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Zusammenfassung:
We present a long-term data set of 1° × 1° monthly mean total column water vapour (TCWV) based on global measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020.
In comparison to the retrieval algorithm of Borger et al. (2020) several modifications and filters have been applied accounting for instrumental issues (such as OMI's "row-anomaly") or the inferior quality of solar reference spectra. For instance, to overcome the problems of low quality reference spectra, the daily solar irradiance spectrum is replaced by an annually varying mean Earthshine radiance obtained in December over Antarctica. For the TCWV data set only measurements are taken into account for which the effective cloud fraction < 20 %, the AMF > 0.1, the ground pixel is snow- and ice-free, and the OMI row is not affected by the "row-anomaly" over the complete time range of the data set. The individual TCWV measurements are then gridded to a regular 1° × 1° lattice, from which the monthly means are calculated.
In a comprehensive validation study we demonstrate that the OMI TCWV data set is in good agreement to reference data sets of ERA5, RSS SSM/I, and ESA CCI Water Vapour CDR-2: over ocean ordinary least squares (OLS) as well as orthogonal distance regressions (ODR) indicate slopes close to unity with very small offsets and high correlation coefficients of around 0.98. However, over land, distinctive positive deviations are obtained especially within the tropics with relative deviations of approximately +10 % likely caused by uncertainties in the retrieval input data (surface albedo, cloud information) due to frequent cloud contamination in these regions. Nevertheless, a temporal stability analysis proves that the OMI TCWV data set is consistent with the temporal changes of the reference data sets and shows no significant deviation trends.
Since the TCWV retrieval can be easily applied to further satellite missions, additional TCWV data sets can be created from past missions such as GOME-1 or SCIAMACHY, which under consideration of systematic differences (e.g. due to different observation times) can be combined with the OMI TCWV data set in order to create a data record that would cover a time span from 1995 to the present. Moreover, the TCWV retrieval will also work for all missions dedicated to NO2 in future such as Sentinel-5 on MetOp-SG.
