Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting
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...
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paper:paper_01677055_v34_n3_p381_Diehl2023-06-08T15:16:48Z Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting Ruiz, Juan Jose I.3.3 [Computer Graphics]: Picture/Image Generation - Viewing algorithms I.3.6 [Computer Graphics]: Methodology and Techniques Interaction techniques I.3.8 [Computer Graphics]: Applications - Weather Forecast Analysis Atmospheric movements Balloons Computer graphics Data visualization Forecasting Visualization Advanced visualizations Forecast analysis I.3.6 [Computer Graphics]: Methodology and Techniques - Interaction techniques Interactive visualizations Numerical weather prediction models Spatiotemporal patterns Viewing algorithms Weather forecast models Weather forecasting 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. © 2015 The Author(s) Computer Graphics Forum © 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. Fil:Ruiz, J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2015 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01677055_v34_n3_p381_Diehl http://hdl.handle.net/20.500.12110/paper_01677055_v34_n3_p381_Diehl |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
I.3.3 [Computer Graphics]: Picture/Image Generation - Viewing algorithms I.3.6 [Computer Graphics]: Methodology and Techniques Interaction techniques I.3.8 [Computer Graphics]: Applications - Weather Forecast Analysis Atmospheric movements Balloons Computer graphics Data visualization Forecasting Visualization Advanced visualizations Forecast analysis I.3.6 [Computer Graphics]: Methodology and Techniques - Interaction techniques Interactive visualizations Numerical weather prediction models Spatiotemporal patterns Viewing algorithms Weather forecast models Weather forecasting |
| spellingShingle |
I.3.3 [Computer Graphics]: Picture/Image Generation - Viewing algorithms I.3.6 [Computer Graphics]: Methodology and Techniques Interaction techniques I.3.8 [Computer Graphics]: Applications - Weather Forecast Analysis Atmospheric movements Balloons Computer graphics Data visualization Forecasting Visualization Advanced visualizations Forecast analysis I.3.6 [Computer Graphics]: Methodology and Techniques - Interaction techniques Interactive visualizations Numerical weather prediction models Spatiotemporal patterns Viewing algorithms Weather forecast models Weather forecasting Ruiz, Juan Jose Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting |
| topic_facet |
I.3.3 [Computer Graphics]: Picture/Image Generation - Viewing algorithms I.3.6 [Computer Graphics]: Methodology and Techniques Interaction techniques I.3.8 [Computer Graphics]: Applications - Weather Forecast Analysis Atmospheric movements Balloons Computer graphics Data visualization Forecasting Visualization Advanced visualizations Forecast analysis I.3.6 [Computer Graphics]: Methodology and Techniques - Interaction techniques Interactive visualizations Numerical weather prediction models Spatiotemporal patterns Viewing algorithms Weather forecast models Weather forecasting |
| description |
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. © 2015 The Author(s) Computer Graphics Forum © 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. |
| author |
Ruiz, Juan Jose |
| author_facet |
Ruiz, Juan Jose |
| author_sort |
Ruiz, Juan Jose |
| title |
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting |
| title_short |
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting |
| title_full |
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting |
| title_fullStr |
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting |
| title_full_unstemmed |
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting |
| title_sort |
visual analysis of spatio-temporal data: applications in weather forecasting |
| publishDate |
2015 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01677055_v34_n3_p381_Diehl http://hdl.handle.net/20.500.12110/paper_01677055_v34_n3_p381_Diehl |
| work_keys_str_mv |
AT ruizjuanjose visualanalysisofspatiotemporaldataapplicationsinweatherforecasting |
| _version_ |
1768545780250968064 |