World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

Review: Visual Analytics of Climate Networks : Volume 2, Issue 2 (30/04/2015)

By Nocke, T.

Click here to view

Book Id: WPLBN0004020149
Format Type: PDF Article :
File Size: Pages 72
Reproduction Date: 2015

Title: Review: Visual Analytics of Climate Networks : Volume 2, Issue 2 (30/04/2015)  
Author: Nocke, T.
Volume: Vol. 2, Issue 2
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Buschmann, S., Marwan, N., Donges, J. F., Tominski, C., Schulz, H., & Nocke, T. (2015). Review: Visual Analytics of Climate Networks : Volume 2, Issue 2 (30/04/2015). Retrieved from http://hawaiilibrary.net/


Description
Description: Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany. 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.

Summary
Review: visual analytics of climate networks

Excerpt
Abello, J. and Pogel, A.: Graph partitions and concept lattices, in: Discrete Methods in Epidemiology, edited by: J. Abello and G. Cormode, AMS-DIMACS Series, American Mathematical Society, Providence, Rhode Island, USA, 70, 115–138, 2006.; Abello, J., Hadlak, S., Schumann, H., and Schulz, H.-J.: A modular degree-of-interest specification for the visual analysis of large dynamic networks, IEEE T. Vis. Comput. Gr., 20, 337–350, 2014.; Adar, E.: GUESS: a Language and Interface for Graph Exploration, in: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI), ACM, 24–27 April 2006, Montreal, Quebec, Canada, 791–800, doi:10.1145/1124772.1124889, 2006.; Aigner, W., Miksch, S., Schumann, H., and Tominski, C.: Visualization of Time-Oriented Data, Springer, London Dordrecht Heidelberg New York, doi:10.1007/978-0-85729-079-3, 2011.; Albert, R. and Barabasi, A. L.: Statistical Mechanics of Complex Networks, Rev. Mod. Phys., 74, 47–97, 2002.; Alper, B., Sümengen, S., and Balcisoy, S.: Dynamic visualization of geographic networks using surface deformations with constraints, in: Proc. of the Computer Graphics International Conference (CGI), 30 May–2 June 2007, Petropolis, Brazil, available at: http://inf.ufrgs.br/cgi2007/cd_cgi/papers.html 2007.; Andrienko, G., Andrienko, N., Bak, P., Keim, D., and Wrobel, S.: Visual Analytics of Movement, Springer, Heidelberg New York Dordrecht London, doi:10.1007/978-3-642-37583-5, 2013.; Bach, B., Pietriga, E., and Fekete, J.-D.: GraphDiaries: animated transitions and temporal navigation for dynamic networks, IEEE T. Vis. Comput. Gr., 20, 740–754, 2013.; Bastian, M., Heymann, S., and Jacomy, M.: Gephi: an Open Source Software for Exploring and Manipulating Networks, in: International AAAI Conference on Weblogs and Social Media, 17–20 May 2009, San Jose, California, USA, abstract no. 154, 2009.; Berezin, Y., Gozolchiani, A., Guez, O., and Havlin, S.: Stability of climate networks with time, Scientific Reports, 2, 666, doi:10.1038/srep00666, 2012.; Bierkandt, R., Wenz, L., Willner, S. N., and Levermann, A.: Acclimate – a model for economic damage propagation. Part 1: basic formulation of damage transfer within a global supply network and damage conserving dynamics, Environ. Syst. Decis., 34, 507–524, 2014.; de Nooy, W., Mrvar, A., and Batagelj, V.: Exploratory Social Network Analysis with Pajek, Cambridge University Press, Cambridge, 2005.; Blaas, J., Botha, C., Peters, B., Vos, F., and Post, F.: Fast and reproducible fiber bundle selection in DTI visualization, in: Visualization, 23–28 October 2005, Minneapolis, Minnesota, USAVIS 05, IEEE, 59–64, 2005.; Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., and Hwang, D. U.: Complex networks: structure and dynamics, Phys. Rep., 424, 175–308, 2006.; Boers, N., Bookhagen, B., Marwan, N., Kurths, J., and Marengo, J.: Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System, Geophys. Res. Lett., 40, 4386–4392, 2013.; Boers, N., Bookhagen, B., Barbosa, H. M. J., Marwan, N., Kurths, J., and Marengo, J. A.: Prediction of extreme floods in the eastern Central Andes based on a complex networks approach, Nature Comm., 5, 5199, doi:10.1038/ncomms6199, 2014.; Böttger, J., Schafer, A., Lohmann, G., Villringer, A., and Margulies, D. S.: Three-dimensional mean-shift edge bundling for the visualization of functional connectivity in the brain, IEEE T. Vis. Comput. Gr., 20, 471–480, 2014.; Brambilla, A., Carnecky, R., Peikert, R., Viola, I., and Hauser, H.: Illustrative flow visualization: state of the art, trend

 

Click To View

Additional Books


  • Role of the Hydrological Cycle in Regula... (by )
  • Evolutionary Modeling-based Approach for... (by )
  • The Rossby Wave Extra Invariant in the D... (by )
  • Current Challenges for Pre-earthquake El... (by )
  • Wave Interactions in a Shallow-water Mod... (by )
  • Extreme Events and Long-range Correlatio... (by )
  • Dynamical Segmentation and Rupture Patte... (by )
  • The Impact of Nonlinearity in Lagrangian... (by )
  • Universal Dependences Between Turbulent ... (by )
  • Organisation of Joints and Faults from 1... (by )
  • Prediction of the Stochastic Behaviour o... (by )
  • Null Modes Effect in Rossby Wave Model :... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from Hawaii eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.