Get a list of Observation objects.

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            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 04.7",
            "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask.  This version of the ancillary datasets were used in the production of the v04.7 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070",
            "creationDate": "2022-07-22T09:15:57.183554",
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            "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.   This dataset forms part of the v04.7 Soil Moisture dataset (doi:10.5285/0683e320d8634a37aa1d9ef62dd41a0d) https://dx.doi.org/10.5285/0683e320d8634a37aa1d9ef62dd41a0d .",
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                "explanation": "as provided by the CCI Soil Moisture team",
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                    "uuid": "c256fcfeef24460ca6eb14bf0fe09572",
                    "short_code": "proj",
                    "title": "ESA Soil Moisture Climate Change Initiative Project",
                    "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies."
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                    "uuid": "0683e320d8634a37aa1d9ef62dd41a0d",
                    "short_code": "coll",
                    "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 04.7 data collection",
                    "abstract": "Soil Moisture data (version 04.7) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project.  This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products.   The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The COMBINED product is generated from the Level 2 active and passive instruments..  \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees.  The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD).  Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070"
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            "uuid": "0bb41477e0a5416190459433cb5ab907",
            "title": "Thermospheric cooling under RCP8.5 due to carbon dioxide increases only, select years from 1975-2095.",
            "abstract": "This dataset contains WACCM-X model results under RCP8.5 (Representative Concentration Pathway) carbon dioxide increases and low solar activity. These cover ground level to a pressure level of 4e-10 hPa (~300 km altitude) on a global 144x96 longitude-latitude grid .\r\n\r\nData is given in daily instantaneous files in the netCDF format. Default WACCM-X outputs remain, along with the following additional variables:\r\n\r\n'PS' - Surface Pressure\r\n'Z3' - Geopotential Height (above sea level)\r\n'T' - Temperature\r\n'U' - Zonal Wind\r\n'V' - Meridional Wind\r\n'CO2' - Carbon Dioxide Concentration\r\n'CO' - Carbon Monoxide Concentration\r\n'NO' - Nitric Oxide Concentration\r\n'H2O' - Water Vapour Concentration\r\n'O' - Atomic Oxygen Concentration\r\n\r\nMore detail on each variable is given within the netCDF files and the readme file.\r\n\r\n16 month runs from edited initial files at 10 year intervals from 2005 to 2095 under RCP8.5. There is also a 16 month 1975 run and 64 month 2000 run. All of these cyclically repeat the initial year. These are separated into individual folders with the RCP8.5 CO2 concentration listed. The first 4 months of each of these datasets have been ignored in processing as the model spins up, but are included here for completeness.\r\n\r\nThis data was collected to understand the density drop at low earth orbit altitudes as carbon dioxide concentrations increase.",
            "creationDate": "2022-07-22T09:15:57.183554",
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            "dataLineage": "Input data other than default is obtained from the subversion input data repository at https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/\r\n\r\nThese files changed in user_nl_cam include\r\nsolar_parms_file               = '/.../inputdata/atm/waccm/phot/wa_smin_quiet_c071210.nc'\r\n\r\nsrf_emis_specifier = 'CH2O -> /.../inputdata/atm/cam/chem/2000-2100_RCP45/IPCC_emissions_houw_CH2O_2000-2100_1.9x2.5.nc',\r\n         'CO   -> /.../inputdata/atm/cam/chem/2000-2100_RCP45/IPCC_emissions_houw_CO_2000-2100_1.9x2.5.nc',\r\n         'NO   -> /.../inputdata/atm/cam/chem/2000-2100_RCP45/IPCC_emissions_houw_NOx_2000-2100_1.9x2.5.nc'\r\n\r\naero_file     = 'aero_rcp45_v1_1.9x2.5_L26_1995-2105_c100316.nc'\r\n\r\nsolar_data_file = '/.../inputdata/atm/cam/solar/spectral_irradiance_Lean_1950-2100_daily_CCMI_Leap_c150727.nc'\r\n\r\n1975 run used all default input files. \r\n\r\nInitial conditions are those of the default year 2000 run, with CO2 and CO concentrations in the initial files edited as described within the paper (Brown et al, 2020).\r\n\r\nThe files uploaded here at CEDA are the raw files output by WACCM-X with no editing.",
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                "title": "WACCM-X as part of CESM v1.2.2",
                "abstract": "WACCM-X as part of CESM v1.2.2 - more details on request"
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                    "title": "ThermosphericCoolingWACCM-X",
                    "abstract": "Studying the future drop in thermospheric densities under increasing carbon dioxide concentrations. The rationale behind this is to understand the impact on the future space debris environment in low earth orbit."
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            "title": "APHH: Volatile organic compound (VOC) measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) field site during the DelhiFlux field campaigns",
            "abstract": "This dataset contains volatile organic compound concentration measurements made by the University of Lancaster using the UK CEH proton transfer reaction-quadrupole ion guide time of flight-mass spectrometer (PTR-QiTOF-MS). Measurements were made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) field site, Dehli, India during the DelhiFlux campaigns. Measurements from 04/10/2018 to 04/11/2018 were made at ground level (~4 m). Measurements from 05/11/2018 to 23/11/2018 were made at 30 m above ground level.  All values are reported in ppbV (parts per billion by volume).\r\n\r\nThe data were collected as part of the DelhiFlux project part of Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme.",
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                "abstract": "CEH Proton Transfer Reaction-Quadrupole ion guide Time of Flight-Mass Spectrometer (PTR-QiTOF-MS) continuously quantifies VOCs over the entire mass range in real-time delivering sub pptv-level detection limits in only a few seconds integration time."
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                    "title": "Atmospheric Pollution & Human Health in a Developing Megacity (APHH)",
                    "abstract": "The Atmospheric Pollution & Human Health in a Developing Megacity (APHH) programme has two separate streams of activity looking at urban air pollution and its impact on Health in Chinese and Indian Megacities. The programme is a collaboration between NERC, the Medical Research Council (MRC) in the UK and the National Natural Science Foundation of China (NSFC) in China, and the Ministry of Earth Sciences (MoES) and Department of Biotechnology (DBT) in India."
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                    "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux):  Atmospheric measurements",
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                    "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux): Air quality measurements",
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            "title": "APHH: Online measurements of VOC mixing ratios using Gas Chromatography with Flame Ionisation Detector (GC-FID) at Indira Gandhi Delhi Technical University for Women (IGDTUW) field site during the DelhiFlux field campaign",
            "abstract": "This dataset contains hourly online measurements of VOC mixing ratios using Gas Chromatography with Flame Ionisation Detector (GC-FID) at Indira Gandhi Delhi Technical University for Women (IGDTUW), Dehli, India. Mixing ratios are reported in parts per billion by volume (ppbV). The stationary inlet was located on the roof of a single-story building. This data was collected\r\nover two measurements periods (28/05/2018 - 05/06/2018 and 05/10/2018 - 27/10/2018), for the APHH-India DelhiFlux project, by the University of\r\nYork. Data analysis was completed by Beth Nelson and Jim Hopkins at the University of York.\r\n\r\nMixing ratios for the following species are included: ethane, ethene, propane, propane, iso-butane, n-butane, acetylene, trans-2-butene, 1-butene, iso-butene*, cis-2-butene, cyclopentane*, iso-pentane, n-pentane, 1,3-butadiene, trans-2-pentene, 1-pentene, n-octane, n-hexane, isoprene, n-heptane, benzene, toluene, ethylbenzene, combined m,p-xylene, o-xylene,\r\nmethanol, acetone, ethanol, 1,2-butadiene*, propyne*.\r\n\r\nDate and time given in Local time as Julian day where 2018 01 01 = 0\r\n\r\nCalibrations have been performed using a certified NPL 30 component mixture, and certified NPL 6 component mixture for o-VOC calibration. NOTE: any compound not contained therein has been assumed to have the same response factor as its closest isomer*.\r\n\r\nThe data were collected as part of the DelhiFlux project part of Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme.",
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                "title": "Acquisition for: Online measurements of VOC mixing ratios using Gas Chromatography with Flame Ionisation Detector (GC-FID) at Indira Gandhi Delhi Technical University for Women (IGDTUW)",
                "abstract": "Acquisition for: Online measurements of VOC mixing ratios using Gas Chromatography with Flame Ionisation Detector (GC-FID) at Indira Gandhi Delhi Technical University for Women (IGDTUW)"
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                    "title": "Atmospheric Pollution & Human Health in a Developing Megacity (APHH)",
                    "abstract": "The Atmospheric Pollution & Human Health in a Developing Megacity (APHH) programme has two separate streams of activity looking at urban air pollution and its impact on Health in Chinese and Indian Megacities. The programme is a collaboration between NERC, the Medical Research Council (MRC) in the UK and the National Natural Science Foundation of China (NSFC) in China, and the Ministry of Earth Sciences (MoES) and Department of Biotechnology (DBT) in India."
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                    "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux)",
                    "abstract": "The project, part of the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme, has four specific objectives:\r\n\r\nTo improve the emission factor database for key source types and compounds in Delhi through a combination of lab and field based emission factor measurements, using harmonised instrumentation.\r\nPrerequisite\r\n\r\nTo compile a state-of-the-art emission inventory for the greater Delhi area at a spatial resolution of (1.6 km)2, together with temporal profiles of the diurnal and seasonal variability.\r\nTo inform and evaluate this emission inventory through direct and independent emission flux measurements at the urban scale (~10 km2).\r\nTo apply atmospheric transport modelling to assess the performance of the emission inventory against concentration measurements and quantify the implications of the emissions improvements for air quality indicators.\r\n\r\nGrant Ref: NE/P016472/1"
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                    "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux):  Atmospheric measurements",
                    "abstract": "This dataset collection contains atmospheric measurements from the APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux) project."
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            "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): GHRSST Multi-Product ensemble (GMPE), v2.0",
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                "title": "ESA CCI Sea Surface Temperature Multi-Product Ensemble, v2.0",
                "abstract": "The Group for High Resolution Sea Surface Temperature (GHRSS) multi-product ensemble (GMPE) product allows comparison of different spatially complete SST analyses. This version compares seven long historical datasets: ESA SST CCI Analysis version 2.0; ESA SST CCI Analysis version 1.1; Copernicus Marine Environment Monitoring Service (CMEMS) Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Reprocessing; National Centers for Environmental Information (NCEI) Advanced Very High Resolution Radiometer (AVHRR) Optimal Interpolation (OI) Global Blended SST Analysis; Canada Meteorological Center (CMC) 0.2-degree Global Foundation SST Analysis; Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) Analysis version 2.2.0.0 (10 realisations); Japan Meteorological Agency (JMA) Merged satellite and in-situ Data Global Daily SST (MGDSST) Analysis. The GMPE includes the median and standard deviation of the input data, differences between each input and the median, and the horizontal gradients in each of the input products and the median. Data are provided on a 0.25 degree regular latitude-longitude grid and cover 1 September 1981 to 31 December 2016, although some of the input products do not cover the full period."
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                    "title": "Sea Surface Temperature Climate Change Initiative Project",
                    "abstract": "The Sea Surface Temperature Climate Change Initiative (SST_cci) project is part of the European Space Agency's Climate Change Initiative programme,  It aims to accurately mapping the surface temperature of the global oceans  using observations from many satellites, and to independently quantify SST to a quality suitable for climate research.\r\n\r\nThe team brings together European expertise in creating climate quality records of ocean temperatures from satellite data, with expertise in climate applications and computer engineering. Through the ESA funded Climate Change Initiative, the team have created a climate record of global sea surface temperature (SST) for the period 1981 to 2016. Based on satellite data, this record is independent of thermometer based measurements from ships and buoys. The new climate SST record complements and challenges existing knowledge of how ocean temperatures have evolved. \r\n\r\nThe project started in August 2010. It is part of a wider initiative by the European Space Agency (ESA) addressing several essential climate variables in addition to SST."
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                    "title": "National Centre for Earth Observation (NCEO) partnered datasets",
                    "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)."
                },
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                    "uuid": "1dc189bbf94209b48ed446c0e9a078af",
                    "short_code": "coll",
                    "title": "Collection of Sea Surface Temperature (SST) Data of the Global Oceans as part of the ESA Climate Change Initiative (CCI)",
                    "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST_cci) datasets accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThe latest version (v2.1) of the data are described in the data paper:  Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ . To comply with the attribution aspect, please cite the above reference and the dataset citation given on the relevant dataset page."
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            "title": "ECMWF ERA5: surface level forecast parameter data",
            "abstract": "This dataset contains ERA5 surface level forecast parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel and surface level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details.",
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            "dataLineage": "Data are generated by the ERA5 project at European Centre for Medium-Range Weather Forecasts (ECMWF) before being prepared by CEDA staff using the ECMWF system and uploaded to Centre for Environmental Data Analysis (CEDA) for ingestion into the archive. Data are translated over to a regular latitude-longitude grid and converted to netCDF format ahead of transfer to the CEDA system.",
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                "short_code": "comp",
                "title": "ECMWF ERA5 Re-analysis Model deployed on ECMWF Computer",
                "abstract": "This computation involved: ECMWF ERA5 Re-analysis Model deployed on ECMWF Computer.  The data assimilation system used to produce ERA5 is based on the Integrated Forecasting System (IFS)Cycle 41r2 release, with several added features specifically developed for reanalysis. The many changes and improvements incorporated into the IFS represent a decade of research and development in modelling and data assimilation. The ERA5 reanalysis benefits from research conducted in the EU-funded ERA-CLIM and ERA-CLIM2 projects carried out by ECMWF and partners. These led to improved input data for the assimilating model that better reflects observed changes in climate forcings, as well as many new or reprocessed observations for data assimilation.\r\n\r\n\r\nThe system includes :\r\n\r\n - Model input:  Appropriate for climate (e.g. CMIP5 greenhouse gases, volcanic eruptions,\r\nSST and sea-ice cover)\r\n - Spatial resolution: 31 km globally, 137 levels to 0.01 hPa\r\n - Uncertainty estimates - From a 10-member Ensemble of Data Assimilations (EDA) at 63 km resolution\r\n - Output frequency: Hourly analysis and forecast fields, 3-hourly for the EDA\r\n - Input observations: As in ERA-40 and from Global Telecommunication System. In addition, various newly reprocessed datasets and recent instruments that could not be ingested in ERA-Interim\r\n - Variational bias scheme: Satellite radiances and also ozone, aircraft and surface pressure data\r\n - Satellite data: RTTOV-11, all-sky for various components\r\n - Additional innovations: Long-term evolution of CO2 in RTTOV, cell-pressure correction SSU, improved bias correction for radiosondes, EDA perturbations for sea-ice cover"
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                }
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                    "abstract": "Major changes are occurring across the North Atlantic (NA) climate system: in ocean and atmosphere temperatures and circulation, in sea ice thickness and extent, and in key atmospheric constituents such as ozone, methane and aerosols. Many observed changes are unprecedented in instrumental records. Changes in the NA directly affect the UK’s climate, weather and air quality, with major economic impacts on agriculture, fisheries, water, energy, transport and health.  The NA also has global importance, since changes here drive changes in climate, hazardous weather and air quality further afield, such as in North America, Africa and Asia.\r\n\r\nACSIS (the North Atlantic Climate System Integrated Study) was an integrated programme of sustained observations, synthesis, and numerical modelling designed to address the overarching objective of enhancing the UK's capability to detect, attribute and predict changes in the North Atlantic (NA) Climate System, comprising: the North Atlantic Ocean, the atmosphere above it including its composition, and interactions with Arctic Sea Ice and the Greenland Ice Sheet. Specific objectives are:\r\n1. To provide the UK science community with sustained observations, data syntheses, leading-edge numerical simulations, and analysis tools, to facilitate world-class research on changes in the NA climate system and their impacts.\r\n2. To provide a quantitative, multivariate, description of how the NA climate system is changing.\r\n3. To determine the primary drivers and processes that are shaping change in the NA climate system now and will shape change in the near future.\r\n4. To determine the extent to which future changes in the NA climate system are predictable.\r\nACSIS enabled and delivered research to address the following research questions:\r\nRQ1. How have changes in natural and anthropogenic emissions and atmospheric circulation combined to shape multiyear trends in NA atmospheric composition and radiative forcing?\r\nRQ2. How have natural variability and radiative forcing combined to shape multi- year trends in the NA physical climate system?\r\nRQ3. To what extent are changes in the NA climate system predictable on multi-year timescales?\r\nACSIS was a partnership between six NERC centres (NCAS, NOC, BAS, NCEO, CPOM, PML) and the UK Met Office, exploiting the partners' unique capabilities in observing and simulating the atmosphere including its composition, the ocean, the cryosphere, and the fully coupled climate system.\r\nThe observational component brought together records from Earth-based (e.g. Cape Verde observatory, FAAM missions, RAPID, Argo, OSNAP) and spacebased (e.g. Cryosat, MetOP) platforms with a focus on the sustained observations that are necessary to measure changes on multi-year timescales.\r\nACSIS worked closely with the NERC-Met Office UKESM programme on Earth System Modelling, and contributed to and benefited from UK participation in international observing programmes such as UK-US RAPID, EU ATLANTOS and Global Atmospheric Watch, and modelling programmes such as CMIP6 and EU PRIMAVERA.\r\nThe legacy of ACSIS includes: new long-term multivariate observational datasets and syntheses; new modelling capabilities and simulations with unprecedented fidelity. ACSIS provided advances in understanding and predicting changes in the NA climate system that can be exploited in further research and related activities, for example to assess the impact of these changes on the UK and other countries - e.g. in terms of the consequences for hazardous weather risk, the environment and businesses. ACSIS outputs will also inform policy on climate change adaptation and air quality.\r\nACSIS was fully funded for five years (2016-2021)by the Natural Environment Research Council (NERC) through National Capability Long Term Science Multiple Centre (NC LTS-M) (grant NE/N018028/1) which aimed to encourage its research centres to work closely together to tackle major scientific and societal challenges. ACSIS is one of the projects funded through this new way of allocating national capability funding, designed to enable more ambitious science than any single research organisation could provide."
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            "title": "Summary for Policymakers of the IPCC Special Report: Global Warming of 1.5°C - data for Figure SPM.1 (v20200602)",
            "abstract": "Data for Figure SPM.1 from the Summary for Policymakers (SPM) of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Global Warming of 1.5°C.\r\n\r\nFigure SPM.1 relates global mean surface temperature to cumulative emissions of CO2 and visualises the probability of limiting global warming to 1.5°C. \r\n\r\n---------------------------------------------------\r\nHow to cite this dataset\r\n---------------------------------------------------\r\nWhen citing this dataset, please include both the data citation below and the following citation for the report component from which the figure originates:\r\n\r\nIPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001.\r\n\r\n---------------------------------------------------\r\nSources of additional information\r\n---------------------------------------------------\r\nLinks to Figure SPM.1 in the IPCC Special Report on Global Warming of 1.5°C, an interactive version of the figure, and supporting information in the Supplementary Material for Chapter 1 (Section 1.SM.6) can be found in the Related Documents section of this catalogue record. \r\n\r\n---------------------------------------------------\r\nFigure subpanels\r\n---------------------------------------------------\r\nThe figure has four panels, with data provided for panels (a), (b) and (d) in subdirectories named panel_a, panel_b and panel_d.  Panel (c) data can be computed from panel (b) data so are not provided here.\r\n\r\n---------------------------------------------------\r\nList of data provided\r\n---------------------------------------------------\r\nThe dataset contains global time-series data from 1960-2100 for:\r\n - Observed global temperature change (1960-2017). \r\n - Historical anthropogenic global warming (1960-2017).\r\n - Modelled warming responses to global emission and radiative forcing pathways (2018-2100).\r\n\r\nThe dataset also contains global time-series data for carbon dioxide (CO2) and non-CO2 radiative forcing from 1960-2100 for:\r\n - Historical global net CO2 emissions (1960-2017).\r\n - Stylized global net CO2 emission pathways (2018-2100).\r\n - Historical global cumulative net CO2 emissions (1960-2017).\r\n - Stylized global cumulative net CO2 emission pathways (1960-2100).\r\n - Historical global non-CO2 radiative forcing pathways (1960-2017).\r\n - Global non-CO2 radiative forcing pathways (2018-2100).\r\n\r\n---------------------------------------------------\r\nData provided in relation to figure \r\n---------------------------------------------------\r\nPanel a:\r\n - Data file: panel_a/temps_hist.csv (monthly data, 1850-2017); relates to the left part showing observed global mean surface temperature change (grey line) and estimated anthropogenic global warming (orange line with shading the assessed likely range). \r\n - Data files: panel_a/temps_blue.csv, panel_a/temps_grey.csv, panel_a/temps_purple.csv (yearly data, 2018-2100, the lower and upper bound variables are plotted). These relate to the right part showing the likely range of warming responses (grey, blue and purple plumes) for different combinations of global net CO2 emission and net non-CO2 radiative forcing pathways.  \r\nPanel b:\r\n - Data file: panel_b/gcp_out.csv (yearly data, 1960-2017); relates to the left part showing historical global net CO2 emissions (grey line). \r\n - Data file: panel_b/CO2_ems.csv (yearly data, 2018-2100, values in GtC rather than GtCO2); relates to the right part  showing two stylized future global net CO2 emission pathways (grey land blue lines). \r\nPanel d:\r\n -  Data file: panel_d/nonCO2_RF.csv (yearly data, 1960-2017, variable nonCO2RF_grey is plotted); relates to the left part showing historical global net non-CO2 radiative forcing. \r\n - Data file: panel_d/nonCO2_RF.csv (yearly data, 2018-2100, variables nonCO2RF_grey and nonCO2RF_purple are plotted); relates to the right part showing two stylized future global net non-CO2 radiative forcing pathways (grey and purple lines).",
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                "title": "Caption for Figure SPM.1 from the Summary for Policymakers of the IPCC Special Report on global Warming of 1.5°C.",
                "abstract": "Panel a: Observed monthly global mean surface temperature (GMST) (grey line up to 2017, from the HadCRUT4, GISTEMP, Cowtan–Way, and NOAA datasets)\r\nchange and estimated anthropogenic global warming (solid orange line up to 2017, with orange shading indicating assessed likely range).\r\nOrange dashed arrow and horizontal orange error bar show respectively the central estimate and likely range of the time at which 1.5°C is reached if the current rate of warming continues. \r\nThe grey plume on the right of panel a shows the likely range of warming responses, computed with a simple climate model, to a stylized pathway (hypothetical future) in which net CO2 emissions (grey line in panels b and c) decline in a straight line from 2020 to reach net zero in 2055 and net non-CO2 radiative forcing (grey line in panel d) increases to 2030 and then declines.\r\nThe blue plume in panel a) shows the response to faster CO2 emissions reductions (blue line in panel b), reaching net zero in 2040, reducing cumulative CO2 emissions (panel c). \r\nThe purple plume shows the response to net CO2 emissions declining to zero in 2055, with net non-CO2 forcing remaining constant after 2030. \r\nThe vertical error bars on right of panel a) show the likely ranges and central terciles (33rd – 66th percentiles, thick lines) of the estimated distribution of warming in 2100 under these three stylized pathways.\r\nVertical dotted error bars in panels b, c and d respectively show the likely range of historical annual and cumulative global net CO2 emissions in 2017 (data from the Global Carbon Project) and of net non-CO2 radiative forcing in 2011 from AR5 (5th IPCC Assessment Report), respectively.\r\nVertical axes in panels c and d are scaled to represent approximately equal effects on GMST. {1.2.1, 1.2.3, 1.2.4, 2.3, Figure 1.2 and Chapter 1 Supplementary Material, Cross-Chapter Box 2 in Chapter 1}."
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