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Trends in precipitation measurement and climate model data and their influence on the assessment of urban systems
(2012)
- Rainfall statistics are composed based on data gained by precipitation measurements and from climate models. These statistics are carried out for both periods in the past and the future. When analysing the time series, different trends can be seen in the measured data of the past and the model data for future periods. Influences on the statistically determined precipitation amounts caused by changes can be neglected for past periods. However, significant increases of the statistical precipitation amounts can be observed for the future. Here a pragmatic approach is presented, showing how to consider possible increases in the statistical precipitation amounts – due to the climate change signal – in the dimensioning of water management systems.
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Bias correction of precipitation data from the CLM regional climate model for water management model application
(2012)
- The precipitation data of the Regional Climate Model CLM are used for the water management impact models within the dynaklim networking and research project. For this purpose, it is necessary to apply a bias correction to the CLM precipitation data. First, the bias assessed for varying temporal resolutions and precipitation characteristics is described. Subsequently, a method for the bias correction is introduced. The developed methodology is a modified form of the socalled quantile mapping. The focus lies on the corrections of the dry days and the heavy rainfall events. They are considered separately, deviating from other quantile mapping procedures.
