Studies dealing with time horizons more than a few years away must be done with the help of scenarios, describing the general evolution of the main aspects of human society such as demography, economy, and technology. Today, the globalization and interconnections of different communities have strengthened so much that scenarios must be built for the Earth as whole. Also, considering the large impact of humans, the scenarios must encompass not only the societal aspects but also the effects upon the natural systems such as local air, soil and water pollution, or global warming. The qualitative descriptions given by such global scenarios receive some quantification at global and large region scales. However, both the spatial scale and the level of detail available are not enough for performing studies at regional or local level. For practical work, it is therefore necessary to downscale the global scenarios. Within the 2-FUN project, methodologies for downscaling local climate and socio-economic scenarios were developed.
A certain global scenario will also imply a certain climate. The impacts from climate change are very dependent on regional geographical features, climate, and socioeconomic conditions, and impact studies should therefore be performed at the local or at most a regional level. At present, climate scenarios are produced for the entire planet, at a spatial resolution of several hundred kilometres. Therefore, methods are needed to bridge the gap between the large scale of climate scenarios and the fine scale where local impacts happen as a consequence of changed weather conditions. Within the project, a set of methodologies for managing this downscaling of climatic data for future scenarios to a specific site or small region have been developed. The main downscaling approaches are using dynamical models or using statistical methods. Statistical approaches produce data of similar quality to current-day dynamical models, but they are simpler, less demanding on resources, and faster to implement.
Also, general methods for downscaling global socio-economic and technological scenarios to country level and smaller regions, such as a metropolitan area, a river basin, or an administrative region have been developed. The method is an adaptation of the story-and-simulation approach recommended for assembling global or regional scenarios. A set of guidelines for the use of these methods and models are also provided by the aforementioned project.
2-FUN project: Deliverable D1.2 ,Methodologies for downscaling socio-economic, technological, and emission scenarios, as well as meteorological scenario data, to country level and smaller regions. October 2008.