The University of Leicester GOSAT Proxy XCH4 v9.0 data set contains column-averaged dry-air mole fraction of methane (XCH4) generated from the Greenhouse Gas Observing Satellite (GOSAT) Level 1B data using the University of Leicester Full-Physics retrieval scheme (UoL-FP) using the Proxy retrieval approach. This data is an NCEO funded update/extension to the European Space Agency Climate Change Initiative (CCI) CH4_GOS_OCPR V7.0. and the Copernicus Climate Change Service (C3S) CH_4 v7.2 data sets. It's a full reprocessing, based on different underlying L1B radiance data with additional changes. The latest version of the GOSAT Level 1B files (version 210.210) was acquired directly from the National Institute for Environmental Studies (NIES) GOSAT Data Archive Service (GDAS) Data Server and are processed with the Leicester Retrieval Preparation Toolset to extract the measured radiances along with all required sounding-specific ancillary information such as the measurement time, location and geometry. These measured radiances have the recommended radiometric calibration and degradation corrections applied as per Yoshida et al., 2013 with an estimate of the spectral noise derived from the standard deviation of the out-of-band signal. The spectral data were then inputted into the UoL-FP retrieval algorithm where the Proxy retrieval approach is used to obtain the column-averaged dry-air mole fraction of methane (XCH4). Post-filtering and bias correction against the Total Carbon Column Observing Network is then performed. See process information and documentation for further details.

This dataset contains Methane, Carbon Dioxide and Nitrous Oxide measurements taken from Heathfield Tower at 50m and 100m. The measurements were taken using a Gas Chromatography-micro Electron Capture Detector (GC-ECD). This data was collected as part of the NERC GAUGE (Greenhouse gAs UK and Global Emissions) project (NE/K002449/1NERC and TRN1028/06/2015). The GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter- calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology.

This dataset contains methane fluxes from peatland plateaus and thawing peatland plateaus and from burnt and unburnt forests from permafrost in subarctic Canada. Methane fluxes were monitored during summer in 2013 and 2014 in Yukon and Northwest Territories. Monitored sites included peatland plateaus and thawing features of peatland plateaus. Full details about this dataset can be found at https://doi.org/10.5285/1d4d70ad-dc38-4e5f-bc39-066babca2fb2

This dataset contains methane, carbon dioxide and meteorological observations taken onboard the commercial freight ferry Finlandia Seaways on route between Rosyth (Scotland, UK: 56°1'21.611''N 3°26'21.558'' W) and Zeebrugge (Belgium : 51°21'16.96''N 3°10'34.645''E) 2015-2017 by the Centre for Ecology and hydrology (CEH). The measurements were taken using a Picarro CRDS model G1301, Vaisala WXT510 weather station and Garmin GPS. This data was collected as part of the Natural Environment Research Council (NERC) Greenhouse gAs Uk and Global Emissions (GAUGE) project (NE/K002449/1NERC) and NERC UK-SCAPE programme delivering National Capability (NE/R016429/1). The GAUGE project aimed to determine the magnitude, spatial distribution, and uncertainties of the UK's Greenhouse Gas budget using new and existing measurement networks and modelling approaches at a range of scales.

This dataset contains methane, carbon dioxide and nitrous oxide measurements taken from Bilsdale Tower at 42, 108 and 248m. The measurements were taken using a Cavity Ring Down Spectrometer (CRDS). This data was collected as part of the NERC GAUGE (Greenhouse gAs UK and Global Emissions) project (NE/K002449/1NERC and TRN1028/06/2015). The GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter- calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology.

This data set consist of a single file which contains a set of optimised global surface fluxes of methane (CH4), produced through variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. These surface fluxes are produced as monthly mean values on the (approximately) 5.6-degree horizontal model grid. The associated uncertainty for the flux from each grid cell is also included. The fluxes and uncertainties are global and cover the period Jan 2010 - Dec 2018. The emissions from fossil fuels are labelled FF_FLUX, whilst the uncertainties are labelled FF_ERROR. The emissions from natural, agricultural and biomass burning sources are labelled NAT_FLUX, whilst the uncertainties are labelled NAT_ERROR. These two sectors (fossil fuel and non-fossil fuel) are solved for separately in the inversion. Flux and uncertainty units are kg(CH4)/m2/s, and time units are days since January 1st 2010. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in Wilson et al. (2020) in the documentation section.

Part of the European Space Agency's (ESA) Greenhouse Gases (GHG), the XCH4 EMMA product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced by applying the ensemble median algorithm EMMA to level 2 data of several different retrieval products from the Japanese Greenhouse gases Observing Satellite (GOSAT) This is therefore a merged GOSAT XCH4 Level 2 product, primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). For further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR) in the documentation section. The GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/

Part of the European Space Agency's (ESA) Greenhouse Gases (GHG), the XCO2 EMMA product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced by applying the ensemble median algorithm EMMA to level 2 data of 7 XCO2 retrievals from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This is therefore a merged SCIAMACHY and GOSAT XCO2 Level 2 product, primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). This version of the product covers 4 years. For further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR) in the documentation section. The GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/

The dataset contains greenhouse gas fluxes (N2O, CO2 and CH4) following artificial and real sheep urine applied to organic soils within the Carneddau mountain range (556 m a.s.l.) in Snowdonia National Park, North Wales, UK. The study was conducted across two contrasting seasons (summer and autumn). Soil greenhouse gas emission data was collected using a combination of automated chambers and manually sampled chambers, with gas samples analysed via gas chromatography. Supporting data include characterisation of the soil properties at each site, meteorological data, soil moisture and soil chemistry on a time-series following treatment application. The data were used to calculate sheep urine patch N2O-N emission factors, to improve estimates of greenhouse gas emissions from sheep urine deposited to extensively grazed montane agroecosystems. Full details about this dataset can be found at https://doi.org/10.5285/01811fce-1e0f-43be-8649-336b5c51d6cf

Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the XCH4 SCI product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the SWIR spectra (channel 6) of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This product has been derived by applying the IMAP-DOAS algorithm developed at the University of Heidelberg and SRON to the SCIAMACHY data. This procedure and the algorithms validity are thoroughly described in Frankenberg et al (2011). A second product is also available which has been generated using the Weighting Function Modified DOAS (WFM-DOAS) algorithm. The data product is stored per orbit in a single NetCDF4 file. Retrieval results are provided for the individual SCIAMACHY spatial footprints, no averaging having been applied. The product file contains the key products and information relevant to using the data, such as the vertical layering and averaging kernels. For further details on the product, including the IMAP algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section. The GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/