Monday, 7 January 2013
Exhibit Hall 3 (Austin Convention Center)
Climatologists concerned with global warming are familiar with the significance of research into the climate of the polar regions. Because the arctic region is the most sensitive to react to climatic changes, the modeling of atmospheric temperature profiles over the arctic region is being investigated. Mean tropospheric temperature profiles from global meteorological data sets are used to model the arctic climatology. 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 the arctic seasons. From ground based and satellite observations, it has been observed that seasonal changes can produce temperature profiles that are significantly different for this high latitude geographical region. Parameterization of mean monthly tropospheric temperature profiles from radiosonde stations in the arctic are examined and specific characteristics are analyzed. Radiosonde temperature profiles from various arctic radiosonde stations were used to test the modeled temperature profile performance.
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