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  • The Methane and other greenhouse gases in the Artic - Measurements, process studies and Modelling (MAMM) project was a consortium as part of the NERC Artic Research Programme. This project used a range of expertise, from measurements of methane and its isotopes, and other greenhouse gases, through flux measurements to numerical analysis and modelling. Analysis of gas mixing ratios (concentrations), isotopic character, and source fluxes, both from the ground and aircraft. Both past and new measurements were modelled using a suite of techniques. Fluxes were implemented into the JULES land surface model. Atmospheric modelling, including trajectory and inverse modelling will improve understanding on the local/regional scale, placing the role of Arctic emissions in large scale global atmospheric change. The project was led by the University of Cambridge, and in association with the University of Manchester, University of East Anglia, Royal Holloway, University of London, Centre for Ecology and Hydrology and UK and International partners (Met Office, NILU, NOAA, etc).

  • These data are NERC-funded but not held by the EIDC. These data are archived in the SAFE repository, hosted by Zenodo. This dataset contains calculated greenhouse gas fluxes and associated parameters from 56 static chambers that were installed within the Stability of Altered Forest Ecosystems (SAFE) landscape in Malaysian Borneo. Of the chosen ‘fragment’ in the SAFE design, all chambers were put in the 10 ha fragments. Four chambers each were placed in each of the two 10 ha plots in Logged Fragmented Forest (LFE), Fragment B, and Fragment E resulting in 8 per site. Additionally 12 chambers were installed in a 7-year old oil palm plantation, 8 in a young (2-year) old oil palm and 8 in a 12 – year old oil palm plantations. All 56 chambers were sampled for greenhouse gases (methane, nitrous oxide and carbon dioxide soil respiration) every two months over a two-year period from January 2015 to November 2016, resulting in 12 measurement occasions for each of the chambers. Other environmental parameters were measured during the time of chamber enclosure as possible explanatory variables for correlation with recorded greenhouse gas fluxes including soil and air temperature, soil moisture, soil mineral N (nitrate and ammonium).

  • This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2), using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm which has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA. This version of the data was produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg) and got co-funding from the Univ. Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810). When citing this dataset, please also cite the following peer-review publications: M.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017 M.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017

  • 'Are tropical uplands regional hotspots for methane and nitrous oxide?' was a NERC (Natural Environment Research Council) funded project from 2010-2015 with the following grant references NE/H007849/1, NE/H006753/1 and NE/H006583/2. This dataset collection contains in-situ ground based soil-atmosphere flux and soil condition measurements from 4 different ecosystems located in the Peruvian Andes over ~2.5 years between 2010-2013. The ecosystems included upper montane forest (Wayqecha), lower montane forest (San Pedro), premontane forest (Villa Carmen) and grassland sites. At present, data are only available for 3 ecosystems; Wayqecha, San Pedro and Villa Carman. However, the grassland dataset will follow shortly along with some model output.

  • These data are NERC-funded but not held by the EIDC. These data are archived in the SAFE repository, hosted by Zenodo. This dataset contains calculated greenhouse gas fluxes and associated parameters from three transects of static chambers that were set up from oil palm into riparian forests in the SAFE landscape in Malaysian Borneo, Sabah. A total of 48 chambers were installed in two transects of 6 x 3 chambers and one transect of 4 x 3 chambers. Soil greenhouse gases (methane, nitrous oxide and carbon dioxide) were measured every two months for one year (Nov 2016 until Nov 2017) resulting in 7 measurement occasions. Other environmental parameters were measured during the time of chamber enclosure as possible explanatory variables for correlation with recorded greenhouse gas fluxes including soil and air temperature, soil moisture, soil mineral N (nitrate (NO3) and ammonium (NH4)). In addition, water samples were taken from the stream and analysed for NO3, NH4, pH, temperature, total dissolved solids, conductivity and greenhouse gases using the headspace method.

  • The CH4_GOS_OCFP dataset is comprised of level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT), using the University of Leicester Full-Physics Retrieval Algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version is version 2.1 and forms part of the Climate Research Data Package 4. The University of Leicester Full-Physics Retrieval Algorithm is based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and has been modified for use on GOSAT spectra. A second GOSAT CH4 product, generated using the SRFP algorithm, is also available. The XCH4 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG).

  • The CH4_GOS_SRFP dataset is comprised of level 2, column-averaged mole fractiona (mixing ratioa) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra onboard the Japanese Greenhouse gases Observing Satellite (GOSAT) using the SRFP (RemoTec) algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci). This version of the dataset is v2.3.8 and forms part of the Climate Research Data Package 4. The RemoTeC SRFP baseline algorithm is a Full Physics algorithm. The data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key products with and without bias correction. Information relevant for the use of the data is also included in the data file, such as the vertical layering and averaging kernels. Additionally, the parameters retrieved simultaneously with XCH4 are included (e.g. surface albedo), as well as retrieval diagnostics like retrieval errors and the quality of the fit. For further information on the product, including the RemoTeC Full Physics algorithm and the TANSO-FTS instrument please see the Product User Guide (PUG) or the Algorithm Theoretical Basis Document.

  • The CH4_GOS_SRPR dataset is comprised of Level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT), using the RemoTeC SRPR Proxy Retrieval algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the data is version 2.3.8, and forms part of the Climate Research Data Package 4. This Proxy Retrieval product has been generated using the RemoTeC SRPR algorithm, which is being jointly developed at SRON and KIT. This has been designated as an 'alternative' GHG CCI algorithm, and a separate product has also been generated by applying the baseline GHG CCI proxy algorithm (the University of Leicester OCPR algorithm). It is advised that users who aren't sure whether to use the baseline or alternative product use the OCPR product generated with the baseline algorithm. For more information regarding the differences between the baseline and alternative algorithms please see the GHG-CCI data products webpage. The data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. As well as containing the key product, the product file contains information relevant for the use of the data, such as the vertical layering and averaging kernels. The parameters which are retrieved simultaneously with XCH4 are also included (e.g. surface albedo), in addition to retrieval diagnostics like quality of the fit and retrieval errors. For further details on the product, including the RemoTeC algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents.

  • The CH4_EMMA dataset is comprised of level 2, column-averaged dry-air mole fractions (mixing ratios) for methane (XCH4). It has been produced using the ensemble median algorithm EMMA to several different versions of the Japanes Greenhouse gases Observing Satellite (GOSAT) XCH4 data, as part of the ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the product is v1.2, and forms part of the Climate Research Data Package 4. The ensemble median algorithm EMMA has been applied 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, which is 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).

  • The CH4_SCI_WFMD dataset comprises level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's (ESA's) environmental research satellite ENVISAT, as part of the ESA's Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the data is version 4.0, and forms part of the Climate Research Data Package 4. The Weighting Function Modified DOAS (WFMD) algorithm is a least-squares method based on scaling pre-selected atmospheric vertical profiles. A second product is also available, which has been generated from the SCIAMACHY data using the IMAP algorithm. The data product is stored per day in separate NetCDF-files (NetCDF-4 classic model). The product files contain the key products and other information relevant for the use of the data e.g. the averaging kernels. Note that the results since November 2005 are considered to be of reduced quality in comparison to the earlier results because the extended-wavelength part (1590-1770 nm) of SCIAMACHY's channel 6, covering the methane 2v3 absorption band used for the methane retrieval, is subject to irreversible displacement damage induced by high energy solar protons, which occurs from time to time at individual detector pixels. Therefore several affected detector pixels had to be excluded for the time period since November 2005. For further information on the product, including details of the WFMD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents.