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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

  • 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 comprises seven ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0.1° × 0.1° grid (approximate grid of 10 km × 10 km) across West Africa for historical (1950 to 2005) and projected future (2006 to 2099) periods. This dataset is the output from the Hydrological Modelling Framework for West Africa, or “HMF-WA” model. The ensembles correspond to historical and three projected future climate scenarios (RCP2.6, RCP4.5 and RCP8.5) with two future scenarios of water use. The scenarios of water use are (i) future water use that varies in line with projected population increases, and (ii) future water use is the same as present day. This dataset is an output from the regional scale hydrological modelling study from African Monsoon Multidisciplinary Analysis-2050 (AMMA-2050) project. Full details about this dataset can be found at https://doi.org/10.5285/6429828f-6a06-4d2d-8f50-4910b18f7ff4

  • 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 2019. 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/dbf13dd5-90cd-457a-a986-f2f9dd97e93c

  • A new monthly long term average (climatology) of Leaf Area Index (LAI) has been developed for use as ancillary data with the Joint UK Land Environment Simulator (JULES) Land Surface Model and the UK Met Office Unified Model. It is derived from an improved version of long time series of LAI from the original Global LAnd Surface Satellite (GLASS) products (http://www.glass.umd.edu/LAI/MODIS/0.05D/). The GLASS data consists of a time series of LAI from Moderate Resolution Imaging Spectroradiometer (MODIS) surface-reflectance data for the period 2000-2014. The MODIS data was provided in a spatial resolution of 1km in a sinusoidal projection and is interpolated into 0.5◦ on a geographic latitude/longitude projection in this dataset. The total LAI from MODIS is segregated into five different Plant Functional Types (PFTs) using the fractional coverage of each PFT from the Climate Change Initiative (CCI) Land Cover data. For this reason this new LAI climatology should be used in combination with the CCI PFT data, which is also provided here. Two variables are provided with the dataset containing LAI, each covering the same spatial and time extent. The PFT data provided with this dataset covers a time span of only one year, 2010. - Leaf Area Index (LAI) - LAI is an important parameter in land-surface models, influencing the surface roughness, transpiration rate and the soil water content and temperature. Numerous outputs of vegetation models such as net primary productivity (NPP), evapotranspiration (ET), light absorption by plants (FAPAR), nutrient dynamics etc., are influenced by LAI where it is a key variable in energy and water balance calculations. - Vegetation Canopy Height (H) - H plays an important role in the interface between the atmosphere and land surface and it impacts weather and climate at local to global scales by modulating aerodynamic conductance and vegetation dynamics. Therefore, H is fundamentally needed for the calculation of turbulent exchanges of energy and mass between the atmosphere and the terrestrial ecosystem. One variable is provided with the dataset containing CCI PFTs: - Fractional coverage of 5 PFTS or vegetation classes and 4 land use classes – The 5 PFTs are Broad Leaf, Needle Leaf, C3 Grass, C4 Grass and Shrub. The 4 land use classes are Urban area, Inland Water, Bare Soil and Snow/Ice. Full details about this dataset can be found at https://doi.org/10.5285/6d07d60a-4cb9-44e4-be39-89ea40365236

  • Gridded daily meteorological variables over Great Britain for the years 1961-2017 at 1 km resolution. 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 with daily disaggregation. 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 temporal coverage 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/10.5285/2ab15bf0-ad08-415c-ba64-831168be7293

  • A soil moisture product for Great Britain at two spatial resolutions: 12.5km and 1km, based on triple collocation error estimation and a least-squares merging scheme. Two remote sensing soil moisture datasets (one passive microwave dataset: SMAP, and one active microwave dataset: ASCAT) and a modelled soil moisture dataset (from JULES-CHESS land surface model) were combined to produce this dataset. The dataset covers the period going from 1st April 2015 to 31st December 2017, at a daily timestep, and is available at two spatial resolutions: 12.5km; and 1km, which has been obtained after resampling all three underlying datasets to a 1km resolution. Full details about this dataset can be found at https://doi.org/10.5285/26b8ddd4-09fd-4e40-a556-6a8f3a7481ea

  • [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]. The dataset contains 1km gridded estimates of hourly rainfall for Great-Britain for the period 1990-2014. The estimates are derived by applying the nearest neighbour interpolation method to a national database of hourly raingauge observations collated by Newcastle University and the Centre for Ecology & Hydrology (CEH). These interpolated hourly estimates were then used to temporally disaggregate the CEH-GEAR daily rainfall dataset. The estimated rainfall on a given hour refers to the rainfall amount accumulated in the previous hour. The dataset also contains data indicating the distance between the grid point and the closest recording raingauge used in its interpolation. When this distance is greater than 50km, or there is zero rainfall recorded in the closest gauge, the daily value is disaggregated using a design storm. The dataset therefore also contains a flag indicating if the design storm was used. These data are provided as an indicator of the quality of the estimates. Full details about this dataset can be found at https://doi.org/10.5285/d4ddc781-25f3-423a-bba0-747cc82dc6fa

  • This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and MORECS potential evaporation). It provides monthly mean flow (m3/s) and soil moisture (mm water/m soil) on a 1 km grid for the period 1960 to 2015. To aid interpretation, two additional spatial datasets are provided: * Digitally-derived catchment areas on a 1km x 1km grid * Estimated locations of flow gauging stations on a 1km x 1km grid and as a csv file. The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity. Full details about this dataset can be found at https://doi.org/10.5285/e911196a-b371-47b1-968c-661eb600d83b