The SPARC water vapour assessment II: Profile-to-profile comparisons of stratospheric and lower mesospheric water vapour data sets obtained from satellites

Abstract

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 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 hPa and 5 hPa. Typically, they range from 0.25 ppmv 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 are overall increasing with altitude but this general behaviour is accompanied by considerable variations. Characteristic values vary between 0.3 ppmv 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 hPa to 10 hPa. Histograms considering results from all altitudes indicate the largest occurrence for drifts between 0.05 ppmv decade−1 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. Like 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 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.

Validation of SAGE III/ISS Solar Water Vapor Data With Correlative Satellite and Balloon‐Borne Measurements

“…Over this range, the estimated accuracy (precision) for water vapor ranges from 4% to 19% (4%–15%, Livesey et al., 2020), based on both retrieval characterization and validation with independent measurements (Hurst et al., 2014; Lambert et al., 2007; Read et al., 2007; Vomel, Barnes, et al., 2007; Vömel, David, & Smith, 2007). The MLS data are broadly in agreement with correlative satellite data sets at this level, as addressed by the recent second SPARC data initiative and water vapor assessment (WAVAS‐II) activities (Hegglin et al., 2013; Khosrawi et al., 2018; Lossow et al., 2019). MLS data are screened according to the recommendations in the Aura MLS version 4.2 data quality document (Livesey et al., 2020).…”

“…Validation efforts for ACE‐FTS v3.5 data have demonstrated that the water vapor product has good stability and mean bias within 10% (17–70 km) in comparison to the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and Aura MLS measurements (Sheese et al., 2017). The assessment of ACE‐FTS data in WAVAS‐II also corroborates these results (Khosrawi et al., 2018; Lossow et al., 2019).…”

“…1984. This collection of satellite SWV measurements, which is described comprehensively by the second Stratosphere-troposphere Processes And their Role in Climate (SPARC) water vapor assessment (WAVAS-II, Lossow et al, 2019), includes both the SAGE II instrument (1984( -2005( , Damadeo et al, 2013, as well as the SAGE III instrument that flew aboard the METEOR-3M satellite (SAGE III/M3M, 2002-2005, Thomason et al, 2010.…”

Far‐Ranging Impact of Mountain Waves Excited Over Greenland on Stratospheric Dehydration and Rehydration

“…(2002) also reported some cases when the dehydrated air was observed downwind from mountain wave‐induced polar stratospheric clouds (PSCs). Since ILAS, different satellite sensors allowed a continuous monitoring of the stratospheric water vapor distribution (Khosrawi et al., 2018; Lossow et al., 2019). Especially, the remote‐sensing observations by the Microwave Limb Sounder (MLS) onboard of the Upper Atmosphere Research Satellite (UARS) and the Earth Observing System (EOS) on Aura (e.g., Herman et al., 2002; Nedoluha et al., 2002) have been used to document Arctic dehydration.…”

Technical note: Reanalysis of Aura MLS Chemical Observations

“…The MIPAS ozone product was thoroughly investigated within the European Space Agency's Climate Change Initiative (Laeng et al, 2014). The MIPAS water vapour product has been validated within the framework of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) Water Vapor Assessment activity (Lossow et al, 2017(Lossow et al, , 2018. A high bias in the lower part of MIPAS N 2 O retrievals is discussed and partly remedied by Plieninger et al (2015).…”