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Descripción
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| The evolution of projected climate patterns associated with climate change will have important impacts on all components of European agricultural systems. These will range from an expansion of areas suitable for cultivation of many crops (e.g. maize) in Northern Europe as temperatures increase, to changes in rainfall patterns and more frequent drought episodes in southern Europe. Nevertheless, global climate models (GCMs) are still unable to represent surface heterogeneities at scales below 150-100 km. Because of the small size, complex orography and variety of vegetation types of the Iberian Peninsula, greater resolution is needed for establishing regional impacts and adaptations of cropping and agricultural systems. This can be achieved with high resolution models such as Regional Climate Models (RCMs) for regional climate simulations. Ouputs from GCMs or RCMs have been used as inputs for crop/impact simulation models in various ways in impact/adaptation studies. Uncertainties are introduced all along the simulation chain beginning with the emissions scenarios and continuing through climate models, crop/impact models and up-scaling of the results: in this project, quantification of uncertainties, mapping of areas with maximum and minimum uncertainties will improve the interpretation of impact/adaptation projections. We will establish a methodology for interfacing climate models to crop/impact models, establish a systematic impact/adaptation evaluation, and explore the application of neural networks in the up-scaling process to regional projections. This research will build on our experience in the EU project PRUDENCE: 'Prediction of regional scenarios and uncertainties for defining European climate change risks and effects'. A single realisation of simulated climate (ie the use of one climate model) is insufficient to provide information needed for impact assessment and adaptation strategies because of the uncertainties involved, nor is the use of one single impact model. In this context, ten regional climate models will be linked to various crop/impact models (DSSAT family, CropSyst, evapotranspiration models, phenological models). The RCM simulated climate will provide 30 year-simulations for baseline (1969-1990) and future (2070-2100) climate. Soil data will correspond to 11 locations, with observed soil profiles, as well as averaged soils representative of all agricultural areas. Crop/impact models have been calibrated and validated in previous studies and will be continued here. Autonomous adaptations (changes in crop species, cultivars, sowing dates etc) will be explored as well as long-term adaptations (changes in cropping systems and agricultural systems) for the attention of the Administration and policy makers. A farm-level approach will be incorporated in this part of the project through the use of a bioeconomic model. Finally a tool for Specific Support to Policies will be built to allow decision makers to establish the impact and adaptation range of possibilities that will be distributed on a CD and will made available on the web. | |
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Internacional
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No |
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Tipo de proyecto
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Proyectos y convenios en convocatorias públicas competitivas |
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Entidad financiadora
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CICYT |
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Nacionalidad Entidad
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ESPAÑA |
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Tamaño de la entidad
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Desconocido |
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Fecha concesión
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01/01/2008 |