The SPARC water vapour assessment II: profile-to-profile comparisons of stratospheric and lower mesospheric water vapour data sets obtained from satellites
Authors: Lossow Stefan , Khosrawi Farahnaz , Kiefer Michael , Walker Kaley A. , Bertaux Jean-Loup , Blanot Laurent , Russell James M. , Remsberg Ellis E. , Gille John C. , Sugita Takafumi , Sioris Christopher E. , Dinelli Bianca M. , Papandrea Enzo , Raspollini Piera , García-Comas Maya , Stiller Gabriele P. , von Clarmann Thomas , Dudhia Anu , Read William G. , Nedoluha Gerald E. , Damadeo Robert P. , Zawodny Joseph M. , Weigel Katja , Rozanov Alexei , Azam Faiza , Bramstedt Klaus , Noël Stefan , Burrows John P. , Sagawa Hideo , Kasai Yasuko , Urban Joachim , Eriksson Patrick , Murtagh Donal P. , Hervig Mark E. , Högberg Charlotta , Hurst Dale F. , Rosenlof Karen H. 
Published: May 2019

Abstract. Within the framework of the second SPARC (Stratosphere-troposphere Processes
And their Role in Climate) water vapour assessment (WAVAS-II),
profile-to-profile comparisons of stratospheric and lower mesospheric water
vapour were performed by
considering 33 data sets derived from satellite observations of 15 different
instruments. These comparisons aimed to provide a picture of the typical
biases and drifts in the observational database and to identify
data-set-specific problems. The observational database typically exhibits the
largest biases below 70 hPa, both in absolute and relative terms. The
smallest biases are often found between 50 and 5 hPa. Typically, they
range from 0.25 to 0.5 ppmv (5 % to 10 %) in this altitude
region, based on the 50 % percentile over the different comparison
results. Higher up, the biases increase with altitude overall but this
general behaviour is accompanied by considerable variations. Characteristic
values vary between 0.3 and 1 ppmv (4 % to 20 %). Obvious
data-set-specific bias issues are found for a number of data sets. In our
work we performed a drift analysis for data sets overlapping for a period of
at least 36 months. This assessment shows a wide range of drifts among the
different data sets that are statistically significant at the 2σ
uncertainty level. In general, the smallest drifts are found in the altitude
range between about 30 and 10 hPa. Histograms considering results
from all altitudes indicate the largest occurrence for drifts between 0.05
and 0.3 ppmv decade−1. Comparisons of our drift estimates to
those derived from comparisons of zonal mean time series only exhibit
statistically significant differences in slightly more than 3 % of the
comparisons. Hence, drift estimates from profile-to-profile and zonal mean
time series comparisons are largely interchangeable. As for the biases, a
number of data sets exhibit prominent drift issues. In our analyses we found
that the large number of MIPAS data sets included in the assessment affects
our general results as well as the bias summaries we provide for the
individual data sets. This is because these data sets exhibit a relative
similarity with respect to the remaining data sets, despite the fact that they are based on different
measurement modes and different processors implementing different retrieval
choices. Because of that, we have by default considered an aggregation of the
comparison results obtained from MIPAS data sets. Results without this
aggregation are provided on multiple occasions to characterise the effects
due to the numerous MIPAS data sets. Among other effects, they cause a
reduction of the typical biases in the observational database.