In this communication, Earth temperature series in air and soil are analyzed and features that become convoluted with the known earth cycles of day-night and its orbit around the sun are separated. Atmospheric carbon dioxide concentrations are also considered. Earth weather changes (e.g., cloud, wind, rain, polar jet streams, and atmospheric pressure) in real time affect daily temperatures in a complex manner. A statistical model that accounts for autocorrelation and linear trend is evaluated together with empirical description of the series. Further graphical analysis is used to enhance remaining features and extreme events. Gaussian bell-shaped curve modeling of each year's daily profile is described. Further, Gaussian parameter-based anomalies are introduced together with soil anomalies at 30 cm depth. Semi-variogram components are shown along with folded percentile or mountain plots for data visualization. The Chow test is described for detection of any structural changes in data series. For much of the statistical analysis, temperatures observed daily are most appropriate because they carry variation due to earth, sea and sky weather over a single day-night earth rotation cycle. Also, the ever changing earth position along its orbital path captures a varying amount of solar energy, hence the shape of the temperature cycle as one sees it. Human activity and climate changing factors appear to affect temperature cycles within and over years. A double bell-shaped Gaussian curve fit can indicate climate changing effects of Earth life.