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Exploration of Climate Data Using Interactive Visualization

Florian Ladstädter, Andrea K. Steiner, Bettina C. Lackner, Barbara Pirscher, Gottfried Kirchengast, Johannes Kehrer, Helwig Hauser, Philipp Muigg, Helmut Doleisch

ARTICLE, Journal of Atmospheric and Oceanic Technology, April, 2010

Abstract

In atmospheric and climate research, the increasing amount of data available from climate models and observations provides new challenges for data analysis. We present interactive visual exploration as an innovative approach to handle large datasets. Visual exploration does not require any previous knowledge about the data as is usually the case with classical statistics. It facilitates iterative and interactive browsing of the parameter space in order to quickly understand the data characteristics, to identify deficiencies, to easily focus on interesting features, and to come up with new hypotheses about the data. These properties extend the common statistical treatment of data, and provide a fundamentally different approach. We demonstrate the potential of this technology by exploring atmospheric climate data from different sources including reanalysis datasets, climate models, and radio occultation satellite data. Results are compared to those from classical statistics revealing the complementary advantages of visual exploration. Combining both, the analytical precision of classical statistics and the holistic power of interactive visual exploration, the usual work flow of studying climate data can be enhanced.

Published

Journal of Atmospheric and Oceanic Technology

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BibTeX

@article{ladstaedter10explorationClimateData,
  title = {Exploration of Climate Data Using Interactive Visualization},
  author = {Florian Ladst{\"a}dter and Andrea K. Steiner and Bettina C. Lackner and 
  Barbara Pirscher and Gottfried Kirchengast and Johannes Kehrer and Helwig Hauser and 
  Philipp Muigg and Helmut Doleisch},
  journal = {Journal of Atmospheric and Oceanic Technology},
  volume = {27},
  number = {4},
  pages =  {667--679},
  month = {April},
  year = {2010},
  abstract = {In atmospheric and climate research, the increasing amount of 
data available from climate models and observations provides new challenges for 
data analysis. We present interactive visual exploration as an innovative approach 
to handle large datasets. Visual exploration does not require any previous knowledge 
about the data as is usually the case with classical statistics. It facilitates
iterative and interactive browsing of the parameter space in order to quickly 
understand the data characteristics, to identify deficiencies, to easily focus on 
interesting features, and to come up with new hypotheses about the data. These 
properties extend the common statistical treatment of data, and provide a 
fundamentally different approach. We demonstrate the potential of this 
technology by exploring atmospheric climate data from different sources 
including reanalysis datasets, climate models, and radio occultation satellite 
data. Results are compared to those from classical statistics revealing the 
complementary advantages of visual exploration. Combining both, the analytical 
precision of classical statistics and the holistic power of interactive visual 
exploration, the usual work flow of studying climate data can be enhanced.},


  URL = {http://dx.doi.org/10.1175/2009JTECHA1374.1}
}






 Last Modified: Jean-Paul Balabanian, 2014-04-09