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From 1 - 10 / 2096
  • Skin Sea Surface Temperature data from the (A)ATSR Validation Campaign by SISTeR. The prime objective of the (A)ATSR mission is to return accurate measurements of the global sea surface temperature. To ensure the accuracy of the measurement, there have been joint efforts to validate the data. One of these efforts is the (A)ATSR Validation Campaign which involves the deployment of the Scanning Infrared Sea surface Temperature Radiometer (SISTeR). The SISTeR is a self-calibrating radiometer that measures the skin sea surface temperature. The SISTeR was mounted on MS Color Festival and MS Prinsesse Ragnhild to return skin sea surface temperature in the North Sea in 2006, and was on-board RMS Queen Mary 2 collecting data from the Atlantic Ocean, Indian Ocean and Western Pacific between 2010 and 2014. Data was collected continuously throughout the cruises unless severe weather conditions required the instrument to be protected, which results in the prevention of the data collection.

  • This dataset collection contains Chemical Ablation Model version 3 (CABMOD3) simulations of metal ablation from meteoroids and Meteoric Ablation Simulator (MASI) sodium and nickel ablation experimental data. This experiment was undertaken as part of Natural Environment Research Council (NERC) First study of the global Nickel and Aluminium Layers in the upper atmosphere (NIALL) project (NE/P001815/1). This project aimed to make the first ever study of Ni and Al chemistry in the mesosphere/lower thermosphere.

  • Cloud properties derived from a synergetic retrieval from MERIS and AATSR on ENVISAT by the ESA Cloud CCI project. The L3C dataset consists of data combined (averaged) into a global space-time grid, with a spatial resolution of 0.5 degrees lat/lon and a temporal resolution of 1 month. This dataset is version 2.0 data from Phase 1 of the CCI project.

  • This dataset contains a series of 99 limited-area models (LAMs) nested within the Met Office global model. Met Office Unified Model (MetUM) deployed on xce, xcf and xcs in Exeter. Model data generated using Met Office Unified Model using a nesting suite (u-bw210) that runs an N512 global forecast and 99 embedded limited-area models each using a convection-permitting grid-length of 1.5km. The LAMs are each 360x360 grid points. The outer region is deemed to be a spin-up region and is ignored. The central 240x240 is then coarse-grained onto a 45km scale using 30x30 horizontal averaging to produce a 8x8=64 grid of spatially averaged data. Each file contains data from only one of these 64 subdomains, but data from every one the 99 regions around the globe. The nesting simulations are free-running within each LAM, but the driving model is re-initialised every 00Z using operational atmospheric analyses. All 99 regions are wholly over the sea. The central lat/lon for each of the 99 regions are: (80,-150), (70,0), (60,-35), (60,-15), (50,-160), (50,-140), (50,-45), (50,-25), (50,-149), (50,170), (40,-160), (40,-140), (40,-65), (40,-45), (40,-25), (40,150), (40,170), (30,-170), (30,-150), (30,-130), (29,-65), (30,-45), (30,-25), (30,145), (30,170), (20,-170), (20,-145), (21,-115), (20,-55), (20,-30), (20,65), (20,135), (20,170), (10,-170), (10,-140), (10,-120), (10,-100), (10,-50), (10,-30), (10,60), (10,88), (10,145), (10,160), (0,-160), (0,-130), (0,-100), (0,-30), (0,-15), (0,0), (0,50), (0,70), (0,88), (0,160), (-10,-170), (-10,-140), (-10,-120), (-10,-90), (-10,-30), (-10,-15), (-10,5), (-10,60), (-10,88), (-10,170), (-20,-160), (-20,-130), (-20,-100), (-20,-30), (-20,0), (-20,55), (-20,80), (-20,105), (-30,-160), (-30,-130), (-30,-100), (-30,-40), (-30,-15), (-30,10), (-30,60), (-30,88), (-40,-160), (-40,-130), (-40,-100), (-40,-50), (-40,0), (-40,50), (-40,100), (-50,-150), (-50,-90), (-50,-30), (-50,30), (-50,88), (-50,150), (-60,-140), (-60,-70), (-60,0), (-60,70), (-60,140), (-70,-160), (-70,-40). The data has near global coverage, but using this series of small domains. Training data is available for 6 months: Jan, Mar, Apr, Jul, Oct, Dec 2016. Test data is available for Jun 2017.

  • Sentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). These data products provide geolocated total, tropospheric, or stratospheric Nitrogen dioxide concentrations. The TROPOMI NO2 data products pose an improvement over previous NO2 data sets, particularly in their unprecedented spatial resolution (7×3.5 km2), but also in the separation of the stratospheric and tropospheric contributions of the retrieved slant columns, and in the calculation of the air-mass factors used to convert slant to total columns. Nitrogen dioxide (NO2) and nitrogen oxide (NO) together are usually referred to as nitrogen oxides (NOx = NO + NO2). They are important trace gases in the Earth’s atmosphere, present in both the troposphere and the stratosphere. They enter the atmosphere as a result of anthropogenic activities (notably fossil fuel combustion and biomass burning) and natural processes (such as microbiological processes in soils, wildfires and lightning). During the daytime, i.e. in the presence of sunlight, a photochemical cycle involving ozone (O3) converts NO into NO2 (and vice versa) on a timescale of minutes, so that NO2 is a robust measure for concentrations of nitrogen oxides. Tropospheric and stratospheric concentrations of NO2 are monitored all over the world by a variety of instruments either ground-based, in-situ (balloon, aircraft), or satellite-based each with its own specific advantages.

  • This dataset contains coupled physical-biogeochemical ocean second generation Canadian Earth System Model (CanESM2) 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: CanESM2 surface fluxes (started on 18th for first, 21st for second, and on the 19th for other 2): RCP85: u-ao419 RCP26: u-ao519 Constant atm CO2: RCP85: u-ao529 RCP26: u-ao531 (reduce walltime for nemo to test) 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 ETH-PMOD (Swiss Federal Institute of Technology Zurich and the Physical-Meteorology Observatory Davos) SOCOL3 model, part of the International Global Atmospheric Chemistry (IGAC)/Stratosphere-troposphere Processes and their Role in Climate (SPARC) Chemistry-Climate Model Initiative (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 Program (WCRP). The dataset includes data for the following CCMI-1 experiments: Reference experiments: ref-C1 and ref-C2. Sensitivity experiments: senC2fCH4, senC2CH4rcp85, senC2fEmis, senC2fN2O, senC2rcp26, senC2rcp45, senC2rcp85. 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 (GHGs), tropospheric ozone (O3) precursors, and aerosol and aerosol precursor emissions. senC2CH4rcp85: Similar to ref-C2 but the methane surface-mixing ratio follows the RCP 8.5 scenario (Meinshausen et al., 2011), all other GHGs and forcings follow RCP 6.0. senC2fCH4: Similar to ref-C2 but the methane surface-mixing ratio is fixed to its 1960 value. senC2fEmis: Similar to ref-C2 but with surface and aircraft emissions fixed to their respective 1960 levels. senC2fN2O: Similar to ref-C2 but the nitrous oxide surface-mixing ratio is fixed to its 1960 value. senC2rcp26: The same as ref-C2, but with the GHG scenario changed to RCP 2.6 (Meinshausen et al., 2011). senC2rcp45: The same as ref-C2, but with the GHG scenario changed to RCP 4.5 (Meinshausen et al., 2011). senC2rcp85: The same as ref-C2, but with the GHG scenario changed to RCP 8.5 (Meinshausen et al., 2011).

  • This data set is part of the ESA Sea Ice Climate Change Initiative (CCI) project. The dataset provides sea ice concentration for the Arctic region, derived from the SSMI satellite instrument. It consists of daily gridded SIC fields based on Passive Microwave Radiometer measurements from the SSMI instrument with a 25km grid spacing, along with the total standard error (uncertainty) and quality control flags. It has been built upon the algorithms and processing software originally developed at the EUMETSAT OSI SAF for their SIC dataset. Please note, in the sea ice concentration data set - on purpose - no weather filter has been applied to eliminate weather-induced spurious ice in the open ocean along the ice edge in order to avoid discarding regions with a real sea ice cover. Users are advised to read the product user guide and the publication by Ivanova et al. [2015] (see documentation section). A second sea ice dataset has also been produced from the AMSR-E instrument, and these should be regarded as individual datasets and not combined without further investigations about the compatibility.

  • This dataset contains volatile organic compound (VOC) mixing ratios recorded during two intensive field campaigns in Beijing (winter: 12/11/2016 - 10/12/2016; and summer: 15/05/2017 - 24/06/2017) as part of the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. The species recorded include methanol, acetonitrile, acetaldehyde, acrolein, acetone, isoprene, methyl vinyl ketone and methacrolein, methyl ethyl ketone, benzene, toluene, C2-benzenes, C3-benzenes and monoterpenes. The data were recorded using a proton transfer reaction-time of flight-mass spectrometer (PTR-ToF-MS) from a sampling height of 100m.

  • EVI is a development on Normalised Difference Vegetation Index (NDVI). Sentinel-Hub EVI description: In areas of dense canopy cover, where leaf area index (LAI) is high, the blue wavelengths can be used to improve the accuracy of NDVI, as it corrects for soil background signals and atmospheric influences. The range of values for EVI is -1 to 1, with healthy vegetation generally around 0.20 to 0.80. EVI is calculated: EVI = 2.5 * ((NIR – RED) / ((NIR + (6 * RED) – (7.5 * BLUE)) + 1)) Sentinel 2 EVI = 2.5 * ((B8 – B4) / ((B8 + (6 * B4) – (7.5 * B2)) + 1)) These data have been created by the Joint Nature Conservation Committee (JNCC) as part of a Defra Natural Capital and Ecosystem Assessment (NCEA) project to produce a regional, and ultimately national, system for detecting a change in habitat conditions 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 Enhanced Vegetation Index data derived from Defra and JNCC Sentinel-2 Analysis Ready Data. 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.