The SPARC Data Initiative: Comparison of upper troposphere/lower stratosphere ozone climatologies from limb‐viewing instruments and the nadir‐viewing Tropospheric Emission Spectrometer. Issue 11 (12th June 2014) - Neu, J. L.; Hegglin, M. I.; Tegtmeier, S.; Bourassa, A.; Degenstein, D.; Froidevaux, L.; Fuller, R.; Funke, B.; Gille, J.; Jones, A.; Rozanov, A.; Toohey, M.; et al.
Abstract We present the first comprehensive intercomparison of currently available satellite ozone climatologies in the upper troposphere/lower stratosphere (UTLS) (300–70 hPa) as part of the Stratosphere‐troposphere Processes and their Role in Climate (SPARC) Data Initiative. The Tropospheric Emission Spectrometer (TES) instrument is the only nadir‐viewing instrument in this initiative, as well as the only instrument with a focus on tropospheric composition. We apply the TES observational operator to ozone climatologies from the more highly vertically resolved limb‐viewing instruments. This minimizes the impact of differences in vertical resolution among the instruments and allows identification of systematic differences in the large‐scale structure and variability of UTLS ozone. We find that the climatologies from most of the limb‐viewing instruments show positive differences (ranging from 5 to 75%) with respect to TES in the tropical UTLS, and comparison to a "zonal mean" ozonesonde climatology indicates that these differences likely represent a positive bias for p ≤ 100 hPa. In the extratropics, there is good agreement among the climatologies regarding the timing and magnitude of the ozone seasonal cycle (differences in the peak‐to‐peak amplitude of <15%) when the TES observational operator is applied, as well as very consistent midlatitude interannual variability. The discrepancies in ozone temporal variability are larger in the tropics, with differences between the data sets of up to 55% in the seasonal cycle amplitude. However, the differences among the climatologies are everywhere much smaller than the range produced by current chemistry‐climate models, indicating that the multiple‐instrument ensemble is useful for quantitatively evaluating these models.