Retrieval of atmospheric parameters from GOMOS data
1Finnish Meteorological Institute, Earth Observation, Helsinki, Finland
2Laboratoire Atmosphères, Milieux, Observations Spatiales, Université Versailles St-Quentin, CNRS-INSU, Verrières-le-Buisson, France
3Institut d'Aéronomie Spatiale de Belgique, Brussels, Belgium
4ACRI-ST, Sophia Antipolis, France
5European Space Research Institute (ESRIN), European Space Agency, Frascati, Italy
6EADS-Astrium, Toulouse, France
Abstract. The Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the European Space Agency's ENVISAT satellite measures attenuation of stellar light in occultation geometry. Daytime measurements also record scattered solar light from the atmosphere. The wavelength regions are the ultraviolet-visible band 248–690 nm and two infrared bands at 755–774 nm and at 926–954 nm. From UV-Visible and IR spectra the vertical profiles of O3, NO2, NO3, H2O, O2 and aerosols can be retrieved. In addition there are two 1 kHz photometers at blue 473–527 nm and red 646–698 nm. Photometer data are used to correct spectrometer measurements for scintillations and to retrieve high resolution temperature profiles as well as gravity wave and turbulence parameters. Measurements cover altitude region 5–150 km. Atmospherically valid data are obtained in 15–100 km.
In this paper we present an overview of the GOMOS retrieval algorithms for stellar occultation measurements. The low signal-to-noise ratio and the refractive effects due to the point source nature of stars have been important drivers in the development of GOMOS retrieval algorithms. We present first the Level 1b algorithms that are used to correct instrument related disturbances in the spectrometer and photometer measurements The Level 2 algorithms deal with the retrieval of vertical profiles of atmospheric gaseous constituents, aerosols and high resolution temperature. We divide the presentation into correction for refractive effects, high resolution temperature retrieval and spectral/vertical inversion. The paper also includes discussion about the GOMOS algorithm development, expected improvements, access to GOMOS data and alternative retrieval approaches.