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 meteorological data describes the air and soil temperatures, net radiation balance, down-welling photosynthetically active radiation, wind speed, wind direction and the vapour pressure deficit. Data collection was carried out at Cartmel Sands marsh from the 31st of May 2013 till the 26th of January 2015. The Cartmel Sands site is in Morecambe, North West England, and the meteorological tower was situated in the middle of the marsh. This data was collected as part of Coastal Biodiversity and Ecosystem Service Sustainability (CBESS): NE/J015644/1. The project was funded with support from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. BESS is a six-year programme (2011-2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme. Full details about this dataset can be found at https://doi.org/10.5285/b1e2fb9c-8c34-490a-b6ae-2fdf6b460726

1km and 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. (1993). SPI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn 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 1961 to 2012. Full details about this dataset can be found at https://doi.org/10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0

[THIS DATASET HAS BEEN WITHDRAWN]. 1km resolution gridded potential evapotranspiration over Great Britain for the years 1961-2012. This dataset contains time series of two potential evapotranspiration variables. The first is potential evapotranspiration (PET) (mm/day) calculated using the Penman-Monteith equation [1] for FAO-defined well-watered grass [2]. The second is potential evapotranspiration with interception correction (PETI) (mm/day), which adds a correction for interception by a well-watered grass on days in which there is rainfall. Both PET and PETI are calculated using the Climate Hydrology and Ecology research Support System meteorology dataset (CHESS-met) meteorological variables [3]. [1] Monteith, J. L.: Evaporation and environment, in: 19th Symposia of the Society for Experimental Biology, University Press, Cambridge, 1965 [2] Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration - Guidelines for computing crop water requirements, Food and Agriculture Organization of the United Nations, Rome, Italy, FAO Irrigation and Drainage Paper, 1998. [3] Robinson, E. L., Blyth, E., Clark, D. B., Finch, J., Rudd, A. C. (2015). Climate hydrology and ecology research support system meteorological dataset (1961-2012) [CHESS-met] . NERC-Environmental Information Data Centre https://doi.org/10.5285/80887755-1426-4dab-a4a6-250919d5020c Full details about this dataset can be found at https://doi.org/10.5285/d329f4d6-95ba-4134-b77a-a377e0755653

This dataset presents nationally consistent simulations of available precipitation (rainfall + snowmelt) for Great Britain. These include simulations driven by observational data covering January 1961 – December 2018 and simulations driven by Regional Climate Model (RCM) projections covering December 1980 - November 2080. Both are provided as gridded data at 1km resolution. The observed input data was HadUK-Grid 1km daily precipitation and temperature. The RCM input data was a 12-member perturbed parameter ensemble from the UK Climate Projections 2018 (UKCP18), provided at a ‘Regional’ 12km resolution aligned with the GB national grid. A simple snowmelt module was used to transform these time-series of precipitation and temperature into available precipitation. This data was developed for, and used within, the Enhanced Future Flows and Groundwater (eFLaG) project (Hannaford et al., 2022). The eFLaG project was established through a partnership project funded by the Met Office led component of the Strategic Priorities Fund Climate Resilience Programme under contract P107493 (CR19_4 UK Climate Resilience). Full details about this dataset can be found at https://doi.org/10.5285/755e0369-f8db-4550-aabe-3f9c9fbcb93d

Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) groups (Kral et al., 2015; https://doi.org/10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902). SPI is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [1]. SPI is calculated for different accumulation periods: 1, 3, 6, 9, 12, 18, 24 months. Each of these is in turn 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. NOTE: the difference between this dataset with the previously published dataset 'Standardised Precipitation Index time series for IHU Groups (1961-2012) [SPI_IHU_groups]' (Tanguy et al., 2015; https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f), apart from the temporal 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). Within Historic Droughts project (grant number: NE/L01016X/1), the Met Office has digitised historic rainfall and temperature data to produce high quality historic rainfall and temperature grids, which motivated the change in the underlying data to calculate SPI. The methodology to calculate SPI is the same in the two datasets. This release supersedes the previous version, https://doi.org/10.5285/047d914f-2a65-4e9c-b191-09abf57423db, as it addresses localised issues with the source data (Met Office monthly rainfall grids) for the period 1960 to 2000. [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/a01e09b6-4b40-497b-a139-9369858101b3

Standardised Precipitation Evapotranspiration Index (SPEI) data for Integrated Hydrological Units (IHU) Hydrometric Areas (Kral et al. [1]). SPEI is a drought index based on the probability of occurrence of the Climatic Water Balance (CWB) - which is equivalent to the amount of precipitation minus the amount of evapotranspiration - for a given accumulation period as defined by Vicente-Serrano et al. [2]. SPEI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn 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 1961 to 2012. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Hydrometric Areas without Coastline. NERC-Environmental Information Data Centre https://doi.org/10.5285/3a4e94fc-4c68-47eb-a217-adee2a6b02b3 [2] Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010) A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. https://doi.org/10.1175/2009JCLI2909.1 Full details about this dataset can be found at https://doi.org/10.5285/19c230b2-415b-456a-9e93-7b00b730a465

[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 consists in a collection of remotely sensed drought indicators time series. The data was extracted from CEH's gridded remotely sensed drought indicators product (Tanguy et al., 2016; http://doi.org/10.5285/4e0d0e50-2f9c-4647-864d-5c3b30bb5f4b), which has gridded data for Europe for three drought indicators: - the Vegetation Condition Index (VCI) based on satellite product NDVI (Normalised Difference Vegetation Index); - the Temperature Condition Index (TCI) based on remotely sensed LST (Land Surface Temperature); - the Vegetation Health Index (VHI) which is a combination of VCI and TCI. These three drought indicators have been extracted for European NUTS regions (level 0, 1, 2 and 3). These have been masked with a land use land cover map to be able to study different responses for various land cover types. A simplified LULC was created, with only four classes: forest, crop, shrub and grass. One extra time series was created for all classes together. Full details about this dataset can be found at https://doi.org/10.5285/5b3fcf9f-19d4-4ad3-a8bb-0a5ea02c857e

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