Multi sensor reanalysis of total ozone

• Published in: Atmospheric chemistry and physics discussions Vol. 10; no. 4; pp. 11401 - 11448
• Main Authors: der A, RJvan, Allaart, MAF, Eskes, HJ
• Format: Journal Article
• Language: English
• Published: 28.04.2010
• ISSN: 1680-7367; 1680-7375

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. The MSR dataset results from a 30-year data assimilation run with the 14 corrected satellite datasets as input, and is available on a grid of 11[frac12] degrees with a sample frequency of 6 h for the complete time period (1978-2008). The Observation-minus-Analysis (OmA) statistics show that the bias of the MSR analyses is less than 1 percent with an RMS standard deviation of about 2 percent as compared to the corrected satellite observations used.