Seasonal atmospheric temperature profiles over the Northern Hemisphere arepresented. Mean tropospheric temperature profiles as a function of latitudinal beltsare estimated from global meteorological data sets. Neural network algorithmswere applied to archived radiosonde measurements, retrieved temperature profilesfrom remote sensing methods, standard atmosphere supplement profiles, andmonthly solar insolation. For these investigations, we draw upon a wealth ofobserved global climate data sets which allows us to explore aspects of temperatureprofiles throughout varied regions in the Northern Hemisphere. From ground basedand satellite observations, it has been observed that seasonal changes inconjunction with latitudinal variations can produce temperature profiles that cansignificantly differ from the standard atmosphere, especially for higher latitudegeographical regions. Parameterization of mean monthly tropospheric temperatureprofiles in the Northern Hemisphere are examined and specific characteristics areanalyzed. Radiosonde temperature profiles from various global radiosonde stationswere used to test the temperature profile neural network’s performance.
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