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This dataset provides global annual average atmospheric CO2 concentration for the timeframe 1901-2115 for an emissions scenario leading to 1.5K of global warming around the year 2100. This file can be used with all climate models from the PanClim dataset.

This dataset provides global annual average atmospheric CO2 concentration for the timeframe 1901-2115 for an emissions scenario leading to 2.5K of global warming around the year 2100. This file can be used with all climate models from the PanClim dataset.

This dataset provides global annual average atmospheric CO2 concentration for the timeframe 1901-2115 for an emissions scenario leading to 3.5K of global warming around the year 2100. This file can be used with all climate models from the PanClim dataset.

This dataset provides global annual average atmospheric CO2 concentration for the timeframe 1901-2115 for an emissions scenario leading to 4.5K of global warming around the year 2100. This file can be used with all climate models from the PanClim dataset.

This dataset provides fields of monthly total cloud fraction for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 1.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly mean air temperature for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 1.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly total cloud fraction for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 2.0K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly mean air temperature for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 2.0K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly total cloud fraction for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 2.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly mean air temperature for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 2.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly total cloud fraction for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 3.0K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly mean air temperature for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 3.0K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of monthly total cloud fraction for the timeframe 2010-2115 for the climate model CCSM3 and for an emissions scenario leading to 3.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CCSM3 and for an emissions scenario leading to 1.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CCSM3 and for an emissions scenario leading to 2.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CCSM3 and for an emissions scenario leading to 3.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CCSM3 and for an emissions scenario leading to 4.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CGCM3.1(T47) and for an emissions scenario leading to 1.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CGCM3.1(T47) and for an emissions scenario leading to 2.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CGCM3.1(T47) and for an emissions scenario leading to 3.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CGCM3.1(T47) and for an emissions scenario leading to 4.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CNRM-CM3 and for an emissions scenario leading to 1.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CNRM-CM3 and for an emissions scenario leading to 2.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CNRM-CM3 and for an emissions scenario leading to 3.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CNRM-CM3 and for an emissions scenario leading to 4.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

This dataset provides fields of an indicator of ecosystem shifts in natural vegetation (Gamma metric) around the year 2100 for the climate model CSIRO-Mk3.0 and for an emissions scenario leading to 1.5K of global warming around the year 2100. The spatial resolution is 0.5 by 0.5 degrees. The Gamma metric measures the difference between the ecosystem state in 2100 and the present-day state in terms of biogeochemistry and vegetation structure. More details available in Ostberg et al., 2013.

Scripts, source code and executables used to produce the results for one of the applications of the PanClim dataset: "Critical impacts of global warming on land ecosystems" by S. Ostberg, W. Lucht, S. Schaphoff, and D. Gerten. The full paper can be accessed at the Earth System Dynamics website.