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.
“Adaptation to climate change” as a new field of knowledge challenges agricultural and horticultural (vocational) education and extension. Farmers and horticulturists are confronted with vague scientific findings at best. A broad variety of global climate scenarios is “projected” onto regions and exact predictions are usually not possible. Often, personal observations and experiences seem to contradict scientific assertions. Under this condition farmers and policy makers must decide about future land use.
What does this imply for capacity building? How to transform insecurity into concrete educational measures and programs?
The authors discuss their first experiences within a German R&D network (INKA BB) in which they develop capacity building programs. Two examples from urban agriculture / urban gardening will be used as case studies. Strengths and weaknesses of the development processes and their management will be discussed.
Since the topic is complex and adaptation is a continuous activity, learning in connection with climate change adaptation ideally begins on elementary level, continues in higher and vocational training, and does not end with extension. In other words: “learning chains” must be developed which enable life-long learning in formal, non-formal and informal learning environments.
Competencies are needed beyond classical technological and economic skills. Problem solving - from problem perception, analysis, generation of alternative solutions, to implementation and evaluation - with a key competence in critical analysis and reflection of contemporary research findings - gain in importance.
In INKA BB, participation is seen as axiomatic. As a consequence, an action-oriented, participatory approach has been chosen which enables mutual learning among partners from research, formal and informal, elementary, higher and vocational education.
A crucial point is the question of “Who could be the bridge between science and the educational practitioner?” In INKA BB, a specific working group (the subproject on “Knowledge Management and Transfer”) facilitates the development processes and therefore plays a liaison role between theory and practice. In the long-run, sustainable ownership of this process must be achieved. A combination of network building, mutual learning in permanent work groups, provision of technical trainings, and joint planning, testing, monitoring and evaluation is seen as a precondition.
Dies ist ein Poster aus dem REGKLAM-Vorhaben, in dem das Projekt überblicksmäßig vorgestellt wird. Dieses Poster wurde anlässlich des 5. REGKLAM-Regionalforums am 7.10.2013 erstellt.
Dies ist ein Poster aus dem REGKLAM-Vorhaben zum Thema "Projizierte Trockenheitstrends - Bewertung regionaler Trockenheitstrends anhand eines Ensembles globaler und regionaler Klimamodelle".