STATME · Stability of the atmosphere over Europe

Final Activity Report Summary - STATME (Stability of the atmosphere over Europe)

The STATME project was devoted to the analysis of atmospheric instability. It also focussed on features and events which were related to it, such as precipitable water content in the atmosphere, storminess and extreme weather events, such as heavy precipitation events, prolonged droughts and strong wind events. Strong emphasis was put on achieving new knowledge and training in advanced methodologies, such as statistical and dynamical downscaling, multivariate data analysis and management of datasets from climate model outputs. The project was conducted by the Department of Meteorology and Climatology at University of Lodz in Poland, coordinated by Dr Joanna Wibig, with two partners, namely the Institute for Coastal Research at GKSS Forschungszentrum at Geesthacht in Germany, with Prof. Hans von Storch, and the Department of Physical Geography and Ecosystems Analysis at Lund University in Sweden, with Dr Lars Bärring. The instability conditions in Europe were analysed on the basis of selected indices, e.g. vertical total, total total, K indices and convective available potential energy (CAPE). These indices were calculated on the basis of radiosounding data, different reanalysis and regional climate model outputs. It was shown that there were opposite trends in instability conditions in Europe and differences among tendencies were displayed by different indices. The upward trends were shown more often by indices based mainly on temperature lapse rate. The indices relying on humidity represented more often decreasing tendencies. This clashed with the general opinion that there was clear evidence that in warmer world the water cycle in the atmosphere should be more dynamic. It was also shown that the CAPE was not well represented in all analysed models. Moreover, the amount of water vapour in the atmosphere, described by precipitable water, was analysed. Warmer air could hold greater amounts of water, so the precipitation events could be stronger. The analysis of trends of precipitable water over Europe demonstrated opposite tendencies in different areas. In cooperation with Dr Igor Zveriaev we also analysed how the amount of precipitable water was related to atmospheric circulation, especially with the north Atlantic oscillation (NAO) and the east Atlantic pattern. Prolonged droughts were analysed together with Dr Gintautas Stankunavicius. Those were compared with indices describing the intensity of blocking events in central Europe. On that basis we tried to relate the intensity of droughts with the frequency and strength of blocking events. More dynamic atmosphere could manifest in stronger and more frequent storms. We explored the information in the earliest part of Lund and Stockholm records and used both well-established storminess indices and devise four novel storminess indices. We observed pronounced interdecadal variability in cyclonic activity but no significant overall consistent long-term trend. The major interdecadal scale variability common to all indices was in good agreement with geostrophic wind reconstructions for northeast Atlantic and northwest Europe, as well as with variations in the NAO. This work was performed by Dr Krzysztof Fortuniak and Lars Bärring. Together with Dr Subba Reddy from India we looked on new global datasets of water vapour content in the atmosphere and we analysed the global variation of water vapour using COSMIC, Aqua, National Centres for Environmental Prediction (NCEP) and European Centre for medium range weather forecasts (ECMWF) data sets. With Dr Hari Prasad Dasari and Matteo Zampieri we managed to activate and adapt the regional climate model WRF to Polish conditions. Together with Dr Anthony Kettle we looked on the impacts of NAO on ocean primary productivity, e.g. the way in which it could lead to the collapse of European eel recruitment. Finally, the summer school in statistical downscaling was organised in June 2007. The school demonstrated the overall aims of downscaling and presented the review of different methods of statistical downscaling, such as canonical correlation analysis, neural networks, multiple regression analysis, analog methods, downscaling probability density functions (PDFs) and weather generator.

Data: CORDIS, © European Union