Complex network approaches to analyzing and modeling nonlinear systems in geosciences
Complex network approaches to analyzing and modeling nonlinear systems in geosciences
Editor(s): R. Donner, J. Donges, J. Davidsen, A. Loew, M. Small, and J. Kurths

Nowadays, concepts and techniques from network theory are frequently used to study structures and dynamics of complex systems in various scientific disciplines. Meanwhile, successful applications also cover different fields of geosciences, from hydrology and geomorphology (e.g., scaling of and sediment transport along river networks, spatial structure and interaction of sediment pathways in cascading systems) over climatology (spatiotemporal organization of the climate system, climate model intercomparison on the dynamics level) to seismology (modeling of seismicity in terms of earthquake networks, volcanic eruptions) and natural hazard research (disaster spreading, causality networks).

As a particular example, climate knowledge discovery is an emerging community effort to find new tools for the analysis of the vast quantities of climate data being generated by observations and model simulations. Successful applications of concepts and algorithms from complex network theory to climate data sets have already provided first insights into the potentials of such an approach. There is reason to assume that tools employing a combination of high-performance analytics and of algorithms motivated by network science, nonlinear dynamics and statistics, as well as of methods from data mining and machine learning, could provide new insights into different features of the geophysical systems. Similar efforts are currently undertaken in other geoscientific disciplines as well. Among others, complex network approaches to seismicity allow new deep insights into the spatiotemporal organization of earthquake activity. Different types of time-series networks are increasingly used for studying dynamical scaling properties and non-stationarities associated with the emergence of critical phenomena and extreme events in different components of the Earth system.

This special issue collects contributions from researchers utilizing complex network approaches for time series, spatial or spatiotemporal data analysis, data mining, and conceptual modeling in different geoscientific disciplines. Specifically, it provides a state-of-the-art overview on network-theoretic approaches in various fields of Earth and environmental sciences, which shall stimulate further research as well as transdisciplinary applications based on this fascinating and versatile paradigm of nonlinear sciences.

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23 Sep 2015
Review: visual analytics of climate networks
T. Nocke, S. Buschmann, J. F. Donges, N. Marwan, H.-J. Schulz, and C. Tominski
Nonlin. Processes Geophys., 22, 545–570, https://doi.org/10.5194/npg-22-545-2015,https://doi.org/10.5194/npg-22-545-2015, 2015
Short summary
30 Jul 2015
Global terrestrial water storage connectivity revealed using complex climate network analyses
A. Y. Sun, J. Chen, and J. Donges
Nonlin. Processes Geophys., 22, 433–446, https://doi.org/10.5194/npg-22-433-2015,https://doi.org/10.5194/npg-22-433-2015, 2015
Short summary
27 Nov 2014
Correlations between climate network and relief data
T. K. D. Peron, C. H. Comin, D. R. Amancio, L. da F. Costa, F. A. Rodrigues, and J. Kurths
Nonlin. Processes Geophys., 21, 1127–1132, https://doi.org/10.5194/npg-21-1127-2014,https://doi.org/10.5194/npg-21-1127-2014, 2014
Short summary
24 Nov 2014
Long-term changes in the north–south asymmetry of solar activity: a nonlinear dynamics characterization using visibility graphs
Y. Zou, R. V. Donner, N. Marwan, M. Small, and J. Kurths
Nonlin. Processes Geophys., 21, 1113–1126, https://doi.org/10.5194/npg-21-1113-2014,https://doi.org/10.5194/npg-21-1113-2014, 2014
Short summary
11 Nov 2014
Finding recurrence networks' threshold adaptively for a specific time series
D. Eroglu, N. Marwan, S. Prasad, and J. Kurths
Nonlin. Processes Geophys., 21, 1085–1092, https://doi.org/10.5194/npg-21-1085-2014,https://doi.org/10.5194/npg-21-1085-2014, 2014
30 Sep 2014
Horton laws for hydraulic–geometric variables and their scaling exponents in self-similar Tokunaga river networks
V. K. Gupta and O. J. Mesa
Nonlin. Processes Geophys., 21, 1007–1025, https://doi.org/10.5194/npg-21-1007-2014,https://doi.org/10.5194/npg-21-1007-2014, 2014
11 Sep 2014
Estimating time delays for constructing dynamical networks
E. A. Martin and J. Davidsen
Nonlin. Processes Geophys., 21, 929–937, https://doi.org/10.5194/npg-21-929-2014,https://doi.org/10.5194/npg-21-929-2014, 2014
29 Aug 2014
Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka
V. Stolbova, P. Martin, B. Bookhagen, N. Marwan, and J. Kurths
Nonlin. Processes Geophys., 21, 901–917, https://doi.org/10.5194/npg-21-901-2014,https://doi.org/10.5194/npg-21-901-2014, 2014
08 Aug 2014
Evolution of atmospheric connectivity in the 20th century
F. Arizmendi, A. C. Martí, and M. Barreiro
Nonlin. Processes Geophys., 21, 825–839, https://doi.org/10.5194/npg-21-825-2014,https://doi.org/10.5194/npg-21-825-2014, 2014
24 Jul 2014
Complex networks and waveforms from acoustic emissions in laboratory earthquakes
H. O. Ghaffari, B. D. Thompson, and R. P. Young
Nonlin. Processes Geophys., 21, 763–775, https://doi.org/10.5194/npg-21-763-2014,https://doi.org/10.5194/npg-21-763-2014, 2014
25 Jun 2014
Testing the detectability of spatio–temporal climate transitions from paleoclimate networks with the START model
K. Rehfeld, N. Molkenthin, and J. Kurths
Nonlin. Processes Geophys., 21, 691–703, https://doi.org/10.5194/npg-21-691-2014,https://doi.org/10.5194/npg-21-691-2014, 2014
25 Jun 2014
Characterizing the evolution of climate networks
L. Tupikina, K. Rehfeld, N. Molkenthin, V. Stolbova, N. Marwan, and J. Kurths
Nonlin. Processes Geophys., 21, 705–711, https://doi.org/10.5194/npg-21-705-2014,https://doi.org/10.5194/npg-21-705-2014, 2014
03 Jun 2014
On the influence of spatial sampling on climate networks
N. Molkenthin, K. Rehfeld, V. Stolbova, L. Tupikina, and J. Kurths
Nonlin. Processes Geophys., 21, 651–657, https://doi.org/10.5194/npg-21-651-2014,https://doi.org/10.5194/npg-21-651-2014, 2014
26 May 2014
Distinguishing the effects of internal and forced atmospheric variability in climate networks
J. I. Deza, C. Masoller, and M. Barreiro
Nonlin. Processes Geophys., 21, 617–631, https://doi.org/10.5194/npg-21-617-2014,https://doi.org/10.5194/npg-21-617-2014, 2014
14 Apr 2014
Force chain and contact cycle evolution in a dense granular material under shallow penetration
A. Tordesillas, C. A. H. Steer, and D. M. Walker
Nonlin. Processes Geophys., 21, 505–519, https://doi.org/10.5194/npg-21-505-2014,https://doi.org/10.5194/npg-21-505-2014, 2014
01 Apr 2014
Regional and inter-regional effects in evolving climate networks
J. Hlinka, D. Hartman, N. Jajcay, M. Vejmelka, R. Donner, N. Marwan, J. Kurths, and M. Paluš
Nonlin. Processes Geophys., 21, 451–462, https://doi.org/10.5194/npg-21-451-2014,https://doi.org/10.5194/npg-21-451-2014, 2014
24 Mar 2014
Scale free properties in a network-based integrated approach to earthquake pattern analysis
M. Suteanu
Nonlin. Processes Geophys., 21, 427–438, https://doi.org/10.5194/npg-21-427-2014,https://doi.org/10.5194/npg-21-427-2014, 2014
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