Managing the impacts of climate change is an important issue for sustainable urban planning. A large range of economic activities influence urban climate and are influenced by climate change itself. The impacts of climate change on power plants, manufacturing processes and business locations as well as adaptation options should be analysed to understand the vulnerability to climate change. The seriousness of the potential impacts of
climate change on enterprises requires new concepts and innovative products for flexible and robust adaptation options. The analysis of the impacts of climate change on enterprises and potential adaptation measures is the basis of the research framework of a “climate-focused economic development” within the networking and research project dynaklim. A differentiated vulnerability assessment enables us to define and identify strategies of adaptation in the means of organisational, marked-focused and technical developments.
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.
Proceeding of the 12th International Conference on Urban Drainage, Porto Alegre/Brazil, 11-16 September 2011.
For the development of adaptation strategies in the research project dynaklim (Dynamic Adaptation of Regional Planning and Development Processes to the Effects of Climate Change in the Emscher-Lippe-Region) numerous models (e. g. sewer models) which need rainfall data as input are used. These models need data with a temporal and spatial resolution beyond the resolution provided by regional climate models. Therefore downscaling of the
precipitation data is performed with the help of weather radar data. Comparisons of measurement and model data during 1961-1990 show systematic bias and differing statistical characteristics between the two data types; thus the model data requires preliminary correction before use. A critical point is the corrections´ impact on extreme event data that are applied in extreme value statistics for structure design, e.g. for retention basins. Different characteristics of the analysed rainfall data and correction procedures are described.