg Cave, Thuringia, Central Europe.
Thanks to its location near the Cfb-Dfb climatic boundary, Bleßberg Cave is ideally suited to reconstruct past W-E shifts of this divide longitudinally crossing Central Europe. We compare a decadally resolved stalagmite δ18O record with data from Bunker Cave (Mischel et al. 2017), western Germany, and an NAO reconstruction from Greenland (Olsen et al. 2012).
Over the last 5,000 years, the boundary between Cfb and Dfb climate shifted repeatedly. When the Cfb-Dfb border was east (west) of Bleßberg (Bunker) Cave maritime (continental) climate prevailed at both sites. Discrepancies between investigated proxy records are found when the boundary is located between the two caves. Comparison with the Greenland NAO record shows that a westerly shifted boundary is often associated with a strong SH and a negative NAO. An easterly shift, in contrast, is found to be linked with weak a SH and a positive NAO.
D. Wendi, N. Marwan, B. Merz:
The importance of hydrological signature and its recurring dynamics,
AGU Fall Meeting,
New Orleans (USA),
December 1–17, 2017,
Poster.
» Abstract
Temporal changes in hydrology are known to be challenging to detect and attribute due to multiple drivers that include complex processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defense, river training, and land use change, could impact variably on space-time scales and influence or mask each other. Besides, data depicting these drivers are often not available.
One conventional approach of analyzing the change is based on discrete points of magnitude (e.g. the frequency of recurring extreme discharge) and often linearly quantified and hence do not reveal the potential change in the hydrological process. Moreover, discharge series are often subject to measurement errors, such as rating curve error especially in the case of flood peaks where observation are derived through extrapolation.
In this study, the system dynamics inferred from the hydrological signature (i.e. the shape of hydrograph) is being emphasized. One example is to see if certain flood dynamics (instead of flood peak) in the recent years, had also occurred in the past (or rather extraordinary), and if so what is its recurring rate and if there had been a shift in its occurrence in time or seasonality (e.g. earlier snow melt dominant flood). The utilization of hydrological signature here is extended beyond those of classical hydrology such as base flow index, recession and rising limb slope, and time to peak. It is in fact all these characteristics combined i.e. from the start until the end of the hydrograph. Recurrence plot is used as a method to quantify and visualize the recurring hydrological signature through its phase space trajectories, and usually in the order of dimension above 2. Such phase space trajectories are constructed by embedding the time series into a series of variables (i.e. number of dimension) corresponding to the time delay. Since the method is rather novel in hydrological community, the study presents an overview and a guideline to the method with an application example on analyzing the change of hydrological signature and discussion of its benefits and flaws.
N. Marwan:
Recurrence Plots for Data Analysis,
QUEST Workshop on palaeoclimate time series analysis and statistics,
Potsdam (Germany),
November 3, 2017,
Lecture and workshop.
N. Marwan:
Transparent and efficient data storage,
QUEST Workshop on palaeoclimate time series analysis and statistics,
Potsdam (Germany),
November 3, 2017,
Lecture.
N. Marwan:
Höhlen als wissenschaftliche Archive,
20th Anniversary of Speleo Club Berlin,
Kienitz (Germany),
September 23, 2017,
Talk.
N. Marwan:
What can you see? Perception problems of recurrence plots,
7th International Symposium on Recurrence Plots,
São Paulo (Brazil),
August 23-25, 2017,
» Talk (PDF, 3.44M)
.
» Abstract
Recurrence plots exhibit features and patterns which are characteristic for typical dynamics. How difficult does it be to visually recognize the dynamics from the recurrence plot? Does everybody see the same or judges the different patterns with similar importance? In this (interactive) talk we will figure out the subjective nature of visual inspection and discuss the difficulties. It finally underlines the importance of applying objective quantifiers such as recurrence quantification analysis.
D. Eroglu, N. Marwan:
Multiplex Recurrence Networks,
7th International Symposium on Recurrence Plots,
São Paulo (Brazil),
August 23-25, 2017,
Poster.
» Abstract
The complex nature of a variety of phenomena in physical, biological, or earth sciences is driven by a large number of degrees of freedom which are strongly interconnected. Although the evolution of such systems is described by multivariate time series (MTS), so far research mostly focuses on analyzing these components one by one.
Recurrence based analyses are powerful methods to understand the underlying dynamics of a dynamical system and have been used for many successful applications including examples from earth science, economics, or chemical reactions. The backbone of these techniques is creating the phase space of the system. However, increasing the dimension of a system requires increasing the length of the time series in order get significant and reliable results. This requirement is one of the challenges in many disciplines, in particular in palaeoclimate, thus, it is not easy to create a phase space from measured MTS due to the limited number of available obervations (samples). To overcome this problem, we suggest to create recurrence networks from each component of the system and combine them into a multiplex network structure, the it multiplex recurrence network (MRN). We test the MRN by using prototypical mathematical models and demonstrate its use by studying high-dimensional palaeoclimate dynamics derived from pollen data from the Bear Lake (Utah, US). By using the MRN, we can distinguish typical climate transition events, e.g., such between Marine Isotope Stages.
H. Kraemer, N. Marwan, M. H. Trauth:
Classifying abrupt transitions in IPCC climate models and paleoclimate proxy data using recurrence quantification analysis,
7th International Symposium on Recurrence Plots,
São Paulo (Brazil),
August 23-25, 2017,
Talk.
» Abstract
In many data driven disciplines, categorising abrupt transitions / regime changes are of high interest. The different aspects of recurrence can help to identify and characterize subtle changes in systems dynamics. Besides the identification of transitions, recurrence methods can help to provide a better understanding of the underlying process of these transitions by statistically describing the dynamical characteristics, e.g. the predictability, determinism and complexity of the dynamical system. For example, the characteristic block structures in the recurrence plot can be used to identify different types of intermittency. In general, changes between different dynamics are visually well expressed in recurrence plots. The introduction of selected recurrence quantifiers (such as recurrence rate, determinism, or laminarity) together with a running window approach has paved the way for a quantitative recurrence analysis of transitions and therefore allow a classification of different transition types.
In this work first results of such recurrence based classification is shown. We demonstrate it by analysing prototypical models of transitions as well as on real world data related to palaeoclimate. The prototypical models are selected from a catalogue of transition types which have been used and discussed in models presented in the reports of the Intergovernmental Panel on Climate Change (IPCC)[1]. In the palaeoclimate example we consider two Potassium time series of two drilling cores from the Chew Bahir Bassin, which is part of the Hominin Sites and Paleolakes Drilling Project (HSPDP).
D. Wendi, N. Marwan, B. Merz, J. Kurths:
Change in flood hazard dynamics from recurrence perspective,
7th International Symposium on Recurrence Plots,
São Paulo (Brazil),
August 23-25, 2017,
Talk.
» Abstract
Temporal changes in flood hazard systems are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. Often such analysis of change is quantified from single points perspective (i.e. extreme values) that may subject to high errors and uncertainties. In contrast, the hydrological signature derived from the time series could provide a better picture of a process characteristic resulting from the drivers and hence a step closer to understanding the change of process and is less prone to artifacts caused by single point analysis.
This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazards in Germany through its hydrological signature. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.
A. M. T. Ramos, A. Builes-Jaramillo, G. Poveda, B. Goswami, E. E. N. Macau, J. Kurths, N. Marwan:
Causality detection based on recurrence plot,
7th International Symposium on Recurrence Plots,
São Paulo (Brazil),
August 23-25, 2017,
Talk.
» Abstract
We will present the Recurrence Measure of Conditional Dependence (RMCD), a recent data-driven causality inference method using the framework of recurrence plots. The RMCD incorporates the recurrence behavior into the transfer entropy theory. We will discuss how this methodology can reveal the lagged coupling of some paradigmatic models and how it reveals causal relations of climate systems. For instance, RMCD detects the influence of the Pacific Ocean temperatures on the South West Amazon rainfall during the 2010 droughts, as well as its influence absence during 2005.
D. Eroglu, N. Marwan:
Multiplex Recurrence Networks,
EGU General Assembly,
Vienna (Austria),
April 23-28, 2017,
» Poster (PDF, 5.64M)
.
» Abstract
The complex nature of a variety of phenomena in physical, biological, or earth sciences is driven by a large number of degrees of freedom which are strongly interconnected. Although the evolution of such systems is described by multivariate time series (MTS), so far research mostly focuses on analyzing these components one by one.
Recurrence based analyses are powerful methods to understand the underlying dynamics of a dynamical system and have been used for many successful applications including examples from earth science, economics, or chemical reactions. The backbone of these techniques is creating the phase space of the system. However, increasing the dimension of a system requires increasing the length of the time series in order get significant and reliable results. This requirement is one of the challenges in many disciplines, in particular in palaeoclimate, thus, it is not easy to create a phase space from measured MTS due to the limited number of available obervations (samples). To overcome this problem, we suggest to create recurrence networks from each component of the system and combine them into a multiplex network structure, the multiplex recurrence network (MRN). We test the MRN by using prototypical mathematical models and demonstrate its use by studying high-dimensional palaeoclimate dynamics derived from pollen data from the Bear Lake (Utah, US). By using the MRN, we can distinguish typical climate transition events, e.g., such between Marine Isotope Stages.
F. Brenner, N. Marwan, P. Hoffmann:
Modelling fast spreading patterns of airborne infectious diseases using complex networks,
EGU General Assembly,
Vienna (Austria),
April 23-28, 2017,
Talk.
» Abstract
The pandemics of SARS (2002/2003) and H1N1 (2009) have impressively shown the potential of epidemic outbreaks of infectious diseases in a world that is strongly connected. Global air travelling established an easy and fast opportunity for pathogens to migrate globally in only a few days. This made epidemiological prediction harder. By understanding this complex development and its link to climate change we can suggest actions to control a part of global human health affairs.
In this study we combine the following data components to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human:
- GlobalAirTrafficNetwork(fromopenflights.org) with information on airports, airportlocation, directflight connection, airplane type
- Global population dataset (from SEDAC, NASA)
- Susceptible-Infected-Recovered (SIR) compartmental model to simulate disease spreading in the vicinity of airports. A modified Susceptible-Exposed-Infected-Recovered (SEIR) model to analyze the impact of the incubation period.
- WATCH-Forcing-Data-ERA-Interim(WFDEI) climatedata: temperature, specific humidity, surface air pressure, and water vapor pressure
These elements are implemented into a complex network. Nodes inside the network represent airports. Each single node is equipped with its own SIR/SEIR compartmental model with node specific attributes. Edges between those nodes represent direct flight connections that allow infected individuals to move between linked nodes. Therefore the interaction of the set of unique SIR models creates the model dynamics we will analyze.
To better figure out the influence on climate change on disease spreading patterns, we focus on Influenza-like-Illnesses (ILI). The transmission rate of ILI has a dependency on climate parameters like humidity and temperature. Even small changes of environmental variables can trigger significant differences in the global outbreak behavior. Apart from the direct effect of climate change on the transmission of airborne diseases, there are indirect ramifications that alter spreading patterns. An example is seasonal human mobility behavior which will change with varied climate conditions. The direct and indirect effects of climate change on disease spreading patterns will be discussed in this study.
A. Agarwal, N. Marwan, M. Rathinasamy, U. Oeztuerk, B. Merz, J. Kurths:
Multiscale complex network analysis: An approach to study spatiotemporal rainfall pattern in south Germany,
EGU General Assembly,
Vienna (Austria),
April 23-28, 2017,
Poster.
» Abstract
Understanding of the climate sytems has been of tremendous importance to different branches such as agriculture, flood, drought and water resources management etc. In this regard, complex networks analysis and time series analysis attracted considerable attention, owing to their potential role in understanding the climate system through characteristic properties. One of the basic requirements in studying climate network dynamics is to identify connections in space or time or space-time, depending upon the purpose. Although a wide variety of approaches have been developed and applied to identify and analyse spatio-temporal relationships by climate networks, there is still further need for improvements in particular when considering precipitation time series or interactions on different scales. In this regard, recent developments in the area of network theory, especially complex networks, offer new avenues, both for their generality about systems and for their holistic perspective about spatio-temporal relationships.
The present study has made an attempt to apply the ideas developed in the field of complex networks to examine connections in regional climate networks with particular focus on multiscale spatiotemporal connections. This paper proposes a novel multiscale understanding of regional climate networks using wavelets. The proposed approach is applied to daily precipitation records observed at 543 selected stations from south Germany for a period of 110 years (1901-2010). Further, multiscale community mining is performed on the same study region to shed more light on the underlying processes at different time scales.
Various network measure and tools so far employed provide micro-level (individual station) and macro-level (community structure) information of the network. It is interesting to investigate how the result of this study can be useful for future climate predictions and for evaluating climate models on their implementation regarding heavy precipitation.
U. Ozturk, N. Marwan, J. Kurths:
Identifying typhoon tracks based on event synchronization derived spatially embedded climate networks,
EGU General Assembly,
Vienna (Austria),
April 23-28, 2017,
Poster.
» Abstract
Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons.
In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms’ and typhoons’ individual behaviors.
U. Ozturk, N. Marwan, O. Korup, J. Jensen:
Completing the record of 20th century sea level rise in the Eastern Mediterranean,
EGU General Assembly,
Vienna (Austria),
April 23-28, 2017,
Poster.
» Abstract
Quantitative studies of sea-level rise in the Mediterranean are becoming more and more accurate thanks to detailed satellite monitoring campaigns. However, these studies cover several years to a couple of decades at best, while longer-term sea-level records for the area are rare. Long-term sea-level measurements are essential in order to derive accurate trends free of conspicuous oscillations in shorter records. We use an approach from data archaeology to meet this shortcoming, and to offer a more complete record of sea-level rise cross-checked among several tide gauges. Specifically, we investigate monthly mean sea-level data of the Antalya-I (1935-1977) tide gauge provided by the Turkish National Mapping Agency. We checked how accurately and reliably these monthly records were digitized, quality-controlled, and tied to a common datum. We then merged these data with the more recent records of the nearby Antalya-II (1985-2010) tide gauge, obtaining a composite time series of monthly and annual mean sea levels spanning approximately 75 years. We thus offer the hitherto longest record in the Eastern Mediterranean Basin as an essential tool for studying the region’s sea-level trends. We estimate a relative mean sea-level rise of 2.46 ± 1.65 mm/yr between 1935 and 2010, with a sub-decadal variability (σresiduals = 49.47 mm) that is higher than at nearby tide gauges (e.g. Thessaloniki, Greece, σresiduals = 28.71 mm). Our study highlights the value of data archaeology for recovering and integrating early tide-gauge data for long-term sea-level an
