QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains a map of a ecosystem. This map depicts the 825 terrestrial ecoregions of the globe. Ecoregions are relatively large units of land contain ing distinct assemblages of natural communities and species, with boundaries that approximate the original extent of natural communities prior to major land-use change. This comprehensive, global map provides a useful framework for conducting biogeographical or macroecological research, for identifying areas of outstanding biodiversity and conse rvation priority, for assessing the representation and gaps in conservation efforts worldwide, and for communicating the global distribution of natural communities on earth.

This dataset contains coupled physical-biogeochemical ocean second generation Geophysical Fluid Dynamics Laboratory (GFDL-ESM2M) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes. Job IDs included in this dataset are: GFDL-ESM2M surface fluxes (started on 19th July ~14h): RCP85: u-ao541 (copy from u-ao419, change model names, restart + reduce walltime for nemo to test ) RCP26: u-ao551 (copy from u-ao541 and change rcp26 surface fluxes) Constant atm CO2: RCP85: u-ao552 (copy from u-ao541 with cst atm changes) RCP26: u-ao554 (copy from u-ao551 with cst atm changes) This data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.

Data from the GSFC (Goddard Space Flight Centre) GEOSCCM model simulations, part of the International Global Atmospheric Chemistry (IGAC)/ Stratosphere-troposphere Processes and their Role in Climate (SPARC) Chemistry-Climate Model Initiative phase 1 (CCMI-1). CCMI-1 is a global chemistry climate model intercomparison project, coordinated by the University of Reading on behalf of the World Climate Research Programme (WCRP). The dataset includes data for the CCMI-1 reference experiments ref-C1 and ref-C2. ref-C1: Using state-of-knowledge historic forcings and observed sea surface conditions, the models simulate the recent past (1960–2010). ref-C2: Simulations spanning the period 1960–2100. The experiments follow the WMO (2011) A1 baseline scenario for ozone depleting substances and the RCP 6.0 (Meinshausen et al., 2011) for other greenhouse gases, tropospheric ozone (O3) precursors, and aerosol and aerosol precursor emissions.

Sentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). TROPOMI on the Sentinel 5 Precursor (S5P) satellite observes the CO global abundance exploiting clear-sky and cloudy-sky Earth radiance measurements in the 2.3 µm spectral range of the shortwave infrared (SWIR) part of the solar spectrum. TROPOMI clear sky observations provide CO total columns with sensitivity to the tropospheric boundary layer. For cloudy atmospheres, the column sensitivity changes according to the light path. Carbon monoxide (CO) is an important atmospheric trace gas for our understanding of tropospheric chemistry. In certain urban areas, it is a major atmospheric pollutant. The main sources of CO are the combustion of fossil fuels, biomass burning, and atmospheric oxidation of methane and other hydrocarbons. Whereas fossil fuel combustion is the main source of CO at Northern mid-latitudes, the oxidation of isoprene and biomass burning play an important role in the tropics.

This dataset comprises monthly mean data from a global, transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 1950 to 2015. WACCM-X is a global atmosphere model covering altitudes from the surface up to ~500 km, i.e. including the troposphere, stratosphere, mesosphere and thermosphere. WACCM-X version 2.0 (Liu et al., 2018) was used, part of the Community Earth System Model (CESM) release 2.1.0 made available by the US National Center for Atmospheric Research. The model was run in free-running mode with a horizontal resolution of 1.9° latitude 2.5° longitude (giving 96 latitude points and 144 longitude points) and 126 vertical levels. Further description of the model and simulation setup is provided by Cnossen (2020) and references therein. A large number of variables are included on standard monthly mean output files on the model grid, while selected variables are also offered interpolated to a constant height grid or vertically integrated in height (details below). Zonal mean and global mean output files are included as well. The following data file types are included: 1)Monthly mean output on the full grid for the full set of variables; [DFT] = '' 2)Zonal mean monthly mean output for the full set of variables; [DFT] = _zm 3)Global mean monthly mean output for the full set of variables; [DFT] = _gm 4)Height-interpolated/-integrated output on the full grid for selected variables; [DFT] = _ht A cos(latitude) weighting was used when calculating the global means. Data were interpolated to a set of constant heights (61 levels in total) using the Z3GM variable (for variables output on midpoints, with "lev" as the vertical coordinate) or the Z3GMI variable (for variables output on interfaces, with "ilev" as the vertical coordinate) stored on the original output files (type 1 above). Interpolation was done separately for each longitude, latitude and time. Mass density (DEN [g/cm3]) was calculated from the M_dens, N2_vmr, O2, and O variables on the original data files before interpolation to constant height levels. The Joule heating power QJ [W/m3] was calculated using Q_J=_P B^2 [(u_i-u_n )^2+(v_i-v_n )^2+(w_i-w_n )^2] with P = Pedersen conductivity [S], B = geomagnetic field strength [T], ui, vi, and wi = zonal, meridional, and vertical ion velocities [m/s] and un, vn, and wn = neutral wind velocities [m/s]. QJ was integrated vertically in height (using a 2.5 km height grid spacing rather than the 61 levels on output file type 4) to give the JHH variable on the type 4 data files. The QJOULE variable also given is the Joule heating rate [K/s] at each of the 61 height levels. All data are provided as monthly mean files with one time record per file, giving 792 files for each data file type for the period 1950-2015 (66 years).

This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations which, have been re-surveyed at different times. This plot site was situated in French Guiana, Cayenne, Nourague Nautre Reserve. The plot site had the following geographical features; Moisture type: Moist, Elevation: Lowland, Edaphic Type: Terra Firma, Substrate:Mixed, Geology: Pre-Quaternary,Forrestry: Old-growth. The project scanned all trees in the permanent sample plot (PSP) spanning a range of soil fertility and productivity gradients (24 x 1 ha PSPs in total). The aim of the weighing trees with lasers project is to test if current allometric relationships are invariant across continents, or whether they differ significantly, and require continental level models; quantify the impact of assumptions of tree shape and wood density on tropical forest allometry; test hypotheses relating to pan-tropical differences in observed AGB (Above Ground Biomass) from satellite and field data. It also aims to apply new knowledge to assessing retrieval accuracy of forthcoming ESA BIOMASS and NASA GEDI (Global Ecosystem Dynamics Investigation Lidar) missions and providing calibration datasets; In addition to testing the capability of low-cost instruments to augment TLS data including: UAVs (unmanned aerial vehicle) for mapping cover and canopy height; low-cost lidar instruments to assess biomass rapidly, at lower accuracy.

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains decadal surface meteorology climatologies from CRU TS3.0 data 1901- 2000. Data includes parameters such as temperature, water vapour and precipitation.

Sentinel Hub NBR description: To detect burned areas, the NBR-RAW index is the most appropriate choice. Using bands 8 and 12 it highlights burnt areas in large fire zones greater than 500 acres. To observe burn severity, you may subtract the post-fire NBR image from the pre-fire NBR image. Darker pixels indicate burned areas. NBR = (NIR – SWIR) / (NIR + SWIR) Sentinel-2 NBR = (B08 - B12) / (B08 + B12) These data have been created by the Joint Nature Conservation Committee (JNCC) as part of a Defra Natural Capital & Ecosystem Assessment (NCEA) project to produce a regional, and ultimately national, system for detecting a change in habitat condition at a land parcel level. The first stage of the project is focused on Yorkshire, UK, and therefore the dataset includes granules and scenes covering Yorkshire and surrounding areas only. The dataset contains the following indices derived from Defra and JNCC Sentinel-2 Analysis Ready Data. NDVI, NDMI, NDWI, NBR, and EVI files are generated for the following Sentinel-2 granules: • T30UWE • T30UXF • T30UWF • T30UXE • T31UCV • T30UYE • T31UCA As the project continues, JNCC will expand the geographical coverage of this dataset and will provide continuous updates as ARD becomes available.

The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises the Level 2 aerosol products from ATSR-2, using the ORAC algorithm, version 3.02. For further details about these data products please see the linked documentation.

Cascade was a NERC funded consortium project to study organized convection and scale interactions in the tropical atmosphere using large domain cloud system resolving model simulations. This dataset contains data from the xeule simulation which ran using the Met Office Unified Model (UM) at 40km horizontal resolution over an idealised equatorial domain of about 8000x4000km. Cascade Idealised simulations are used to study warm pool convection and equatorial waves.