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

The data resource consists of half hourly time series of heat (latent and sensible) and trace gas (carbon dioxide and methane) fluxes obtained by eddy-covariance, gas concentrations and ancillary meteorological data (e.g. air temperature, relative humidity, pressure, photosynthetically active radiation, total incoming radiation, wind speed and direction). The data were collected at Guma Lagoon (18°57'53.01"S; 22°22'16.20"E), in the perennially flooded area of the Okavango Delta, Botswana, for the purpose of quantifying greenhouse gas fluxes over a Cyperus papyrus stand. The measurement period was 01/01/2018 to 31/12/2020. The instrumentation was installed the UK Centre for Ecology and Hydrology; monthly maintenance and data collection visits were effected by the Okavango Research Institute, University of Botswana. The research was funded through NERC grant reference NE/N015746/2 - The Global Methane Budget. Full details about this dataset can be found at https://doi.org/10.5285/d366ed40-af8c-42be-86f2-bb90b11a659e

The WATCH Forcing data is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or DAT formats. The data covers land points only and excludes the Antarctica. Snowf or snowfall is the snowfall rate based on the GPCC bias corrected, undercatch corrected measured in kg/m2/s at 3 hourly resolution averaged over the next 3 hours and at 0.5 x 0.5 degrees spatial resolution. Please note that there is also a WFD Snowf CRU bias corrected dataset, but as the GPCC dataset is the preferred dataset only this snowfall dataset is available from the EIDC. These snowfall datasets contain snowfall data only and need to be combined with the respective WFD rainfall datasets to obtain precipitation data.

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 1961 to 2012. [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. Full details about this dataset can be found at https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f

The WATCH Forcing data is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or DAT formats. The data covers land points only and excludes the Antarctica. LWdown or surface incident longwave radiation (also known as downwards long-wave radiation flux ) is the surface incident longwave radiation averaged over the next six hours, measured in W/m2 at 6 hourly resolution and 0.5 x 0.5 degrees spatial resolution.

Averaged outputs from the WRF (Weather Research and Forecasting) model for the Rio Santa and Vilcanota, Urubamba and Vilcabamba catchments in Peru. Averaging was applied over the entire model period from 1980 to 2018. Data includes: - Averaged precipitation and air temperature records and the related standard deviation at a 4km resolution (annually and for each season) for each catchment. Monthly averaged and monthly totals of air temperature and precipitation (averaged over each catchment). - WRF model input elevation for each catchment. - WRF total precipitation and maximum/minimum air temperature at the location of five on-glacier weather stations (Artesonraju Glacier, Shallap Glacier, Cuchillacocha Glacier, Quisoquipina Glacier and Quelccaya Ice Cap) at a daily resolution from 1980 to 2018. Full details about this dataset can be found at https://doi.org/10.5285/7dbb2d72-7032-4cfa-bc9b-aa02bebe8df5

This dataset contains fire emissions from Equatorial Asia for the years 2004, 2006, 2009, 2012, 2014 and 2015. The data is based on the Fire Inventory from National Center for Atmospheric Research with the addition of emissions from Indonesian peat fires, which contribute substantially to fire emissions in the region. The files for each year contain daily information on the area burned and emissions of several species, including CO, CO2 and PM2.5. Data is given for individual fires at 1km resolution. Fire emissions are provided for each year both for fires as measured, and under a scenario where degraded peatland in the region has been partially restored, reducing fire emissions. Full details about this dataset can be found at https://doi.org/10.5285/fdae44ed-8b22-4935-b889-b4b271138385

Monthly and daily 5km gridded Potential Evapotranspiration (PET) data for the UK. PET was derived using temperature-based equation from McGuinness-Bordne calibrated for the UK (calibration period: 1961-1990). The units are mm/day for daily PET and mm/month for monthly PET. The dataset covers the period from 1891-2015. For both subsets (daily and monthly), a set of performance metrics were calculated, which are provided together with the PET grids. The list of metrics provided is: Mean Absolute Percent Error (MAPE), Nash-Sutcliffe Efficiency (NSE), Kling-Gupta Efficiency (KGE), Correlation Coefficient, Variability Ratio (VR), Bias Ratio and monthly MAPE. Full details about this dataset can be found at https://doi.org/10.5285/17b9c4f7-1c30-4b6f-b2fe-f7780159939c

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]. 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