NASA's Earth Observing System (EOS) produces vast quantities of satellite data. These data are intended for the study of global climate change, its consequences for life on Earth, and the impact of human activities on it. However, EOS data sets are so large and complex that it is difficult, if not impossible, to understand their large-scale structure and draw conclusions that could help to inform the debate over climate change. In this talk we discuss our procedure for visualizing structure in these massive data sets. We present a prototype visualization tool written in Java, and demonstrate its use on data from JPL's Multi-angle Imaging SpectroRadiometer (MISR).