GOME level 1-to-2 data processor version 3.0: a major upgrade of the GOME/ERS-2 total ozone retrieval algorithm
Van Roozendael, M.
Earth and related Environmental sciences
Optical data processing
automated pattern recognition
Information Storage and Retrieval
Pattern Recognition, Automated
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The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME data processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between -2% and +4% of ground-based values for moderate solar zenith angles lower than 70°. A larger variability of about +5% and -8% is observed for higher solar zenith angles up to 90°.
CitationSpurr, R.; Loyola, D.; Thomas, W.; Balzer, W.; Mikusch, E.; Aberle, B.; Slijkhuis, S.; Ruppert, T.; Van Roozendael, M.; Lambert, J.-C.; Soebijanta, T. (2005). GOME level 1-to-2 data processor version 3.0: a major upgrade of the GOME/ERS-2 total ozone retrieval algorithm. , Applied Optics, Vol. 44, Issue 33, 7196-7209, DOI: 10.1364/AO.44.007196.