1Finnish Meteorological Institute, Earth Observation, Helsinki, Finland
2LATMOS/IPSL, UVSQ, CNRS-INSU, Paris, France
3BIRA-IASB, Brussels, Belgium
4ACRI ST, Sophia Antipolis, France
6EADS-Astrium, Toulouse, France
Received: 31 Jan 2010 – Published in Atmos. Chem. Phys. Discuss.: 11 Mar 2010
Abstract. The Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument uses stellar occultation technique for monitoring ozone, other trace gases and aerosols in the stratosphere and mesosphere. The self-calibrating measurement principle of GOMOS together with a relatively simple data retrieval where only minimal use of a priori data is required provides excellent possibilities for long-term monitoring of atmospheric composition.
Revised: 07 Sep 2010 – Accepted: 23 Sep 2010 – Published: 08 Oct 2010
GOMOS uses about 180 of the brightest stars as its light source. Depending on the individual spectral characteristics of the stars, the signal-to-noise ratio of GOMOS varies from star to star, resulting also in varying accuracy of retrieved profiles. We present here an overview of the GOMOS data characterisation and error estimation, including modeling errors, for O3, NO2, NO3, and aerosol profiles. The retrieval error (precision) of night-time measurements in the stratosphere is typically 0.5–4% for ozone, about 10–20% for NO2, 20–40% for NO3 and 2–50% for aerosols. Mesospheric O3, up to 100 km, can be measured with 2–10% precision. The main sources of the modeling error are incompletely corrected scintillation, inaccurate aerosol modeling, uncertainties in cross sections of trace gases and in atmospheric temperature. The sampling resolution of GOMOS varies depending on the measurement geometry. In the data inversion a Tikhonov-type regularization with pre-defined target resolution requirement is applied leading to 2–3 km vertical resolution for ozone and 4 km resolution for other trace gases and aerosols.
Tamminen, J., Kyrölä, E., Sofieva, V. F., Laine, M., Bertaux, J.-L., Hauchecorne, A., Dalaudier, F., Fussen, D., Vanhellemont, F., Fanton-d'Andon, O., Barrot, G., Mangin, A., Guirlet, M., Blanot, L., Fehr, T., Saavedra de Miguel, L., and Fraisse, R.: GOMOS data characterisation and error estimation, Atmos. Chem. Phys., 10, 9505-9519, doi:10.5194/acp-10-9505-2010, 2010.