[THIS DATASET HAS BEEN WITHDRAWN].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

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. PSurf or surface pressure is the surface pressure (instantaneous) measured in Pa at 6 hourly resolution and 0.5 x 0.5 degrees spatial resolution.

Data comprise relative humidity measured at an automatic monitoring buoy located in Blelham Tarn, UK. Data are provided from January 2012 to December 2019. Hourly averages are given, calculated from measurements taken every four minutes. All data is given in GMT (Greenwich Mean Time). 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/10.5285/3df05e85-2c56-4bd9-9918-44b760e20b2e

The WATCH forcing data (WFD) 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. Rainf or rainfall rate is the rainfall rate based on the Global Precipitation Climatology Centre (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 Rainf CRU bias corrected dataset, but as the GPCC dataset is the preferred dataset only this rainfall dataset is available from the EIDC. These rainfall datasets contain rainfall data only and need to be combined with the respective WFD snowfall 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

Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program.

This dataset contains measurements of the water vapour isotope composition of ambient vapour obtained from a water vapour isotope analyzer manufactured by Los Gatos Research (LGR), and from discrete sampling of surface snow and precipitation and subsequent laboratory analysis. The analyzer was installed in the harbour of Húsavik, Iceland. Discrete sampling included precipitation and surface snow from two surface transects in northern Iceland and in several locations in southern Norway. The LGR LWIA analyzer is an off-axis cavity ring-down spectrometer using infrared absorption bands for the retrieval of the water isotope ratios for H216O, H218O, and HDO, quantified as mixing ratio of water vapour (w, ppmv), delta 18-O, and delta-D (permil). The data set for the Húsavik station is accompanied by automatic weather station data (air temperature, relative humidity, wind speed, wind direction, sea-level pressure) from the Icelandic weather service (vedur.is) for several nearby locations. For further details and figures for the vapour measurements, and the surface sample collection during the campaign, and processing thereafter, please read the attached documentation. This research is funded by the Research Council of Norway under the Sources of the Norwegian winter season snow pack constrained by stable water isotopes - SNOWPACE project (Project Nr. 262710) and the Facility for advanced isotopic research and monitoring of weather, climate and biogeochemical cycling (FARLAB) project (Project Nr. 245907).

The Quantifying the Amazon Isoprene Budget: Reconciling Top-down versus Bottom-up Emission Estimates project produced a unique high resolution model (GEOS-Chem version v8-03-01 - with modifications) for the Amazon, which simulated isoprene emissions and atmospheric chemistry. Model outputs associated with Barkley et al. publication is available through CEDA-BADC. An evaluation of a nested high-resolution Goddard Earth Observing System (GEOS)-Chem chemistry transport model simulation of tropospheric chemistry over tropical South America is presented. The model has been constrained with two isoprene emission inventories: (1) the canopy-scale Model of Emissions of Gases and Aerosols from Nature (MEGAN) and (2) a leaf-scale algorithm coupled to the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model, and the model has been run using two different chemical mechanisms that contain alternative treatments of isoprene photo-oxidation. The publication is: Barkley, M. P., P. I. Palmer, L. Ganzeveld , A. Arneth , D. Hagberg , T. Karl , A. Guenther , F. Paulot , P. Wennberg , J. Mao , T. Kurosu , K. Chance , J.-F. Muller, I. De Smedt , M. Van Roozendael , D. Chen , Y. Wang , R. Yantosca, Can a 'state of the art' chemistry transport model really simulate Amazonian tropospheric chemistry?, J. Geophys. Res., 116, D16302, doi:10.1029/2011JD015893, 2011 This is a NERC funded project.

This dataset contains estimates of turbulent heat and momentum fluxes calculated by applying the eddy covariance technique to the flux-components data product. Estimates are calculated over 15-minute and 30-minute averaging intervals, at two heights on the 15 m tower at Summit Station, Greenland. - ace-flux-1 are the lower level (~2 m above surface) calculations, from a Metek uSonic-3 scientific 3D sonic anemometer and Licor Li-7500 gas analyzer. - ace-flux-2 are the higher level measurements (~14 m above surface), from a Metek uSonic-3 scientific 3D sonic anemometer only (no latent heat flux). Also see the ICECAPS-ACE: surface turbulent heat flux components data product for the high resolution (10 Hz) data used to make these calculations. These data were collected as part of the joint Natural Environmental Research Council (NERC) and US National Science Foundation (NSF) -funded Integrated Characterisation of Energy, Clouds, Atmospheric state, and Precipitation at Summit - Aerosol Cloud Experiment (ICECAPS-ACE) project. These data were continued through the 3 year extension to the ICECAPS-ACE project called ICECAPS-MELT.

Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 20 for South AMerican Biomass Burning Analysis (SAMBBA) project.