[THIS DATASET HAS BEEN WITHDRAWN]. 1km resolution gridded meteorological variables over Great Britain for the years 1961-2015. This dataset contains time series of daily mean values of air temperature (K), specific humidity (kg kg-1), wind speed (m s-1), downward longwave radiation (W m-2), downward shortwave radiation (W m-2), precipitation (kg m-2 s-2) and air pressure (Pa), plus daily temperature range (K). These are the variables required to run the JULES land surface model [1] with daily disaggregation. The precipitation data were obtained by scaling the Gridded estimates of daily and monthly areal rainfall (CEH-GEAR) daily rainfall estimates [2,3] to the units required for JULES input. Other variables were interpolated from coarser resolution datasets, taking into account topographic information. [1] Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes, Geoscientific Model Development, 4, 677-699. https://doi.org/10.5194/gmd-4-677-2011, 2011. [2] Tanguy, M.; Dixon, H.; Prosdocimi, I.; Morris, D. G.; Keller, V. D. J. (2016). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2015) [CEH-GEAR]. NERC Environmental Information Data Centre. https://doi.org/10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca [3] Keller,V. D. J., Tanguy, M. , Prosdocimi, I. , Terry, J. A. , Hitt, O., Cole, S. J. , Fry, M., Morris, D. G., Dixon, H. (2015) CEH-GEAR: 1km resolution daily and monthly areal rainfall estimates for the UK for hydrological use. Earth Syst. Sci. Data Discuss., 8, 83-112. https://doi.org/10.5194/essdd-8-83-2015. Full details about this dataset can be found at https://doi.org/10.5285/10874370-bc58-4d23-a118-ea07df8a07f2

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

5km gridded Standardised Precipitation Index (SPI) data for Great Britain, which is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al [1]. There are seven accumulation periods: 1, 3, 6, 9, 12, 18, 24 months and for each period SPI is calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1862 to 2015. This version supersedes previous versions (version 2 and 3) of the same dataset due to minor errors in the data files. NOTE: the difference between this dataset with the previously published dataset "Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]" (Tanguy et al., 2015; https://doi.org/10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0) , apart from the temporal and spatial extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Tanguy et al., 2014; https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e) was used, whereas in this new version, Met Office 5km rainfall grids were used (see supporting information for more details). The methodology to calculate SPI is the same in the two datasets. [1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. Full details about this dataset can be found at https://doi.org/10.5285/233090b2-1d14-4eb9-9f9c-3923ea2350ff

This dataset presents modelled estimates of soil nitrogen concentration (% dry weight soil) at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil nitrogen data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil nitrogen data from 913 locations across Great Britain and is representative of 0-15 cm soil depth. Soil N concentration was determined using a total elemental analyser. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/8ec2d5ae-5d19-4b58-8cf6-aafdad485bb2

This dataset presents modelled estimates of soil invertebrate density (individuals m-2) at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil invertebrate density data from 2007 and including climate, habitat, soil and spatial predictors. The model is based on soil invertebrate density data from 830 locations across Great Britain and is representative of 0-8 cm soil depth. Soil invertebrates were extracted from cores using a dry Tullgren extraction method and enumerated by microscope. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/93207428-aace-4bb5-9073-2eb44ad632d1

[THIS DATASET HAS BEEN WITHDRAWN]. The topographic index is a hydrological quantity describing the propensity of the soil at landscape points to become saturated with water as a result of topographic position (i.e. not accounting for other factors such as climate that also affect soil moisture but are accounted for separately). Modern land surface models require a characterisation of the land surface hydrological regime and this parameter allows the use of the TOPMODEL hydrological model to achieve this .This Geographic Information System layer is intended for use as topographic ancillary files for the TOPMODEL routing model option within the Joint UK Land Environment Simulator (JULES) land surface model. The topographic index variable here is directly comparable to the compound topographic index available from United States Geological Survey's Hydro1K at 30 sec resolution. Full details about this dataset can be found at https://doi.org/10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da

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 presents modelled estimates of soil carbon concentration (g kg-1) at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil carbon data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil carbon data from 2446 locations across Great Britain and is representative of 0-15 cm soil depth. Loss-on-ignition (LOI) was determined by combustion of 10g dry soil at 375 degrees Celsius for 16 hours; carbon concentration was estimated by multiplying LOI by a factor of 0.55. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/3aaa52d3-918a-4f95-b065-32f33e45d4f6

Gridded potential evapotranspiration over Great Britain for the years 1961-2017 at 1 km resolution. This dataset contains two potential evapotranspiration variables: daily total potential evapotranspiration (PET; kg m-2) for a well-watered grass and daily total potential evapotranspiration with interception correction (PETI; kg m-2). The data are provided in gridded netCDF files. There is one file for each variable for each month of the data set. This data set supersedes the previous version as bugs in the calculation of the variables have been fixed (for all years), temporal coverage of both variables has been extended to include the years 2016-2017 and the netCDF metadata has been updated and improved. Full details about this dataset can be found at https://doi.org/10.5285/9116e565-2c0a-455b-9c68-558fdd9179ad

This dataset contains modelled vegetation carbon output from the land surface model JULES, along with the temperature and rainfall outputs (which were originally inputted) at a monthly, 1.5km resolution. There are four different JULES simulations, using two different climate projections (global climate sensitivity of 3.5K and highest global climate sensitivity of 7.1K) under a constant, present day atmospheric CO2 and a CO2 pathway that follows the SRES (Special Report on Emissions Scenarios) A1B scenario. Full details about this dataset can be found at https://doi.org/10.5285/f493ad5c-585c-475d-a374-2f77b5866bc4