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Meteorological geographical features

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  • [This dataset is embargoed until November 17, 2025]. This dataset provides daily estimates at locations that are part of the COSMOS-UK monitoring network for meteorological and potential evapotranspiration variables in the Climate hydrology and ecology research support system for the period 2013-2017 (CHESS-met and CHESS-PE). Additionally, for the same period, it provides estimates at COSMOS-UK sites locations for soil moisture simulations provided by JULES (Joint UK Land Environment Simulator) at four layers: top layer (0.0-0.1 m depth), second layer (0.1-0.35 m depth), third layer (0.35-1 m depth) and bottom layer (1-3 m depth). The following variables are available in the dataset: daily temperature range (K), specific humidity (kg kg-1), precipitation (kg m-2 s-1), air pressure (Pa), downward longwave radiation (W m-2), downward shortwave radiation (W m-2), wind speed (m s-1), potential evapotranspiration (mm day-1) and potential evapotranspiration with interception correction (mm day-1), soil moisture content of 1-top layer (m depth), soil moisture content of 2-second layer (m depth), soil moisture content of 3-third layer (m depth) and soil moisture content of 4-bottom layer (m depth). Full details about this dataset can be found at https://doi.org/10.5285/2bc23a5a-3a47-44da-80f6-ced6ae4ac45f

  • 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

  • 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 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 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 contains information about meteorological conditions and ammonia concentration and deposition rates resulting from an experimental setup. An NH3 enhancement experiment along with a full suite of multi-height meteorological measurements was established in a Birch woodland near Edinburgh, UK. Under suitable wind conditions measured at the meteorological tower, NH3 is released towards a monitoring transect. Along the downwind monitoring transect, NH3 concentrations in the air are measured using monthly passive samplers. Deposition rates are modelled using a bi-directional resistance model based on measured NH3 concentrations in the air, micrometeorology and plant physiology. Additionally, NH3 concentrations were measured at high temporal resolution at a fixed downwind distance from the source to achieve the target enhancement concentrations. The work was supported by UKRI GCRF South Asian Nitrogen Hub (Grant NE/S009019/1) and NERC (Grant NE/R016429/1). Full details about this dataset can be found at https://doi.org/10.5285/e30ca77b-9118-4279-8b3a-a4c7773d1c43

  • [THIS DATASET HAS BEEN WITHDRAWN]. 1km resolution gridded potential evapotranspiration over Great Britain for the years 1961-2015. 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. (2016). Climate hydrology and ecology research support system meteorological dataset (1961-2015) [CHESS-met] . NERC-Environmental Information Data Centre https://doi.org/10.5285/10874370-bc58-4d23-a118-ea07df8a07f2 Full details about this dataset can be found at https://doi.org/10.5285/8baf805d-39ce-4dac-b224-c926ada353b7

  • 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

  • Standardised Precipitation Evapotranspiration Index (SPEI) data for Integrated Hydrological Units (IHU) groups (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 general logistic 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: Groups. NERC-Environmental Information Data Centre https://doi.org/10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902 [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 to 1718. https://doi.org/10.1175/2009JCLI2909.1 Full details about this dataset can be found at https://doi.org/10.5285/9b550cc5-4cba-45fb-ab92-8408454fa1d4

  • [THIS DATASET HAS BEEN WITHDRAWN]. Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) groups (Kral et al. [1]). SPI is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [2]. 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 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 [3]), apart from the temporal extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Keller et al., 2015 [4], Tanguy et al., 2014 [5]) 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. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Groups. NERC-Environmental Information Data Centre doi:10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902 [2] 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. [3] Tanguy, M.; Kral., F.; Fry, M.; Svensson, C.; Hannaford, J. (2015). Standardised Precipitation Index time series for Integrated Hydrological Units Groups (1961-2012). NERC Environmental Information Data Centre. https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f [4] Keller, V. D. J., Tanguy, M., Prosdocimi, I., Terry, J. A., Hitt, O., Cole, S. J., Fry, M., Morris, D. G., and Dixon, H.: CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological use, Earth Syst. Sci. Data Discuss., 8, 83-112, doi:10.5194/essdd-8-83-2015, 2015. [5] 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. https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e Full details about this dataset can be found at https://doi.org/10.5285/047d914f-2a65-4e9c-b191-09abf57423db