The purpose of the study was to determine, through the utilization of a multivariate statistical technique called Principal Component Analysis (PCA), whether ozone measurements derived from satellites could be used to infer surface-layer concentrations. Examination of the spatial and temporal characteristics associated with the first nonrotated principal components (which are the dominant components, explaining 37.95 and 41.25% of the total variance of the surface and satellite data sets, respectively) revealed considerable coherence between the data sets suggesting that on continental-scales, seasonal O3 patterns derived from the satellite data replicate, quite well, those of the surface. This coherence diminishes, however, when daily patterns are compared. Upon orthogonal rotation, the PCA delineated four contiguous and statistically unique subregions with each data set (the Northwest, Northeast, Southwest and Southeast) that were similar, suggesting that the satellite data may be able to discern O3 patterns on spatial scales as small as 1000 km.