Extension of the ESA CCI Total Ozone Climate Data Record with the Application of the GODFITv3 Algorithm to OMI Observations

Christophe Lerot (1) , Thomas Danckaert (1) , Michel van Roozendael (1) , Robert Spurr (2) , Diego Loyola (3) , Melanie Coldewey-Egbers (3) , Mariliza Koukouli (4) , Irene Zyrichidou (4) , Dimitris Balis (4) , Jean-Christopher Lambert (1) , José Granville (1) , Florence Goutail (5) , Jean-Pierre Pommereau (5) , Claus Zehner (6)

1 BIRA-IASB - Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique
2 RT Solutions Inc.
3 IMF - DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute
4 Laboratory of Atmospheric Physics [Thessaloniki]
5 STRATO - LATMOS
6 ESRIN - European Space Research Institute

One of the great achievements of the first phase of the ESA Ozone Climate Change Initiative has been the release of new level-2 total ozone data sets from GOME, SCIAMACHY and GOME-2/Metop-A reprocessed with the latest GODFIT-3 algorithm. These data sets are characterized by unprecedented standards of consistency, stability and accuracy. Recently, new algorithmic developments have been implemented within GODFIT in order to ingest and analyse backscattered light spectra measured by OMI (Ozone Monitoring Instrument), the hyperspectral imager launched as part of the AURA platform payload in 2004. In particular, a new look-up table version of GODFIT has been developed to process the massive OMI level-1 data set in a timely and fast manner. We show that this approach maintains a level of accuracy similar to that of the on-line GODFIT version, in addition to providing accelerated performance by a factor of 10. This fast algorithm has been recently used to reprocess the entire OMI time series, thus extending the ESA CCI Climate data record for total ozone In this work, the OMI GODFIT-3 total ozone product is compared to the two operational products OMI-TOMS and OMI-DOAS, and also to the historical multi-sensor CCI data set. These comparisons clearly indicate that the new product is highly consistent with other data sets and is of very high quality, even in extreme geophysical conditions (ozone hole, Polar Regions, …). We show that an optimization of the pre-flight instrumental slit functions has been necessary in the ozone fitting window (325-335 nm) in order to completely eliminate any row dependence in the product. With its remarkable long-term stability, OMI has the potential to be used in combination with GOME as a long-term reference for producing multi-sensor climate total ozone data record.

Domaines: Climatologie; Océan, Atmosphère

Christophe Lerot, Thomas Danckaert, Michel van Roozendael, Robert Spurr, Diego Loyola, et al.. Extension of the ESA CCI Total Ozone Climate Data Record with the Application of the GODFITv3 Algorithm to OMI Observations. ATMOS 2015. Advances in Atmospheric Science and Applications, Jun 2015, Heraklion, Greece. 41, Paper 115, 2015. ⟨insu-01162162⟩