The work presented here is part of the socioeconomic analysis that is carried out within the RADOST project. It has been the starting point of developing a dynamic regionalized Input-Output (IO) model that is used to assess the effects of climate change and adaptation strategies on the regional economy. In a first step the model has been set up for the tourist sector in Mecklenburg-Western Pomerania. The possible developments of the tourism demand – influenced by climate change and other factors – were represented in three scenarios, which in turn were used as input data for the IO model.
Based on concepts for innovation processes and co-production of knowledge, approaches are investigated that address the urgent and complex problems related to climate change, because especially the participation of, and close collaboration with, practice partners is needed. The paper presents the agricultural knowledge management approach in the organic agriculture module of the R&D project INKA BB (Innovation Network for Climate Change Adaptation Brandenburg Berlin) in north-eastern Germany (Knierim et al. 2009). The methodology for the science-practice collaboration follows an action research approach that supports the communication and cooperation of researchers and practitioners. The framework is the action research cycle with iterative stages of planning, action, and reflection. The organic agriculture module, which addresses individual research questions on several farms, is presented as a good practice example for close transdisciplinary network cooperation. The workshop contribution will provide reflections on the innovation development process over two project years.
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%.
Vorstellung von Projektergebnissen aus KLIMZUG-NORD bezüglich jährliche und saisonale Temperatur- und Niederschlagsänderungen zur Mitte und Ende des 21. Jahrhunderts, sowie Ergebnisse aus dem Projekt Hamburg 2K. In Hamburg 2K wird analysiert, was eine Begrenzung auf eine Temperaturänderung von 2K für Hamburg bedeutet. Ausgewertet wurden Temperatur- und Niederschlagsänderungen sowie ausgewählte Indices.
Hinweise für REMO-Datennutzer beinhaltet folgende Punkte: Verfügbarkeit der Daten, Datenformat, Erläuterung zu Variablen, Vergelich mit anderern Daten, Klimaläufe, Häufige Fragen, sowie einen Anhnag mit Gitter- und Produktinformationen und ein Testprogramm in FORTRAN90 zum Einlesen und Herausschreiben der Daten und eine Codeliste
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.
Regional climate change projections show a changing climate in the metropolitan region of Hamburg for the end of the century: The temperature could increase and the precipitation in summer could decrease. To cope with the probably longer lasting and hotter summer conditions in Europe there are different possible adaptation measures in land management practice, e.g. forest conversion. That means the conversion of mostly coniferous forest monocultures to deciduous and mixed forests. Mixed forests are generally more adaptable in comparison to conifer forests. They ensure an increased groundwater recharge because of less canopy interception and reduced transpiration outside the growing season. An interesting question is how forest conversion would feedback to the regional climate under different climate conditions. To explore climate feedbacks, REMO (regional climate model at the Max Planck Institute for Meteorology, Hamburg) is applied. To get a more realistic representation of the land surface, a current dataset from a digital basis landscape model of the Federal Agency for Cartography and Geodesy is used instead of the standard representation of the land surface in REMO. In some areas of the metropolitan region of Hamburg the updated land surface increases the forest fraction. Additionally, all coniferous forest types are converted into broadleaf forest types to study the maximum impact on the simulated near surface climate. This set-up is used for a climate simulation with REMO, forced by ERA-INTERIM reanalysis data for the period of 1990-2008. Selected climate variables are analyzed and the associated processes are investigated: The different forest distributions affect particularly the evapotranspiration and thus the water- and energy cycle of the soil and the lower atmosphere. Especially, the effects in the very hot and dry year 2003 and in the wet year 2002 are analyzed. To study the impacts of the forest distributions under different climate conditions, a second climate simulation is set up with REMO, forced by ECHAM5-MPIOM for the historical period 1970-2000 and for the future time periods 2035-2065 and 2070-2100 under A1B emissions. This allows analyzing the impact of a changed forest cover under different climate conditions. It gives a first estimation of climate sensitivity.