Seasonal atmospheric temperature profiles over the Northern Hemisphere are presented. Mean tropospheric temperature profiles as a function of latitudinal belts are estimated from global meteorological data sets. Neural network algorithms were applied to archived radiosonde measurements, retrieved temperature profiles from remote sensing methods, standard atmosphere supplement profiles, and monthly solar insolation. For these investigations, we draw upon a wealth of observed global climate data sets which allows us to explore aspects of temperature profiles throughout varied regions in the Northern Hemisphere. From ground based and satellite observations, it has been observed that seasonal changes in conjunction with latitudinal variations can produce temperature profiles that can significantly differ from the standard atmosphere, especially for higher latitude geographical regions. Parameterization of mean monthly tropospheric temperature profiles in the Northern Hemisphere are examined and specific characteristics are analyzed. Radiosonde temperature profiles from various global radiosonde stations were used to test the temperature profile neural network's performance.