These data contain 408 instances of annual model output from JULES/IMOGEN simulations, covering the period between 1850-2100. Each simulation (which corresponds to one netcdf file) provides annual average of carbon stocks of the land, atmosphere and ocean store required to calculate the anthropogenic fossil fuel emissions as the residual of the yearly changes. Also included are the global warming variables, fractional land-cover, natural wetland extent and methane (CH4) flux and the soil temperature and moisture content for additional analysis. The spatial coverage is global with spatial resolution of the data is 2.5 degrees latitude, 3.75 degrees longitude. This dataset is the model output that was used in Comyn-Platt et al (2018) [ Comyn-Platt, E. et al. (2018). Carbon budgets for 1.5 and 2C targets lowered by natural wetland and permafrost feedbacks. Nature Geoscience. https://doi.org/10.1038/s41561-018-0174-9] Full details about this dataset can be found at https://doi.org/10.5285/1cebd79c-02e7-475a-a1da-1f26a963d41e

The dataset contains annual global plant respiration (and related diagnostics, such as Net Primary Productivity, Gross Primary Productivity and soil respiration), applicable for pre-industrial times (taken as year 1860) through to the end of the 21st Century (year 2100). The spatial resolution of the data is 2.5 degrees latitude x 3.75 degrees longitude. These diagnostics are outputs from the Joint UK Land Environment Simulator (JULES land surface model) under four different approaches to calcluate leaf respiration. Each of four sets contains a total of 34 runs, each driven by a different CMIP5 model climate pattern, using the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) system. These are for a "business-as-usual" approach to fossil fuel usage, as the Representative Concentration Pathway scenario RCP8.5. These simulations form the basis for new research paper by Huntingford et al (2017, under review). Full details about this dataset can be found at https://doi.org/10.5285/24489399-5c99-4050-93ee-58ac4b09341a