 |
| Titel |
Review: visual analytics of climate networks |
| VerfasserIn |
T. Nocke, S. Buschmann, J. F. Donges, N. Marwan, H.-J. Schulz, C. Tominski |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
2198-5634
|
| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 2, no. 2 ; Nr. 2, no. 2 (2015-04-30), S.709-780 |
| Datensatznummer |
250115161
|
| Publikation (Nr.) |
 copernicus.org/npgd-2-709-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| Network analysis has become an important approach in studying
complex spatiotemporal behaviour within geophysical observation and
simulation data. This new field produces increasing amounts of large
geo-referenced networks to be analysed. Particular focus lies
currently on the network analysis of the complex statistical
interrelationship structure within climatological fields. The
standard procedure for such network analyses is the extraction of
network measures in combination with static standard visualisation
methods. Existing interactive visualisation methods and tools for
geo-referenced network exploration are often either not known to the
analyst or their potential is not fully exploited. To fill this gap,
we illustrate how interactive visual analytics methods in
combination with geovisualisation can be tailored for visual climate
network investigation. Therefore, the paper provides a problem
analysis, relating the multiple visualisation challenges with
a survey undertaken with network analysts from the research fields
of climate and complex systems science. Then, as an overview for the
interested practitioner, we review the state-of-the-art in climate
network visualisation and provide an overview of existing tools. As
a further contribution, we introduce the visual network analytics
tools CGV and GTX, providing tailored solutions for climate network
analysis, including alternative geographic projections, edge
bundling, and 3-D network support. Using these tools, the paper
illustrates the application potentials of visual analytics for
climate networks based on several use cases including examples from
global, regional, and multi-layered climate networks. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|