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Total column water vapour retrieval from S-5P/TROPOMI in the visible blue spectral range

Abstract. Total column water vapour has been retrieved from TROPOMI measurements
in the visible blue spectral range and compared to a variety of different
reference data sets for clear-sky conditions during boreal summer and
winter. The retrieval consists of the common two-step DOAS approach:
first the spectral analysis is performed within a linearized scheme
and then the retrieved slant column densities are converted to vertical
columns using an iterative scheme for the water vapour a priori profile
shape, which is based on an empirical parameterization of the water
vapour scale height. Moreover, a modified albedo map was used
combining the OMI LER albedo and scaled MODIS albedo map. The use of
the alternative albedo is especially important over regions with very
low albedo and high probability of clouds like the Amazon region. The errors of the total column water vapour (TCWV) retrieval have been theoretically estimated considering the contribution of a variety of different uncertainty
sources. For observations during clear-sky conditions, over ocean surface, and at low solar zenith angles the error typically is around values of 10 %–20 %, and during cloudy-sky conditions, over land surface, and
at high solar zenith angles it reaches values around 20 %–50 %. In the framework of a validation study the retrieval demonstrates
that it can well capture the global water vapour distribution:
the retrieved H2O vertical column
densities (VCDs) show very good agreement with the reference data sets over ocean for boreal summer and winter whereby the modified albedo map substantially improves the retrieval's consistency to the
reference data sets, in particular over tropical land masses. However, over land the retrieval underestimates the VCD by about 10 %, particularly
during summertime. Our investigations show that this underestimation
is likely caused by uncertainties within the surface albedo and
the cloud input data: low-level clouds cause an underestimation, but for mid- to high-level clouds good agreement is found.
In addition, our investigations indicate that these
biases can probably be further reduced by the use of improved
cloud input data. For the general purpose we recommend only using VCDs with cloud fraction <20 % and AMF >0.1, which
represents a good compromise between spatial coverage and
retrieval accuracy. The TCWV retrieval can be easily applied to further satellite
sensors (e.g. GOME-2 or OMI) for creating uniform, long-term measurement data sets, which is particularly interesting for climate and trend studies
of water vapour.
