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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 Beirle et al.
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Cited articles  
Andersson, A., Fennig, K., Klepp, C., Bakan, S., Graßl, H., and Schulz, J.: The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS-3, Earth Syst. Sci. Data, 2, 215–234, https://doi.org/10.5194/essd-2-215-2010, 2010.
Andersson, A., Graw, K., Schröder, M., Fennig, K., Liman, J., Bakan, S., Hollmann, R., and Klepp, C.: Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS 4.0, Satellite Application Facility on Climate Monitoring, https://doi.org/10.5676/EUM_SAF_CM/HOAPS/V002, 2017.
Beirle, S., Sihler, H., and Wagner, T.: Linearisation of the effects of spectral shift and stretch in DOAS analysis, Atmos. Meas. Tech., 6, 661–675, https://doi.org/10.5194/amt-6-661-2013, 2013.
Bovensmann, H., Burrows, J., Buchwitz, M., Frerick, J., Noel, S., Rozanov, V., Chance, K., and Goede, A.: SCIAMACHY: Mission objectives and measurement modes, J. Atmos. Sci., 56, 127–150, 1999.
Burrows, J. P., Weber, M., Buchwitz, M., Rozanov, V., Ladstätter-Weißenmayer, A., Richter, A., DeBeek, R., Hoogen, R., Bramstedt, K., Eichmann, K. U., and Eisinger, M.: The global ozone monitoring experiment (GOME): Mission concept and first scientific results, J. Atmos. Sci., 56, 151–175, https://doi.org/10.1175/1520-0469(1999)056<0151:TGOMEG>2.0.CO;2, 1999.
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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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