A statistical downscaling method has been developed to produce highly resolved precipitation data from regional climate model (RCM) output, using the model CLM (2 runs, scenario A1B). The procedure is based on the analogue method with the predictors precipitation (daily sums on CLM grid points) and objective weather types (DWD). Analogue days of the time period 2001-2009 are searched using corrected and adjusted data of radar Essen and DWD measurements of objective weather types. The radar data is used to produce high-resolution precipitation data sets (1km², 5min) with realistic spatial and temporal correlations for three catchments in North Rhine-Westphalia. Results in
the reference period (1961 - 1990) are examined using extreme value statistics and compared to corrected station data. Data sets of the near and the far future (2021-2050, 2071-2100) are analysed with respect to future trends, and uncertainties of the downscaling procedure are discussed.
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.
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.
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.
Dies ist ein Poster aus dem REGKLAM-Vorhaben, welches das Teilprojekt 3.2.1 mit dem Thema "Wasserhaushalt im Einzugsgebiet von Talsperren - Modellierung des Stofhaushaltes unter veränderten klimatischen Randbedingungen" vorstellt.
Consequences resulting from future Climate Change may be one of the most severe threats for people and economies in many countries of the world. Besides the problem of sea level rise, also possible general changes in the frequency and intensity of storms as well as general changes in the average wind field are expected for the future. With respect to the coastal protection possible future strategies and also possible future measures are analyzed and assessed with the result that technical, morphological, socio-economic and aesthetical aspects play a role.
Information about possible changes of extreme wave heights are essential for the future safe design of coastal and flood protection structures likes dykes, flood protection dunes, revetments etc. In this study, scenarios of regional climate change up to 2100 are used for the evaluation of changes of wave conditions. Analyses on calculated significant wave heights derived from extreme value statistics are showing a different signal of change for the selected locations along the German Baltic Sea Coast. The results are showing that extreme wave heights with a return level of 200 years can increase up to +14%. But also a decrease of down to -14% were found compared to actual conditions, depending on the location and climate change scenario applied. At the location of Warnemünde a slight increasing trend for the change of extreme wave heights could be found for 3 of 4 scenario runs with a maximum increase of +7%.
Statistical downscaling of CLM precipitation using adjusted radar data and objective weather types
(2012)
