Daily rain gauge data over Europe for the period from 1950 to 2009 were used to analyze changes in the duration of wet and dry spells. The duration of wet spells exhibits a statistically significant growth over northern Europe and central European Russia, which is especially pronounced in winter when the mean duration of wet periods increased by 15%–20%. In summer wet spells become shorter over Scandinavia and northern Russia. The duration of dry spells decreases over Scandinavia and southern Europe in both winter and summer. For the discrimination between the roles of a changing number of wet days and of a regrouping of wet and dry days for the duration of the period, the authors suggest a fractional truncated geometric distribution. The changing numbers of wet days cannot explain the long-term variability in the duration of wet and dry periods. The observed changes are mainly due to the regrouping of wet and dry days. The tendencies in duration of wet and dry spells have been analyzed for a number of European areas. Over the Netherlands both wet and dry periods are extended in length during the cold and the warm season. A simultaneous shortening of wet and dry periods is found in southern Scandinavia in summer. Over France and central southern Europe during both winter and summer and over the Scandinavian Atlantic coast in summer, opposite tendencies in the duration of wet and dry spells were identified. Potential mechanisms that might be responsible for the changing durations of wet and dry periods and further perspectives are discussed.

The long-term variability in heavy precipitation characteristics over Europe for the period 1950-2000 is analyzed using high-quality daily records of rain gauge measurements from the European Climate Assessment (ECA) dataset. To improve the accuracy of heavy precipitation estimates, the authors suggest estimating the fractional contribution of very wet days to total precipitation from the probability distribution of daily precipitation than from the raw data, as it is adopted for the widely used R95tot precipitation index. This is feasible under the assumption that daily precipitation follows an analytical distribution like the gamma probability density function (PDF). The extended index R95tt based on the gamma PDF is compared to the classical R95tot index. The authors find that R95tt is more stable, especially when precipitation extremes are estimated from the limited number of wet days of seasonal and monthly time series. When annual daily time series are analyzed, linear trends in R95tt and R95tot are qualitatively consistent; both hint at a growing occurrence of extreme precipitation of up to 3% decade 21 in central western Europe and in south European Russia, with a somewhat more evident trend pattern for the R95tt index. Linear trends estimated for individual seasons, however, exhibit pronounced differences when derived from both indices. In particular, in winter, R95tt clearly reveals an increasing occurrence of extreme precipitation in western European Russia (up to 4% decade 21 ), while during summer, a downward tendency in the fractional contribution of very wet days is found in central western Europe. The new index also allows for a better association of European extreme precipitation with the North Atlantic Oscillation (NAO) index by showing a more consistent spatial correlation pattern and higher correlation levels compared to R95tot.

To analyze the probability density distributions of surface turbulent heat fluxes, the authors apply the twoparametric modified Fisher-Tippett (MFT) distribution to the sensible and latent turbulent heat fluxes recomputed from 6-hourly NCEP-NCAR reanalysis state variables for the period from 1948 to 2008. They derived the mean climatology and seasonal cycle of the location and scale parameters of the MFT distribution. Analysis of the parameters of probability distributions identified the areas where similar surface turbulent fluxes are determined by the very different shape of probability density functions.

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Different data assimilation methods such as an extended Kalman filter, the optimal interpolation method, and a method based on the Fokker-Planck equation applications are considered. Data from the ARGO drifters are assimilated into the HYCOM shallow water model (University of Miami, USA). Through out the study, the schemes and methods of parallel computations with an MPI library are used. The results of the computations with assimilations are compared between themselves and with independent observations. The method based on the Fokker-Planck equation and the extended Kalman filter are preferable because they give better results than the optimal interpolation scheme. The various model characteristics of the ocean, such as the heat content fields and others, are analyzed after the data assimilation.

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