Visual data mining in atmospheric science data

This paper discusses the use of simple visual tools to explore multivariate spatially-referenced data. It describes interactive approaches such as lin ked brushing, and dynamic methods such as the grand tour, applied to studyi ng the Comprehensive Ocean-Atmosphere Data Set (COADS). This visual approac h provides an alternative way to gain understanding of high-dimensional dat a. It also provides cross-validation and visual adjuncts to the more comput ationally intensive data mining techniques.