Albero: A Visual Analytics Approach for Probabilistic Weather Forecasting

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dc.contributor.authorDiehl, Alexandraen_US
dc.contributor.authorPelorosso, Leandroen_US
dc.contributor.authorDelrieux, Claudioen_US
dc.contributor.authorMatkovic, Kresimiren_US
dc.contributor.authorRuiz, Juanen_US
dc.contributor.authorGröller, M. Eduarden_US
dc.contributor.authorBruckner, Stefanen_US
dc.contributor.editorJernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornungen_US
dc.date.accessioned2017-10-16T05:24:13Z
dc.date.available2017-10-16T05:24:13Z
dc.date.issued2016
dc.description.abstractProbabilistic weather forecasts are amongst the most popular ways to quantify numerical forecast uncertainties. The analog regression method can quantify uncertainties and express them as probabilities. The method comprises the analysis of errors from a large database of past forecasts generated with a specific numerical model and observational data. Current visualization tools based on this method are essentially automated and provide limited analysis capabilities. In this paper, we propose a novel approach that breaks down the automatic process using the experience and knowledge of the users and creates a new interactive visual workflow. Our approach allows forecasters to study probabilistic forecasts, their inner analogs and observations, their associated spatial errors, and additional statistical information by means of coordinated and linked views. We designed the presented solution following a participatory methodology together with domain experts. Several meteorologists with different backgrounds validated the approach. Two case studies illustrate the capabilities of our solution. It successfully facilitates the analysis of uncertainty and systematic model biases for improved decision-making and process-quality measurements.en_US
dc.description.number7
dc.description.sectionheadersVideo and Visualization
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.13279
dc.identifier.issn1467-8659
dc.identifier.pages135-144
dc.identifier.urihttps://doi.org/10.1111/cgf.13279
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13279
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]
dc.subjectPicture/Image Generation
dc.subjectViewing algorithms
dc.subjectI.3.6 [Computer Graphics]
dc.subjectMethodology and Techniques
dc.subjectInteraction techniques
dc.subjectI.3.8 [Computer Graphics]
dc.subjectApplications
dc.subjectProbabilistic Weather Forecasting
dc.titleAlbero: A Visual Analytics Approach for Probabilistic Weather Forecastingen_US
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