Atmospheric Chemistry and Physics Discussions www.atmos-chem-phys-discuss.net 1680-7367 1680-7375 10 1 2010 10.5194/acpd-10-1417-2010 http://www.atmos-chem-phys-discuss.net/10/1417/2010/ http://www.atmos-chem-phys-discuss.net/10/1417/2010/acpd-10-1417-2010.html http://www.atmos-chem-phys-discuss.net/10/1417/2010/acpd-10-1417-2010.pdf 1417 1456 2010-01-20 Intercomparison methods for satellite measurements of atmospheric composition: application to tropospheric ozone from TES and OMI L. Zhang linzhang@fas.harvard.edu D. J. Jacob X. Liu J. A. Logan K. Chance A. Eldering B. R. Bojkov Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02138, USA School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland, USA Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA NASA Goddard Space Flight Center, Greenbelt, Maryland, USA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA European Space Agency (ESA/ESRIN), Science, Applications and Future Technologies Department, Via Galileo Galilei, Casella Postale 64, 00044 Frascati (RM), Italy We analyze three different methods to validate and intercompare satellite measurements of atmospheric composition, and apply them to tropospheric ozone retrievals from the Tropospheric Emission Spectrometer (TES) and the Ozone Monitoring Instrument (OMI). The first method (in situ method) uses in situ vertical profiles for absolute instrument validation; it is limited by the sparseness of in situ data. The second method (CTM method) uses a chemical transport model (CTM) as an intercomparison platform; it provides a globally complete intercomparison with relatively small noise added by model error. The third method (averaging kernel smoothing method) involves smoothing the retrieved profile from one instrument with the averaging kernel matrix of the other; it also provides a global intercomparison but dampens the actual difference between instruments and adds noise from the a priori. Application to a full year (2006) of TES and OMI data shows mean positive biases of 5.3 parts per billion volume (ppbv) (10%) for TES and 2.8 ppbv (5%) for OMI at 500 hPa relative to in situ data from ozonesondes. We show that the CTM method (using the GEOS-Chem CTM) closely approximates results from the in situ method while providing global coverage. 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