Forward Model for Temperature Derivation from Atmospheric Lidar


Jaren Hobbs

Document Type


Journal/Book Title/Conference

USU Student Showcase

Publication Date


Faculty Mentor

Vincent Wickwar


Atmospheric Lidar takes advantage of Rayleigh backscattering to create a relative density profile of the atmosphere. The method for temperature derivation is based on the work of Chanin and Hauchecorne (CH). Beginning with an initial temperature, and utilizing the ideal gas law, a downward integration procedure is applied to create a temperature profile from the density profile down to forty-five kilometers. Since this initial temperature is only a best guess, the temperatures towards the top of the profile may not be accurate. However, so long as the guess is reasonable, within perhaps a fifty Kelvin margin (though hopefully not far off), multiple guesses seem to converge after working down fifteen or so kilometers. The Khanna method attempts to reclaim the uppermost data by applying a forward model using the CH temperatures and working back up from the bottom. The forward model takes a temperature profile and derives a density profile. The Khanna method adjust the CH temperatures until the derived densities converge with the observed densities.

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