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Volume 18, issue 13
Atmos. Chem. Phys., 18, 9189-9205, 2018
https://doi.org/10.5194/acp-18-9189-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Chem. Phys., 18, 9189-9205, 2018
https://doi.org/10.5194/acp-18-9189-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Jul 2018

Research article | 03 Jul 2018

Harmonisation and trends of 20-year tropical tropospheric ozone data

Elpida Leventidou1, Mark Weber1, Kai-Uwe Eichmann1, John P. Burrows1, Klaus-Peter Heue2, Anne M. Thompson3, and Bryan J. Johnson4 Elpida Leventidou et al.
  • 1Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
  • 2Deutsches Zentrum für Luft- und Raumfahrt, Münchener Str. 20, 82234 Oberpfaffenhofen, Germany
  • 3NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
  • 4Global Monitoring Division, NOAA ESRL, Boulder, Colorado, USA

Abstract. Using a convective-cloud differential (CCD) method, developed in-house and applied to retrievals of total ozone and cloud data from three European satellite instruments (viz. GOME/ERS-2, 1995–2003; SCIAMACHY/Envisat, 2002–2012 and GOME-2/MetOp-A, 2007–2015), monthly mean tropical tropospheric columns of ozone (TTCO) have been retrieved, which are in good agreement with ozonesondes (biases less than 6DU). As small differences in TTCO between the individual instruments were evident, it was necessary to develop a scheme to harmonise the three datasets into one consistent time series starting from 1996 until 2015. Correction offsets (biases) between the instruments using SCIAMACHY as intermediate reference have been calculated and six different harmonisation or merging scenarios have been evaluated. Depending on the merging approach, the magnitude, pattern and uncertainty in the trends strongly vary. The harmonisation or merging represents an additional source of uncertainty in the trends (2DUdecade−1 on average, in most of the cases exceeding the uncertainty from the regression). For studying further details on tropospheric ozone trends on various spatial scales in the tropics, we stick with one preferred merged dataset that shows best agreement with ozonesondes. In this merged dataset, no correction was applied for GOME, and mean biases with respect to SCIAMACHY in the overlapping period (2007–2012) were calculated and applied for GOME-2 in each grid box (2.5° × 5°). In contrast with other studies we found that the tropospheric trend averaged over the tropics (−15°S to 15°N) is not statistically significant. The mean tropospheric ozone trend equals −0.2±0.6DUdecade−1 (2σ). Regionally, tropospheric ozone has a statistically significant increase of  ∼ 3DUdecade−1 over southern Africa ( ∼1.5%yr−1), the southern tropical Atlantic ( ∼1.5%yr−1), southeastern tropical Pacific Ocean ( ∼1%yr−1), and central Oceania ( ∼2%yr−1) and by  ∼ 2DUdecade−1 over central Africa (2–2.5%yr−1) and south India ( ∼1.5%yr−1). On the other hand, tropospheric O3 decreases by  ∼ 3DUdecade−1 over the Caribbean Sea and parts of the North Pacific Ocean ( ∼2%yr−1), and by less than 2DUdecade−1 over some regions of the southern Pacific and Indian oceans ( ∼ 0.5–1%yr−1).

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Three individual tropical tropospheric ozone (TTCO) datasets (1996–2015) retrieved with the convective-cloud differential method (Leventidou et al., 2016) have been harmonised in order to study the global and regional TTCO trends. The trends range between −4 to 4 DU per decade testing six different merging scenarios. No trend has been found for the global tropics using the preferred scenario. It is concluded that harmonisation is one of the major sources of uncertainty in the trend estimates.
Three individual tropical tropospheric ozone (TTCO) datasets (1996–2015) retrieved with the...
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