Retrieval Technique Of Key Ionospheric Parameters From Far Ultraviolet Remote Sensing

The space borne far ultraviolet imaging spectrograph can be used to observe theEarth’s far ultraviolet (FUV) airglow, which can provide us with fundamental diagnosticinformation about the state of the ionosphere and the ionospheric environmental parameters.It’s concerned and necessary to study the retrieval method of using the remote sensingmeasurements of far ultraviolet imaging spectrograph to derive the ionosphere’senvironmental parameters. The thesis is centered on “Retrieving key ionosphericenvironmental parameters from space borne far ultraviolet remote sensing data”, aiming tocontinuously monitor and forecast the space weather of the upper atmosphere.Firstly, the chemical mechanism of far ultraviolet airglow is discussed and theradiance equation for a given observing direction is derived. Based on the AtmosphericUltraviolet Radiance Integrated Code, the influences of the solar reference spectrum and O2absorption cross section on the disk and limb airglow radiance intensity are analyzed, amethod to modify the simulated airglow radiance intensity using the observed solarspectrum is put up, and the problem of the accuracy of the simulated radiance intensity issolved, thus laying a foundation for the research on extracting the information ofthermospheric and ionospheric species and the response to the external energy.Secondly, based on the Atmospheric Ultraviolet Radiance Integrated Code, theretrieval method of using the disk measurements of OI130.4nm dayglow to infer thethermospheric O/N2is investigated. The imaging geometry of Global Ultraviolet Imagerused as an example, the equations of the satellite observing angle and solar zenith angle arederived, the theoretical model between OI130.4nm dayglow and thermospheric O/N2isestablished, and applying HSV color-space histogram cross matching method to evaluatingthe retrieved O/N2results from far ultraviolet remote sensing measurements. The resultsdemonstrate that OI130.4nm dayglow is suitable for remote sensing thermospheric O/N2,which will greatly reduce the difficulties of using far ultraviolet imaging spectrograph toremote sense the ionospheric state.Thirdly, the ionospheric Electron Density Profile is obtained from the limb-viewing OI135.6nm nightglow measurements of Global Ultraviolet Imager. In this paper, the limb-scanning viewing model is established, the computation of the projected matrix isderived, a free-form ionospheric Electron Density Profile is computed using theregularization method combined with Newton iteration, the Chapman-fitted ElectronDensity Profile is obtained by substitution of the peak altitude and peak electron density ofthe free-form ionospheric Electron Density Profile into the Chapman function, and comparethem with the corresponding results from the ground-based measurements and FullAnalytic Ionosphere Model, evaluating the effectiveness of the retrieval algorithm.Finally, the ionospheric Total Electron Content is inferred from the disk measurementsof OI135.6nm nightglow radiance intensity. The theoretical formulation betweennadir-viewing OI135.6nm nightglow radiance intensity and ionospheric Total ElectronContent is established, the radiometric correction of the measurements based onAtmospheric Ultraviolet Radiance Integrated Code is put forward, which serves as areference of using the disk-scanning OI135.6nm nightglow of far ultraviolet imagingspectrograph to monitor the ionospheric Total Electron Content. In this paper, theionospheric Total Electron Content retrieved from the disk and limb measurements of OI135.6nm nightglow radiation using three methods is computed, and the ionospheric TotalElectron Content of the same time and space using the neighboring linear interpolationmethod is used as the reference to evaluate the retrieved ionospheric Total ElectronContent.This paper focuses on both of the disk and limb viewing modes of space borne farultraviolet imaging spectrograph, leads the research of retrieving ionospheric environmentalparameters, such as O/N2, EDP and TEC, from the remote sensing data, and provides atheoretical basis and technical support for developing technology in future.