This dataset contains a range of model output from both operational runs of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) CY45R1 model forecasts and hindcasts and output from specific experimental runs. These data were produced to support the article "Forecast-based attribution of a winter heatwave within the limit of predictability" (see citation and link to paper elsewhere on this record). Within the archived products the directory tree structure is as follows: Top level domain splitting: >EU Model data at 0.25 degree resolution for the region contained within (33 to 73.5N / -27 to 45E). >GLOB Model data at 0.25 degree resolution for the full globe. Below which there are sub-directories as follows (note, M-climate is only available for the EU domain): >>ENS​ Data from the operational Ensemble Prediction System (EPS) forecast. >>M-climate Data from EPS hindcasts used to construct model climate. See https://confluence.ecmwf.int/display/FUG/M-climate%2C+the+ENS+Model+Climate. >>pi-CO2 Data from EPS forecast that replicates operations *but for* reduced CO2 concentrations, set to 285 ppm. >>incr-CO2 Data from EPS forecast that replicates operations *but for* increased CO2 concentrations, set to 600 ppm. Within these runs the data are then available on the following level types: >>>pl Data on pressure levels. >>>sfc Data on single levels. Ensemble data are further split into sub-directories as follows: >>>>cf Control forecast member. >>>>pf Perturbed forecast members. The specific variables available within each netCDF file can differ depending on the region and experiment type (eg. the operational ENS forecasts whose initialisation dates match those of the perturbed CO2 experiments have more variables available than the others). All the datasets & variables required to reproduce the analysis are described in the paper. Forecast-based attribution of a winter heatwave within the limit of predictability. Nicholas J. Leach, Antje Weisheimer, Myles R. Allen, Tim Palmer. Proceedings of the National Academy of Sciences Dec 2021, 118 (49) e2112087118; DOI: 10.1073/pnas.2112087118

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 (v09) 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 data, please also cite the following peer-reviewed 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

This dataset contains carbon dioxide and water vapour concentration measurements from the University of Leeds' LI-COR LI-7500 open path gas analyser mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record. The instrument's sensing head was located on the foremast of Icebreaker Oden, approximately 1 m forward of the sonic anemometer. Note the LiCOR LI-7500 CO2 data are generally not suitable for flux measurements at sea. Only the water vapour signal has been used for flux analysis. Data times were truncated to match those from the sonic anemometer and the internal lag was corrected for. Users should also note that the instrument's temperature and pressure measurements are made inside the interface box. Temperature is thus likely to be high due to solar heating of box, and pressure will be biased low (box is ~3 m below sensor) and may be subject to dynamic pressure fluctuations resulting from airflow around pressure inlet. Measurements are made at 20 Hz frequency. The Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat. ACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud. The UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.

This dataset contains measurements of enrichment of 14C in carbon dioxide in air taken from Tacolneston tower. The samples were taken at 185m and analysed by Aerosol Mass Spectrometer (AMS) at Keck-Carbon Cycle AMS facility, University of California, Irvine. 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, 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 measurements of enrichment of 14C in carbon dioxide in air taken from the sampling tower at Mace Head Observatory. The samples were taken at 185m and analysed by Aerosol Mass Spectrometer (AMS) at Keck-Carbon Cycle AMS facility, University of California, Irvine. 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 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

This dataset contains coupled physical-biogeochemical ocean second generation Institut Pierre-Simon Laplace (IPSL-CM5A-LR) 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: IPSL-CM5A-LR surface fluxes: RCP85: u-ao559 (copy from u-ao419, change model names, restart + reduce walltime for nemo to test) Failed in nemo_cice 20431201: v10 not found in y2044 (and same for the years after) => download,merge,transfer,re-run => fixed RCP26: u-ao562 (copy from u-ao559 and change rcp26 surface fluxes) Constant atm CO2: RCP85: u-ao563 (copy from u-ao559 with cst atm changes) RCP26: u-ao564 (copy from u-ao562 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.

This dataset contains 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 - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the RemoTeC SRFP Full Physics Retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints. These data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme.

This dataset contains coupled physical-biogeochemical ocean second generation Met Office (HadGEM2-ES) 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: HadGEM2-ES surface fluxes (2099 for rcp85 not resolved yet) (runs started on 26th July) RCP85: u-ao789 (nov 2099)(copy from u-ao559,change model name, restart path, and surface fluxes files) RCP26: u-ao790 (nov 2099) (copy from u-ao789,change rcp26 surface fluxes) Constant atm CO2 RCP85: u-ao791 (nov 2099) (copy from u-ao789 with cst atm changes) RCP26: u-ao793 (nov 2099) copy from u-ao790 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.