High-resolution and bias-corrected CMIP5 projections for climate change impact assessments
Copyright policy )High-resolution and bias-corrected CMIP5 projections for climate change impact assessments
AbstractProjections of climate change are available at coarse scales (70–400 km). But agricultural and species models typically require finer scale climate data to model climate change impacts. Here, we present a global database of future climates developed by applying the delta method –a method for climate model bias correction. We performed a technical evaluation of the bias-correction method using a ‘perfect sibling’ framework and show that it reduces climate model bias by 50–70%. The data include monthly maximum and minimum temperatures and monthly total precipitation, and a set of bioclimatic indices, and can be used for assessing impacts of climate change on agriculture and biodiversity. The data are publicly available in the World Data Center for Climate (WDCC; cera-www.dkrz.de), as well as in the CCAFS-Climate data portal (http://ccafs-climate.org). The database has been used up to date in more than 350 studies of ecosystem and agricultural impact assessment.
- CGIAR Consortium France
- CGIAR France
- University of Leeds United Kingdom
- CGIAR France
- International Center for Tropical Agriculture Kenya
Data Descriptor, Scale (ratio), Adaptation to Climate Change in Agriculture, FOS: Political science, Precipitation, Agricultural and Biological Sciences, Climate change, Environmental resource management, Political science, agriculture, Climatology, Species Distribution Modeling and Climate Change Impacts, Geography, Ecology, Ecological Modeling, factors, Life Sciences, Agriculture, Geology, Biodiversity, Computer Science Applications, climate change, Archaeology, Physical Sciences, Statistics, Probability and Uncertainty, Information Systems, Statistics and Probability, Cartography, Physical geography, Impact assessment, Soil Science, precipitation, Library and Information Sciences, Climate model, Environmental science, Education, models, Meteorology, Biology, Ecology, Evolution, Behavior and Systematics, Habitat Suitability, Public administration, food security, FOS: Earth and related environmental sciences, Species Distribution Modeling, FOS: Biological sciences, Environmental Science, Soil Carbon Dynamics and Nutrient Cycling in Ecosystems
Data Descriptor, Scale (ratio), Adaptation to Climate Change in Agriculture, FOS: Political science, Precipitation, Agricultural and Biological Sciences, Climate change, Environmental resource management, Political science, agriculture, Climatology, Species Distribution Modeling and Climate Change Impacts, Geography, Ecology, Ecological Modeling, factors, Life Sciences, Agriculture, Geology, Biodiversity, Computer Science Applications, climate change, Archaeology, Physical Sciences, Statistics, Probability and Uncertainty, Information Systems, Statistics and Probability, Cartography, Physical geography, Impact assessment, Soil Science, precipitation, Library and Information Sciences, Climate model, Environmental science, Education, models, Meteorology, Biology, Ecology, Evolution, Behavior and Systematics, Habitat Suitability, Public administration, food security, FOS: Earth and related environmental sciences, Species Distribution Modeling, FOS: Biological sciences, Environmental Science, Soil Carbon Dynamics and Nutrient Cycling in Ecosystems
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