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Abstract. The use of multiplicative random cascades (MRCs) for temporal rainfall disaggregation has been extensively studied in the past. MRCs are appealing for rainfall disaggregation due to their formal simplicity and the possibility to extract the model parameters directly from observed high resolution rainfall data. These parameters, however, represent the rainfall characteristics of the observation period. Since rainfall characteristics of different time slices are changing due to climate variability, we propose a parameterization approach for MRCs to adjust the parameters according to past (observed) or future (projected) time series. This is done on the basis of circulation patterns (CPs) by extracting a distinct MRC parameterization from high resolution rainfall data, as observed on days governed by each individual CP. The parameterization approach is tested by comparing the statistical properties of disaggregated rainfall time series of two time slices, 1969-1979 and 1989-1999, to the results obtained by two other disaggregation methods (a conceptually similar MRC without CP-based parameterization and a recombination approach) and to the statistical properties of observed hourly rainfall data. In this context, all three approaches use rainfall data of the time slice 1989-1999 for parameterization. We found that the inclusion of CPs into the parameterization of a MRC yields hourly time series that better reproduce the properties of observed rainfall in time slice [1989][1990][1991][1992][1993][1994][1995][1996][1997][1998][1999], as compared to the simple MRC. Despite similar results of both MRCs in the validation period of 1969-1979, we can conclude that the CP-based parameterization approach is applicable for temporal rainfall disaggregation in time slices distinct from the parameterization period. This approach accounts for changes in rainfall characteristics due to changes in the frequency of occurrence of the CPs and allows generating hourly rainfall from daily data, as often provided by a statistical downscaling of global climate change.

This study focuses on changes in irradiance, temperature, precipitation, evaporation, snow cover, and water balance in Saxony (eastern Germany) over the past 50 yr. It had 2 main objectives: (1) collection of all available climatological data with daily resolution, (2) statistical analysis of the climate. Time series of more than 600 meteorological stations from Saxony and the surrounding regions have been organized in the Saxon climate databank. This databank contains tools for homogeneity tests and trend analysis of climatologic time series. This makes it possible to calculate derived and complex quantities from single climate elements. About half of the time series tested were sufficiently homogeneous for a regional climate analysis of Saxony. The most important results of the trend analysis are: (1) marked decrease in summer rainfall (-10 to -30%); (2) significant increase in winter precipitation; (3) increase in heavy rainfall events during early summer; (4) increase in the length and frequency of dry periods in both vegetation periods; (5) increase in temperature in all seasons, and especially in winter (> 2°C in northern Saxony); (6) increase in irradiance and potential evaporation by about 7% in the last 30 years.

A weather-pattern-based multiple regression model to derive future possible changes in the level of the higher temporal resolution spectrum of heavy precipitation has been developed. The temporal spectrum was described using statistical precipitation amounts as a function of the event's duration (1-24 h) and return period (once in 5 yr to once in 100 yr). The principle of the method consists in projecting a statistical relationship between the parameters of a transformed Gumbel distribution (theoretical extreme value distribution) and the distribution of classes of objective weather patterns to time slices in the near future of climate. Changes in distribution parameters were constructed in the model from changes in the distribution of weather patterns. Possible change signals were calculated for the catchment of the Weißeritz River (Ore Mountains, Germany) for the time slices centred around 2025 (2011-2040) and 2050 (2036-2065) as changes versus the reanalyses of the reference period 1961-2000 (May-September). For the climate conditions to be expected in the near future (IPCC A1B scenario), increases in the amounts of heavy precipitation, i.e. decreases in the return periods of equal amounts of heavy precipitation from the reference period, were obtained for the entire temporal spectrum covered by this paper. Overall, the change signals derived on the basis of a concept of weather patterns seem plausible because they represent a possible continuation of the already observed increase in frequency and intensification of events of heavy precipitation in the extended study area.