Visual analysis of spatio-temporal data : Applications in weather forecasting

dc.contributor.authorDiehl, Alexandra
dc.contributor.authorPelorosso, Leandro
dc.contributor.authorDelrieux, Claudio
dc.contributor.authorSaulo, Celeste
dc.contributor.authorRuiz, Juan
dc.contributor.authorGröller, M. Eduard
dc.contributor.authorBruckner, Stefan
dc.date.accessioned2019-02-19T11:58:26Z
dc.date.available2019-02-19T11:58:26Z
dc.date.issued2015eng
dc.description.abstractWeather conditions affect multiple aspects of human life such as economy, safety, security, and social activities. For this reason, weather forecast plays a major role in society. Currently weather forecasts are based on Numerical Weather Prediction (NWP) models that generate a representation of the atmospheric flow. Interactive visualization of geo‐spatial data has been widely used in order to facilitate the analysis of NWP models. This paper presents a visualization system for the analysis of spatio‐temporal patterns in short‐term weather forecasts. For this purpose, we provide an interactive visualization interface that guides users from simple visual overviews to more advanced visualization techniques. Our solution presents multiple views that include a timeline with geo‐referenced maps, an integrated webmap view, a forecast operation tool, a curve‐pattern selector, spatial filters, and a linked meteogram. Two key contributions of this work are the timeline with geo‐referenced maps and the curve‐pattern selector. The latter provides novel functionality that allows users to specify and search for meaningful patterns in the data. The visual interface of our solution allows users to detect both possible weather trends and errors in the weather forecast model. We illustrate the usage of our solution with a series of case studies that were designed and validated in collaboration with domain experts.eng
dc.description.versionpublishedeng
dc.identifier.doi10.1111/cgf.12650eng
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/45092
dc.language.isoengeng
dc.subject.ddc004eng
dc.titleVisual analysis of spatio-temporal data : Applications in weather forecastingeng
dc.typeJOURNAL_ARTICLEeng
dspace.entity.typePublication
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@article{Diehl2015Visua-45092,
  year={2015},
  doi={10.1111/cgf.12650},
  title={Visual analysis of spatio-temporal data : Applications in weather forecasting},
  number={3},
  volume={34},
  issn={0167-7055},
  journal={Computer Graphics Forum},
  pages={381--390},
  author={Diehl, Alexandra and Pelorosso, Leandro and Delrieux, Claudio and Saulo, Celeste and Ruiz, Juan and Gröller, M. Eduard and Bruckner, Stefan}
}
kops.citation.iso690DIEHL, Alexandra, Leandro PELOROSSO, Claudio DELRIEUX, Celeste SAULO, Juan RUIZ, M. Eduard GRÖLLER, Stefan BRUCKNER, 2015. Visual analysis of spatio-temporal data : Applications in weather forecasting. In: Computer Graphics Forum. 2015, 34(3), pp. 381-390. ISSN 0167-7055. eISSN 1467-8659. Available under: doi: 10.1111/cgf.12650deu
kops.citation.iso690DIEHL, Alexandra, Leandro PELOROSSO, Claudio DELRIEUX, Celeste SAULO, Juan RUIZ, M. Eduard GRÖLLER, Stefan BRUCKNER, 2015. Visual analysis of spatio-temporal data : Applications in weather forecasting. In: Computer Graphics Forum. 2015, 34(3), pp. 381-390. ISSN 0167-7055. eISSN 1467-8659. Available under: doi: 10.1111/cgf.12650eng
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kops.sourcefieldComputer Graphics Forum. 2015, <b>34</b>(3), pp. 381-390. ISSN 0167-7055. eISSN 1467-8659. Available under: doi: 10.1111/cgf.12650deu
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