Atmospheric phenomena in particular can be represented effectively using the dynamic variables. In the context of climate models, DiBiase, et al. Several EDA methods have been successfully extended to exploratory spatial data analysis. In their case, animation was used not to shift the viewer's focus from one place to another, but from one category of attribute to another, through a sequencing of information by data category. To illustrate their concept of proactive graphics, they developed a prototype that allows an analyst to interactively control an animated representation of tree growth over time.
Uncertainty is a key facet of that metadata.
To represent uncertainty it must be defined, both generally and specifically. A step toward such a definition is a categorization of components. With the general components of uncertainty identified, the next step in the production of a representation of uncertainty is to determine which aspects are relevant to a specific instance. Once this decision is made, estimates of uncertainty must be matched to appropriate visualization tools and methods. Two major issues can be identified.