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Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting

Alexandra Diehl, Leandro Pelorosso, Claudio Delrieux, Celeste Saulo, Juan Ruiz, M. Eduard Gröller, Stefan Bruckner

JOURNAL ARTICLE: Computer Graphics Forum, vol. 34, no. 3, pp. 381–390, 2015. DOI: 10.1111/cgf.12650

Abstract

Weather 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.

Published

Computer Graphics Forum

  • Volume: 34
  • Number: 3
  • Pages: 381–390
  • Event: EuroVis 2015
  • Location: Cagliari, Italy
  • Date: May 2015
  • DOI: 10.1111/cgf.12650

Documents and Links

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BibTeX

@ARTICLE{Diehl-2015-VAS,
  author = {Alexandra Diehl and Leandro Pelorosso and Claudio Delrieux and Celeste
	Saulo and Juan Ruiz and M. Eduard Gr{\"o}ller and Stefan Bruckner},
  title = {Visual Analysis of Spatio-Temporal Data: Applications in Weather
	Forecasting},
  journal = {Computer Graphics Forum},
  year = {2015},
  volume = {34},
  pages = {381--390},
  number = {3},
  month = may,
  abstract = {Weather 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.},
  doi = {10.1111/cgf.12650},
  event = {EuroVis 2015},
  keywords = {weather forecasting, visual analysis, spatiotemporal data},
  location = {Cagliari, Italy},
  owner = {bruckner},
  timestamp = {2015.06.08}
}






 Last Modified: Stefan Bruckner, 2017-06-14