2010
DOI: 10.1109/tvcg.2010.181
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Noodles: A Tool for Visualization of Numerical Weather Model Ensemble Uncertainty

Abstract: Numerical weather prediction ensembles are routinely used for operational weather forecasting. The members of these ensembles are individual simulations with either slightly perturbed initial conditions or different model parameterizations, or occasionally both. Multi-member ensemble output is usually large, multivariate, and challenging to interpret interactively. Forecast meteorologists are interested in understanding the uncertainties associated with numerical weather prediction; specifically variability be… Show more

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Cited by 236 publications
(164 citation statements)
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“…Much of the work has focused on developing typologies of uncertainty that represent various aspects of data and how it might be signified (Buttenfield and Weibel, 1988;Pang et al, 1997;Sanyal et al, 2009;Thomson et al, 2005) and on developing methods to depict uncertainty visually (e.g. Cedilnik and Rheingans, 2000;Ehlschlaeger et al, 1997;Sanyal et al, 2010;Wittenbrink et al, 1996). A comprehensive review of uncertainty typologies is provided by MacEachren et al (2005) and a review of uncertainty visualisation across science by Brodlie et al (2012).…”
Section: Introductionmentioning
confidence: 99%
“…Much of the work has focused on developing typologies of uncertainty that represent various aspects of data and how it might be signified (Buttenfield and Weibel, 1988;Pang et al, 1997;Sanyal et al, 2009;Thomson et al, 2005) and on developing methods to depict uncertainty visually (e.g. Cedilnik and Rheingans, 2000;Ehlschlaeger et al, 1997;Sanyal et al, 2010;Wittenbrink et al, 1996). A comprehensive review of uncertainty typologies is provided by MacEachren et al (2005) and a review of uncertainty visualisation across science by Brodlie et al (2012).…”
Section: Introductionmentioning
confidence: 99%
“…Comparative compose plots, as a standout amongst the most prominent strategies, was first suggested by Inselberg [3] and Wegman recommended it as something for extraordinary viewpoint data inquire about [4]. Directions of n-dimensional data can be authorized upon in parallel tomahawks in a 2-dimensional airplane and connected by straight sections.…”
Section: Related Workmentioning
confidence: 99%
“…In their experiments, scaled sphere and color mapped sphere perform better than traditional error bars and color-mapped surfaces. Later, they proposed graduated glyphs and ribbons to encode uncertainty information of weather simulations [13]. Figure 2.1 is borrowed from Sanyal et al [12] and shows the four uncertainty visualization techniques in their user study.…”
Section: Uncertainty Visualizationmentioning
confidence: 99%
“…Figure 2.1 is borrowed from Sanyal et al [12] and shows the four uncertainty visualization techniques in their user study. While the uncertainty visualization is application-dependent in many cases, two visualization schemes are widely used: using intuitive metaphors, such as blurry and fuzzy effects [11], [14], [15], which naturally implies the existence of uncertainty; and using quantitative glyphs [13], [16], which shows quantified uncertainty information explicitly. Both schemes have their own tradeoffs.…”
Section: Uncertainty Visualizationmentioning
confidence: 99%