UBR has developed the retrieval of water vapour profiles from SCIAMACHY limb measurements and has provided a data record of version 3 data covering 2003 to 2007. This data version has been validated against frost point hygrometer measurements, and MIPAS and MLS satellite data. KIT has continued the MIPAS water vapour record to present and has validated the satellite water vapour data (Stiller et al., 2011). MIPAS water vapour above 12 km is well within 10%, often within 5%, of other measurements, and compares very well with frost point hygrometer measurements, in particular in the hygropause region. We have merged the HALOE and MIPAS data record to a homogeneous time series and have started to analyse this global 20-year data record regarding seasonal and semi-annual variations, QBO impact, and decadal trends. A first step was the comparison to the re-analysed Boulder data record (Hurst et al., 2011). The analysis of the tape recorder signal in HDO and δD as found in MIPAS data indicated that freeze-drying during uplift of water vapour in the tropics is the dominant process. However, a small but significant deviation of the slope of the HDO-to-H2O ratio from that expected from pure Rayleigh fractionation hints towards the presence of other processes like lofting of ice particles into the stratosphere (Steinwagner et al., 2010). Uplift of water vapour in the Indian monsoon anticyclone as seen in MIPAS data and its representation by CCMs has been studied within the FUB activities (Kunze et al. 2010). MPI-C compared various approaches to model convection within EMAC with MIPAS observational data and found that the currently used approach produces the most realistic results. MPI-M investigated the impact of the model configuration on the atmospheric tape recorder signal derived from water vapor concentrations in the tropical stratosphere, and performed, for this purpose, time-slice simulations for preindustrial (SEN0), present and future (both SEN1) climate states with the ECHAM6 GCM. They found that the amplitude of the seasonal water vapour variability is increasing from the preindustrial to the future climate state, and the trend pattern of the water vapour tape recorder is steeper than the tape recorder pattern itself, i.e. an increase in upward propagation speed of water vapour anomalies is predicted for the future in all model configurations.

In general, all work took longer than estimated in the beginning. MIPAS retrievals of HDO from the second mission phase (2005 to present) could not yet be performed. The retrieval of UTLS water vapour from SCIAMACHY limb data turned out to be more complicated and time-consuming than expected, so that no additional analysis with SCIAMACHY data could be performed so far; this refers to WP 3.2.4 of the Phase-I proposal. All other work packages as described in the proposal of the first phase of SHARP-WV have been tackled, but most of them not yet with sufficient depth. In particular, the analysis of the merged MIPAS-HALOE data set has just begun. Regarding the analysis of CCMs using the same methods as for observational data, only the Asian monsoon system has been analysed, while the tropics, the other monsoon systems, and the extratropics are still to be analysed. More progress than expect has been achieved regarding the analysis of the HDO distributions. The tape recorder signal in δD led to a publication in Nature Geoscience. The analysis of the natural variability of water vapour for different model configurations and for observational data will be started in January 2012. The new budgeting tool for stratospheric water vapour and the analysis of different convections schemes in EMAC have been done. The development of an EMAC version including HDO has started in December 2010 only, due to the change of Patrick Jöckel from MPI-C to DLR. While the KIT part of SHARP-WV will be continued until October 2012 due to late personnel acquaintance, DLR will continue Phase I until December 2013. In the remaining months KIT will intensify the analysis of CCM simulations parallel to the analysis of the merged HALOE-MIPAS data set, while DLR will continue with the development of EMAC-HDO.