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ABSTRACT: Daily precipitation data from 162 stations in the Czech Republic over 1961–2012 are used to examine changes in seasonal precipitation indices, their spatial patterns and links to temperature and atmospheric circulation. The results show a divide between the western and eastern parts of the country as to trends in most precipitation characteristics in both winter and summer. Increases were more pronounced in the west, where Atlantic influences are stronger. In the eastern region, where continental and Mediterranean influences become more important, the trends are often inconclusive. Aggregated over the country as a whole, positive trends of mean precipitation as well as indices of precipitation intensity and extremes dominate in both winter and summer, and the mean precipitation trends are significant at a much larger percentage of stations than previously reported for 1961–2005. Spring is the only season with prevailing negative trends in mean precipitation and the number of wet days. The trends are least conclusive and close to zero in autumn. The trends differ for cold days (below the seasonal 25th percentile of daily maximum temperature) and warm days (above the seasonal 75th percentile). In contrast to overall winter trends, negative trends of mean precipitation, seasonal maxima and number of wet days prevail on cold days in winter. In summer, by far the most pronounced positive trends occur during warm days, when most precipitation comes from convective storms. Longitudinal dependency was found for most indices in winter and for mean precipitation and the number of wet days in summer. The different influence of the North Atlantic Oscillation on precipitation in the western and eastern parts of the Czech Republic together with positive (negative) trend of the North Atlantic Oscillation index in winter (summer) may contribute to the longitudinal dependency of the precipitation trends. [ABSTRACT FROM AUTHOR]

ABSTRACT There is growing evidence that the hydrological cycle is affected by climate change. Many studies have dealt with evaluation of precipitation characteristics in regional climate models ( RCMs) and their projected changes. However, little attention has been given to possible differences between scenarios of convective and stratiform precipitation and changes in their proportions on total amounts, although climate models simulate convective (subgrid) and stratiform (large-scale) precipitation separately through deep (precipitating) convection and large-scale precipitation parameterizations. In this study, we analyse outputs of four RCMs ( CCLM, HIRHAM, RACMO2, and RCA4) from the EURO-CORDEX project. The RCM simulations for 1989-2008 driven by ERA-Interim reanalysis with two horizontal resolutions (0.44° and 0.11°) are evaluated against observed data in Central Europe, and projected changes of precipitation characteristics (2071-2100 vs 1971-2000) simulated by the RCMs with 0.11° horizontal resolution driven by the EC-EARTH global climate model are then examined. We find that mean convective and large-scale precipitation amounts tend to increase in all seasons except summer when large-scale precipitation amounts decrease. Extreme precipitation is projected to increase in the late 21st century time slice for both convective and large-scale precipitation. The changes of precipitation characteristics are more pronounced in simulations driven by the RCP8.5 scenario, with a larger increase of temperature, and these changes are larger for precipitation with higher intensity. Increasing proportion of convective precipitation in summer and generally increasing intensity of precipitation may have important consequences, e.g. for soil erosion, replenishment of soil moisture, and occurrence of flash floods and droughts. [ABSTRACT FROM AUTHOR]

Self-organizing maps (SOMs) have recently become one of the most popular methods in synoptic climatology. Owing to its ability to organize circulation types (CTs) into an array in which similar CTs tend to lie close to each other, it was suggested that the leading two modes of circulation variability should project on main diagonals of the array with opposite phases in opposite corners. Based on this concept—never properly tested—, researchers have attempted to directly explain SOM CTs as modes and changes in the CTs as a result of changes in these modes. Our work is based on artificial datasets generated with three predefined modes with predefined ratios of explained variance, which are used to generate SOMs of various settings (including the selection of seed points and array size). The results show that each phase of the leading mode tends to project "well" (that is, with correlation of 0.95 or more) on at least one CT regardless the SOM size, except for cases in which all three modes explain similar portion of the total variability (which, however, resembles real circulation). The projection of the remaining two modes on the CTs is very sensitive to parameters such as size and shape of SOM array, SOM initialization, the exact ratio of modes' explained variances and even to minor changes in the generation of data. Moreover, only the first mode tends to project on a diagonal, although reliably only if it explains at least half of the total variability and for larger SOMs. In other cases, linear combinations of two modes often project on diagonals instead of one mode, or modes project on SOM lines/columns. Additionally, there does not seem to be a link between the quality of classification (in terms of, e.g., explained variance and pattern correlation ratio) and how modes project onto it, although some solutions with similar CTs in opposite corners are clearly inferior in terms of the topographic error. A similar study is planned that will be based on a real circulation dataset and modes identified by PCA, results of which will also be presented. [ABSTRACT FROM AUTHOR]