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The main objective of this dissertation is to provide a novel approach to downscaling of outputs from regional climate models and to simulation of future climate. The resulting method consists of rain generator that operates in 6-hour time step. The generator performs well for the observational data. It consists of following steps: disaggregation of 6-hour cumulative precipitation into convective and stratiform types, fitting of first order 3-state discrete time Markov chain to the data and simulation of long time series of precipitation. Then the mixture of log-normal and Generalized Pareto distribution is fitted to stratiform events and the Generalized extreme value distribution is fitted to convective events. The impact of climate change on precipitation is evaluated by using change factors that are identified for precipitation occurrence (by comparing the transition matrices for the future and control period) and for precipitation amount (by comparing the scale and location parameters of distributions fitted for the future and control period). The observational data are then altered with obtained change factors. From evaluation of observational data it stems that the average volume of an convective event is higher for the western region than for eastern region of the Czech Republic. Additionally, statistically significant trends in number and volume of convective events were identified for the region. The relative portion of convective precipitation is the highest in summer for observational data. From analysis of RCMs simulations, it stems that even though the overall precipitation is projected to be lower in future, the proportion of convective events (versus stratiform ones) would be higher. The number of convective events is projected to be lower in the future, while the volume of a convective event to be bigger. |
