In public discourse on the subject of climate change, there is considerable doubt regarding global climate models (Douglas et al. Int. J. Climatol. 2007), particularly with respect to the effects of clouds. Moreover, there have been questions regarding the magnitude of the rate of global temperature change, as well as its error relative to the error in local temperature measurement. In this paper, an "omic" approach to global temperature change is undertaken utilizing publicly-available temperature databases. Robust statistical approaches are employed to analyze temperature timeseries for over 400 cities of various sizes, latitudes and longitudes, and identify positional and seasonal trends in climate change. A detailed analysis of Antarctic temperatures over the past fifty years is also conducted, illustrating the relationship between global temperature and the Antarctic climate.