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 contains information about meteorological conditions, ammonia concentration and deposition rates resulting from an experimental ammonia (NH3) enhancement setup in a Birch forest in Scotland. The experiment is designed for controlled enhancement of ambient NH3 concentration within the study plot under natural field conditions so that effects of NH3 on vegetation can be studied. This will help identify tolerance thresholds of vegetation to NH3 as an air pollutant and determine critical levels that can be incorporated into regional environmental policy. Meteorological measurements were recorded at multiple heights on a meteorological tower. Under suitable wind conditions, NH3 was released towards a vegetation monitoring transect replicating pollution from a point source, and NH3 concentrations in the air were measured using monthly passive samplers. Continuous meteorological data, NH3 release, and NH3 concentration data are provided in 15-minute intervals and this dataset relates to measurements taken in 2023 – 2024. Deposition rates were modelled using a bi-directional resistance model on a monthly timescale based on measured NH3 concentrations in the air, micrometeorology and plant physiology. This dataset provides an extension of the 2022 dataset to enable longer term analysis of NH3 deposition and its effects in a tropical forest. The work was supported by UKRI GCRF South Asian Nitrogen Hub (Grant NE/S009019/1) and UKCEH National Capability for UK Challenges Programme NE/Y006208/1. Full details about this dataset can be found at https://doi.org/10.5285/89b48766-ab8d-40f9-b9f1-f50df6af131f

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

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

[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

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 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 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 HAS BEEN WITHDRAWN]. 1km resolution gridded meteorological variables over Great Britain for the years 1961-2012. 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-1) 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, doi:10.5194/gmd-4-677-2011, 2011. [2] Tanguy, M., Dixon, H., Prosdocimi, I., Morris, D. G., Keller, V. D. J. (2014). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2012) [CEH-GEAR]. NERC-Environmental Information Data Centre doi:10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e [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, www.earth-syst-sci-data-discuss.net/8/83/2015/ doi:10.5194/essdd-8-83-2015. Full details about this dataset can be found at https://doi.org/10.5285/80887755-1426-4dab-a4a6-250919d5020c

[THIS DATASET HAS BEEN WITHDRAWN]. 1 km gridded estimates of daily and monthly rainfall for Great-Britain and Northern Ireland (together with approximately 3000 km2 of catchment in the Republic of Ireland) from 1890 to 2015. The rainfall estimates are derived from the Met Office national database of observed precipitation. To derive the estimates, monthly and daily (when complete month available) precipitation totals from the UK rain gauge network are used. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly estimates. The estimated rainfall on a given day refers to the rainfall amount precipitated in 24 hours between 9am on that day until 9am on the following day. The CEH-GEAR dataset has been developed according to the guidance provided in BS 7843-4:2012. Full details about this dataset can be found at https://doi.org/10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca