Atmospheric Chemistry and Physics Discussions www.atmos-chem-phys-discuss.net 1680-7367 1680-7375 10 4 2010 10.5194/acpd-10-11401-2010 http://www.atmos-chem-phys-discuss.net/10/11401/2010/ http://www.atmos-chem-phys-discuss.net/10/11401/2010/acpd-10-11401-2010.html http://www.atmos-chem-phys-discuss.net/10/11401/2010/acpd-10-11401-2010.pdf 11401 11448 2010-04-28 Multi sensor reanalysis of total ozone R. J. van der A avander@knmi.nl M. A. F. Allaart H. J. Eskes KNMI, P.O. Box 201, 3730 AE De Bilt, The Netherlands A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based on independent ground-based total ozone data from the World Ozone and Ultraviolet Data Center. The correction is a function of solar zenith angle, viewing angle, time (trend), and stratospheric temperature. As second step data assimilation was applied to create a global dataset of total ozone analyses. The data assimilation method is a sub-optimal implementation of the Kalman filter technique, and is based on a chemical transport model driven by ECMWF meteorological fields. The chemical transport model provides a detailed description of (stratospheric) transport and uses parameterisations for gas-phase and ozone hole chemistry. 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