This talk addresses the challenge of visualizing cluster-compressed atmospheric data from AIRS (Atmospheric Infra-Red Spectroscopy) in a geospatial context. Each cluster has 35 variables including temperature and water vapor at 11 altitudes and cloud fraction at 10 altitudes. One approach uses Java shareware called CCmaps. CCmaps conveys three variables for regions in a map using sliders, color and conditioning. Generating regions representing both altitude and membership in latitude and longitude grid cells brings all altitude data for three variables into play. A second approach uses C++/OpenGL software called Glisten to represent data using 3D rendered glyphs. This shows altitude using a z-axis. Widgets enable variable selection and transfer function control of glyph features such a color (via color ramps), size, transparency, and filtering. Live examples convey options and insights.