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

@article{Rheinwalt2016NonlinearTS,
  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},
  year={2016},
  volume={46},
  pages={1065-1074}
}
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… 

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References

SHOWING 1-10 OF 30 REFERENCES

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 a

Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System

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 CN

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.

A new type of climate network based on probabilistic graphical models: Results of boreal winter versus summer

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 thus can

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 and

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.

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 the

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.

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.

Are North Atlantic multidecadal SST anomalies westward propagating?

The westward propagation of sea surface temperature (SST) anomalies is one of the main characteristics of one of the theories of the Atlantic Multidecadal Oscillation. Here we use techniques from