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

A. Diehl, L. Pelorosso, C. Delrieux, C. Saulo, J. Ruiz, M. E. Gröller, and S. Bruckner

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.

A. Diehl, L. Pelorosso, C. Delrieux, C. Saulo, J. Ruiz, M. E. Gröller, and S. Bruckner, "Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting," Computer Graphics Forum, vol. 34, iss. 3, p. 381–390, 2015. doi:10.1111/cgf.12650
[BibTeX]

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.
@ARTICLE {Diehl-2015-VAS,
author = "Alexandra Diehl and Leandro Pelorosso and Claudio Delrieux and Celeste Saulo and Juan Ruiz and Meister 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",
number = "3",
pages = "381--390",
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.",
pdf = "pdfs/Diehl-2015-VAS.pdf",
images = "images/Diehl-2015-VAS.jpg",
thumbnails = "images/Diehl-2015-VAS.png",
youtube = "https://www.youtube.com/watch?v=hhQwsuXpHo8",
doi = "10.1111/cgf.12650",
event = "EuroVis 2015",
keywords = "weather forecasting, visual analysis, spatiotemporal data",
location = "Cagliari, Italy",
owner = "bruckner",
timestamp = "2015.06.08"
}
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