Merging Ozone Profiles from ESA Envisat and Third Party Missions Limb Measurements
Sofieva, Viktoria1; Tamminen, Johanna1; Kyrölä, Erkki1; Kalakoski, Niilo1; Laine, Marko1; Rahpoe, Nabiz2; Weber, Mark2; Laeng, Alexandra3; von Clarmann, Thomas3; Stiller, Gabriele3; Hauchecorne, Alain4; Degenstein, Doug5; Adams, Cristen5; Lloyd, Nick5; Bernath, Peter6; Hargreaves, Robert6; Urban, Joachim7; Murtagh, Donal7; Van Roosendael, Michel8; Zehner, Claus9
1Finnish Meteorological Institute, FINLAND; 2Institute of Environmental Physics, University of Bremen, GERMANY; 3Karlsruhe Institute of Technology, GERMANY; 4LATMOS, FRANCE; 5University of Saskatchewan, CANADA; 6University of York, UNITED KINGDOM; 7Chalmers University, SWEDEN; 8BISA, BELGIUM; 9ESA/ESRIN, ITALY

The use of combined data from different limb sensors is of high interest, because they provide much better spatio-temporal coverage than each of the instruments separately. However, the data from different instruments can be biased with respect to each other, have different vertical resolution, are attributed to different local times, and might use different a priori information in the inversion process. The creation of homogenized ozone datasets based on limb and occultation measurements from ENVISAT sensors (GOMOS, MIPAS, SCIAMACHY) as well as from ESA Third Party Missions (OSIRIS, SMR and ACE-FTS) is one of the objectives of the on-going ESA ozone-CCI project. In the framework of the ozone-CCI project, different datasets are created. They are the harmonized dataset of ozone profiles from each instrument in a common data format, the merged monthly zonal mean profiles, the merged bi-monthly mean datasets with resolved longitudinal structure, and the fine-resolution merged dataset. In this presentation, we introduce these datasets, discuss the methods used for data merging, and show examples from the created datasets.