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Earth System Science Data The data publishing journal
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Volume 10, issue 1
Earth Syst. Sci. Data, 10, 449-468, 2018
https://doi.org/10.5194/essd-10-449-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 10, 449-468, 2018
https://doi.org/10.5194/essd-10-449-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Review article 12 Mar 2018

Review article | 12 Mar 2018

The ESA GOME-Evolution “Climate” water vapor product: a homogenized time series of H2O columns from GOME, SCIAMACHY, and GOME-2

Steffen Beirle1, Johannes Lampel1,a, Yang Wang1, Kornelia Mies1, Steffen Dörner1, Margherita Grossi2, Diego Loyola2, Angelika Dehn3, Anja Danielczok4, Marc Schröder4, and Thomas Wagner1 Steffen Beirle et al.
  • 1Max-Planck-Institut für Chemie (MPI-C), Mainz, Germany
  • 2German Aerospace Centre (DLR), Remote Sensing Technology Institute, Oberpfaffenhofen, Germany
  • 3European Space Agency (ESA), ESRIN, Frascati, Italy
  • 4Deutscher Wetterdienst (DWD), Offenbach, Germany
  • anow at: Institut für Umweltphysik (IUP), Universität Heidelberg, Heidelberg, Germany

Abstract. We present time series of the global distribution of water vapor columns over more than 2 decades based on measurements from the satellite instruments GOME, SCIAMACHY, and GOME-2 in the red spectral range. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. Potentially systematic effects due to differences in ground pixel size are avoided by merging SCIAMACHY and GOME-2 observations to GOME spatial resolution, which also allows for a consistent treatment of cloud effects. In addition, the GOME-2 swath is reduced to that of GOME and SCIAMACHY to have consistent viewing geometries.

Remaining systematic differences between the different sensors are investigated during overlap periods and are corrected for in the homogenized time series. The resulting Climate product v2.2 (https://doi.org/10.1594/WDCC/GOME-EVL_water_vapor_clim_v2.2) allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.

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We present time series of the global distribution of water vapor over more than 2 decades based on satellite measurements from different sensors. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. The resulting Climate product allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.
We present time series of the global distribution of water vapor over more than 2 decades based...
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