Non-linear time series analysis of precipitation events using regional climate networks for Germany

  title={Non-linear time series analysis of precipitation events using regional climate networks for Germany},
  author={Aljoscha Rheinwalt and Niklas Boers and Norbert Marwan and J. Kurths and Peter Hoffmann and Friedrich-Wilhelm Gerstengarbe and Peter Werner},
  journal={Climate Dynamics},
AbstractSynchronous occurrences of heavy rainfall events and the study of their relation in time and space are of large socio-economical relevance, for instance for the agricultural and insurance sectors, but also for the general well-being of the population. In this study, the spatial synchronization structure is analyzed as a regional climate network constructed from precipitation event series. The similarity between event series is determined by the number of synchronous occurrences. We… Expand
Identification of droughts and heatwaves in Germany with regional climate networks
Abstract. Regional climate networks (RCNs) are used to identify heatwaves and droughts in Germany and two subregions for the summer half-years and summer seasons of the period 1951 to 2019. RCNsExpand
Temporal evolution of the spatial covariability of rainfall in South America
The climate of South America exhibits pronounced differences between rainy and dry seasons, associated with specific synoptic features such as the establishment of the South Atlantic convergenceExpand
Unfolding Community Structure in Rainfall Network of Germany Using Complex Network-Based Approach
The rainfall data, when represented as a complex network using event synchronization, exhibits small-world and scale-free network topology which are a class of stable and efficient networks common in nature. Expand
Complex networks reveal global pattern of extreme-rainfall teleconnections
Analysis of the atmospheric conditions that lead to these teleconnections confirms Rossby waves as the physical mechanism underlying these global teleconnection patterns and emphasizes their crucial role in dynamical tropical–extratropical couplings. Expand
Event coincidence analysis for quantifying statistical interrelationships between event time series
The method of event coincidence analysis is described to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series and yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Expand
Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA
Abstract The quantification of spatio-temporal hydroclimatic extreme events is a key variable in water resources planning, disaster mitigation, and preparing climate resilient society. However,Expand
Unraveling the spatial diversity of Indian precipitation teleconnections via nonlinear multi-scale approach
Abstract. A better understanding of precipitation dynamics in the Indian subcontinent is required since India’s society depends heavily on reliable monsoon forecasts. We introduce a nonlinear,Expand
Interactive comment on “ Multi-scale event synchronization analysis for unraveling climate processes : A wavelet-based approach ”
The temporal dynamics of climate processes are spread across different time scales and, as such, the study of these processes only at one selected time scale might not reveal the complete mechanismsExpand
Spatiotemporal characteristics and synchronization of extreme rainfall in South America with focus on the Andes Mountain range
The South American Andes are frequently exposed to intense rainfall events with varying moisture sources and precipitation-forming processes. In this study, we assess the spatiotemporalExpand
Multi-scale event synchronization analysis for unravelling climate processes
The wavelet-based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization and is tested on synthetic and real-world time series in order to check its replicability and applicability. Expand


Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks
We present a detailed analysis of summer monsoon rainfall over the Indian peninsular using nonlinear spatial correlations. This analysis is carried out employing the tools of complex networks and aExpand
Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System
[1] We investigate the spatial characteristics of extreme rainfall synchronicity of the South American Monsoon System (SAMS) by means of Complex Networks (CN). By introducing a new combination of CNExpand
Prediction of extreme floods in the eastern Central Andes based on a complex networks approach.
This study reveals a linkage between polar and tropical regimes as the responsible mechanism: the interplay of northward migrating frontal systems and a low-level wind channel from the western Amazon to the subtropics. Expand
A new type of climate network based on probabilistic graphical models: Results of boreal winter versus summer
[1] In this paper we introduce a new type of climate network based on temporal probabilistic graphical models. This new method is able to distinguish between direct and indirectconnections and thusExpand
Stability of Climate Networks with Time
There is a gradual monotonic modification of the network pattern as a function of altitude difference and it is found that around the equator, the contribution of the physical coupling is significantly less pronounced compared to off–equatorial regimes. Expand
The backbone of the climate network
We propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system, relying on the nonlinear mutual information of time series analysis andExpand
The South American rainfall dipole: A complex network analysis of extreme events
Intraseasonal rainfall variability of the South American monsoon system is characterized by a pronounced dipole between southeastern South America and southeastern Brazil. Here we analyze theExpand
An exploration of climate data using complex networks
It is shown that communities have a climatological interpretation and that disturbances in structure can be an indicator of climate events (or lack thereof) and how this model can be applied for the discovery of more complex concepts such as unknown teleconnections or the development of multivariate climate indices and predictive insights. Expand
Multivariate and multiscale dependence in the global climate system revealed through complex networks
A systematic characterization of multivariate dependence at multiple spatio-temporal scales is critical to understanding climate system dynamics and improving predictive ability from models and data.Expand
Boundary Effects in Network Measures of Spatially Embedded Networks
The straightforward approach here is to use surrogate networks that provide estimates of boundary effects in graph statistics by using spatially embedded random networks as surrogates that have approximately the same link probability as a function of spatial link lengths. Expand