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  • This dataset is a model output from the JULES land surface model driven with the Watch Forcing Data methodology applied to Era-Interim (WFDEI) data. It provides monthly global methane emissions from natural wetlands on 0.5 x 0.5 degree grid between 1980-2014. It includes the following variables: - fch4_wetl: modelled methane flux from natural wetland, in mg CH4 m-2 day-1 - fwetl: fraction of wetland - cs: soil carbon in each of these four soil carbon pools: decomposable plant material, resistant plant material, microbial biomass and humus), in kg m-2 - t_soil: sub-surface temperature of the four modelled soil layers (0-0.1 m, 0.1-0.35 m, 0.35-1.0 m and 1.0-2.0 m), in K Full details about this dataset can be found at https://doi.org/10.5285/6ce61e91-6912-4fe2-a095-12136af86347

  • 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

  • The dataset contains model output from the land surface model JULES and the econometric agricultural land use model ECO-AG, at kilometre scale resolution over Great Britain for 8 different scenarios using unmitigated climate change. Modelled arable area, net primary productivity, runoff and irrigation demand are provided for scenarios combining and isolating the effects of climate, CO2 and irrigation. The driving climate data used to drive the models is from Regional Climate Model runs performed for the period 1998-2008 and for an 11 year period at 2100 for CO2 levels corresponding to the unmitigated Regional Concentration Pathway RCP8.5. Full details about this dataset can be found at https://doi.org/10.5285/2efac82b-2438-4806-999d-374663210c34

  • 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

  • This dataset includes six sets of model output from JULES/IMOGEN simulations. Each set includes output from JULES (the Joint UK Land Environment Simulator) run with 34 climate change patterns from 2000-2099. The outputs provide carbon stocks and variables related to the surface energy budget to understand the implications of land-based climate mitigation. Full details about this dataset can be found at https://doi.org/10.5285/333eb066-be07-4209-9dfe-2d9d18560de6