This paper describes and assesses the performance of the RAL (Rutherford Appleton Laboratory) ozone profile retrieval scheme for the Global Ozone Monitoring Experiment 2 (GOME-2) with a focus on tropospheric ozone. Developments to the scheme since its application to GOME-1 measurements are outlined. These include the approaches developed to account sufficiently for UV radiometric degradation in the Hartley band and for inadequacies in knowledge of instrumental parameters in the Huggins bands to achieve the high-precision spectral fit required to extract information on tropospheric ozone. The assessment includes a validation against ozonesondes (sondes) sampled worldwide over 2 years (2007-2008). Standard deviations of the ensemble with respect to the sondes are considerably lower for the retrieved profiles than for the a priori, with the exception of the lowest subcolumn. Once retrieval vertical smoothing (averaging kernels) has been applied to the sonde profiles there is a retrieval bias of 6% (1.5 DU) in the lower troposphere, with smaller biases in the subcolumns above. The bias in the troposphere varies with latitude. The retrieval underestimates lower tropospheric ozone in the Southern Hemisphere (SH) (15-20% or similar to 1-3 DU) and overestimates it in the Northern Hemisphere (NH) (10% or 2 DU). The ability of the retrieval to reflect the geographical distribution of lower tropospheric ozone, globally (rather than just ozonesonde launch sites) is demonstrated by comparison with the chemistry transport model TOMCAT. For a monthly mean of cloud-cleared GOME-2 pixels, a correlation of 0.66 is found between the retrieval and TOMCAT sampled accordingly, with a bias of 0.7 Dobson Units. GOME-2 estimates higher concentrations in NH pollution centres but lower ozone in the Southern Ocean and South Pacific, which is consistent with the comparison to ozonesondes.
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Royal Netherlands Meteorol Inst, Climate Observat Dept, NL-3730 AE De Bilt, Netherlands
Eindhoven Univ Technol, Fluid Dynam Lab, NL-5600 MB Eindhoven, NetherlandsChiba Univ, Ctr Environm Remote Sensing, Inage Ku, Chiba 2638522, Japan
Boersma, K. F.
Kanaya, Y.
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Japan Agcy Marine Earth Sci & Technol, Res Inst Global Change, Kanazawa Ku, Yokohama, Kanagawa 2360001, JapanChiba Univ, Ctr Environm Remote Sensing, Inage Ku, Chiba 2638522, Japan
Kanaya, Y.
Takashima, H.
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Japan Agcy Marine Earth Sci & Technol, Res Inst Global Change, Kanazawa Ku, Yokohama, Kanagawa 2360001, Japan
Fukuoka Univ, Fac Sci, Dept Earth Syst Sci, Jounan Ku, Fukuoka 8140180, JapanChiba Univ, Ctr Environm Remote Sensing, Inage Ku, Chiba 2638522, Japan
Takashima, H.
Pan, X.
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Japan Agcy Marine Earth Sci & Technol, Res Inst Global Change, Kanazawa Ku, Yokohama, Kanagawa 2360001, JapanChiba Univ, Ctr Environm Remote Sensing, Inage Ku, Chiba 2638522, Japan
Pan, X.
Wang, Z. F.
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Chinese Acad Sci, Inst Atmospher Phys, LAPC, Beijing 100029, Peoples R ChinaChiba Univ, Ctr Environm Remote Sensing, Inage Ku, Chiba 2638522, Japan
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Belgian Inst Space Aeron BIRA IASB, Brussels, BelgiumDeutsch Zentrum Luft & Raumfahrt DLR, Inst Method Fernerkundung IMF, Oberpfaffenhofen, Germany
Pinardi, Gaia
De Smedt, Isabelle
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Belgian Inst Space Aeron BIRA IASB, Brussels, BelgiumDeutsch Zentrum Luft & Raumfahrt DLR, Inst Method Fernerkundung IMF, Oberpfaffenhofen, Germany
De Smedt, Isabelle
Yu, Huan
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Belgian Inst Space Aeron BIRA IASB, Brussels, BelgiumDeutsch Zentrum Luft & Raumfahrt DLR, Inst Method Fernerkundung IMF, Oberpfaffenhofen, Germany
Yu, Huan
Beirle, Steffen
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Max Planck Inst Chem, Mainz, GermanyDeutsch Zentrum Luft & Raumfahrt DLR, Inst Method Fernerkundung IMF, Oberpfaffenhofen, Germany