Procedure Computation List

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        {
            "ob_id": 26905,
            "uuid": "88a1c5eaa1994bdf8ec56aad9da20167",
            "title": "UKCP18 Climate Simulations from Europe Regional Climate Model Realisations",
            "abstract": "The climate model projections are all variants of the limited-area atmosphere-only version of the Met Office Hadley Centre Global Environmental model (HadGEM3). They provide downscaled projections for the UK or Europe, driven by an ensemble of 60km Hadley Centre global coupled models HadGEM3-GC3.05.\n\nThis dataset consists of 12 projections from the 12km HadREM3-GA705 model. The model spans Europe and is driven by the 60km HadGEM3-GC3.05 global coupled model (GCM) perturbed-physics ensemble, with perturbations applied to the 12km RCM consistent with the driving GCM. All models are configurations of the Unified Model.\n\nThere are discontinuities in the data on 1st Dec 2020 and 1st Dec 2060, due to the simulations being conducted as three separate time slices.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 26910,
            "uuid": "cb0903908c3145029f39299f417a159d",
            "title": "QA4ECV computation to produce polar sea-ice data",
            "abstract": "This dataset was created using a specially processed MISR sea ice albedo product (that was generated at Langley Research Center using Rayleigh correction) combining this with a cloud mask of a sea ice mask product, MOD29, which is derived from the MODerate Resolution Imaging Spectroradiometer (MODIS), which is also, like MISR, onboard the Terra satellite.\r\n\r\nFour daily sea ice products have been created, each with a different averaging time window (24 h, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of MISR cloud-free sea ice albedo is calculated. These products are on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km).",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 26931,
            "uuid": "fd310daa42fd4f18a7f73aee86a248ff",
            "title": "Derivation of the EUSTACE land station daily air temperature measurements with  non-climatic discontinuities identified",
            "abstract": "The EUSTACE dataset, 'Global land station daily air temperature measurements with non-climatic discontinuities applied, for 1850-2015', has been  produced by bringing together daily maximum and minimum temperatures from various public databases (GHCN-D, ECA&D, DECADE, ISTI and ERA-CLIM).  These data have then been quality controlled through the removal of duplicates and unreliable data sources, and were assessed for homogenity by applying tests to look for breakpoints in the time series.\r\nThe data were also assessed to provide a rough estimation of the reporting resolution for each year in the series.\r\n\r\nFor further details see the EUSTACE product user guide.\r\n\r\nThe following datasets have been used as input:\r\nGlobal Historical Climatology Network (GHCN)-Daily v3.22 (Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., & Houston, T. G. (2012). An overview of the global historical climatology network-daily database. Journal of Atmospheric and Oceanic Technology, 29(7), 897-910.); European Climate Assessment & Dataset (ECA&D) – October 2016 update (Klein-Tank, A., Wijngaard, J. B., Können, G. P., Böhm, R., Demarée, G., Gocheva, A., et al. (2002). Daily dataset of 20th‐century surface air temperature and precipitation series for the European Climate Assessment. International Journal of Climatology, 22(12), 1441-1453.); International Surface Temperature Initiative (ISTI) v1.00 (Rennie, J. J., Lawrimore, J. H., Gleason, B. E., Thorne, P. W., Morice, C. P., Menne, M. J., et al. (2014). The international surface temperature initiative global land surface databank: Monthly temperature data release description and methods. Geoscience Data Journal, 1(2), 75-102.); Project DECADE (Hunziker, S., Gubler, S., Calle, J., Moreno, I., Andrade, M., Velarde, F., et al. (2017). Identifying, attributing, and overcoming common data quality issues of manned station observations. International Journal of Climatology, 37(11), 4131-4145.); Projects ERA-CLIM / ERA-CLIM2 (Stickler, A., Brönnimann, S., Valente, M. A., Bethke, J., Sterin, A., Jourdain, S., et al. (2014). ERA-CLIM: historical surface and upper-air data for future reanalyses. Bulletin of the American Meteorological Society, 95(9), 1419-1430.)",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 26984,
            "uuid": "8f67b480b9ab4cfda3a24cfed9baa1b5",
            "title": "Met Office Hadley Centre regional climate models HadGEM3-RA and HadRM3P for CORDEX EUR-44",
            "abstract": "Met Office Hadley Centre regional climate models HadGEM3-RA and HadRM3P running simulations of the European domain at 0.44 degree resolution (EUR-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadGEM3-RA is a regional atmospheric model that is based on the atmospheric component of  the HadGEM3 Global Environment Model. \r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, EUR-44, HadGEM3-RA, HadRM3P, HadGEM3, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 26991,
            "uuid": "2d11ff4b60b44a3f8e4047c4018b2348",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX EUR-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the European domain at 0.44 degree resolution (EUR-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, EUR-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27024,
            "uuid": "e09c154de1cb4d6788ce6c6255e28471",
            "title": "Ensemble prediction from multiple Radom Forest Regressor models.",
            "abstract": "The Radom Forest Regressor is a machine learning algorithm, that builds non-parameteric predictions of a target variable based on other input data or \"features\". Here, multiple Radom Forest Regressor models have been combined to make an ensemble prediction. See related documents for more information.\r\n\r\nMutiple open-source Python packages were used to built this dataset and its output, including: Pandas (Wes McKinney, 2010), Xarray (Hoyer and Hamman, 2017) and Scikit-learn (Pedregosa et al., 2011), and the xESMF package (Zhuang, 2018)\r\n\r\nInputs used were sea-surface iodide observations and existing datasets of ancillary chemical and physical variables described. Iodide observations are described by Chance et al. (2019b) and made available by the British Oceanographic Data Centre 30 (BODC, Chance et al. (2019); DOI:10/czhx). Ancillary data extracted for Chance et al. (2019) observation locations and globally to predict spatial fields as available from sources stated in Table 1 in the accompanying paper (Sherwen et al 2019).",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27049,
            "uuid": "d9d7e0edaef7439baebe9cec89851d00",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX EAS-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the East Asia domain at 0.44 degree resolution (EAS-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, EAS-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27056,
            "uuid": "b29dfce5998c4c789a29702508d2a044",
            "title": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "abstract": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27060,
            "uuid": "34c867fcbc414285b5941dbae6c121c1",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX AUS-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the Australasia domain at 0.44 degree resolution (AUS-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, AUS-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27066,
            "uuid": "0faed9d18356467c9d8ce52390f40009",
            "title": "Calving Front locations derived by the ESA Greenland Ice Sheets Climate Change Initiative project.",
            "abstract": "Calving Front Locations have been derived for Glaciers on the Greenland Ice Sheet as part of the ESA Greenland Ice Sheet Climate Change Initiative project.  The calving front locations have been derived by manual delineation using ERS-1/2, Envisat and Sentinel-1 SAR (Synthetic Aperture Radar) data and LANDSAT 5,7,8 satellite imagery. The digitized calving fronts are stored in ESRI vector shape-file format and include metadata information on the sensor and processing steps in the corresponding attribute table.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27078,
            "uuid": "f3e1c72e32a444cd8026adf1be6c155e",
            "title": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "abstract": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27083,
            "uuid": "f1cc63a9c346425b858afc78fa06895b",
            "title": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "abstract": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27086,
            "uuid": "ddae804ca52d484b91c38ff761e375ba",
            "title": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "abstract": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27091,
            "uuid": "33c8c674607d4ee88160d35f23282fa0",
            "title": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "abstract": "Polar-optimised Weather Research and Forecasting (PWRF) model (version 3.6.1) on the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27095,
            "uuid": "84b90ff6b7c24f22891892275446403e",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX NAM-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the North America domain at 0.44 degree resolution (NAM-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, NAM-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27097,
            "uuid": "d45df8ad3fa4494dba2c287a78438a1a",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX SAM-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the South America domain at 0.44 degree resolution (SAM-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, SAM-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27100,
            "uuid": "78baf096d1be4a4086c8fb0afb7a3189",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX CAS-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the Central Asia domain at 0.44 degree resolution (CAS-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, CAS-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27116,
            "uuid": "1f7b5a3c5b774eaaba2abbe1c9f21c19",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX ANT-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the Antarctica domain at 0.44 degree resolution (ANT-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, ANT-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27118,
            "uuid": "051fe2b39383413e943eb942deb5c0c1",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX ARC-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the Arctic domain at 0.44 degree resolution (ARC-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, ARC-44, HadRM3P, HadCM3",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27119,
            "uuid": "a0400dada10f46f9916a38c3e4276601",
            "title": "Algorithm for the  ESA Soil Moisture Climate Change Initiative",
            "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors.   For information on the algorithm see the Algorithm Theoretical Baseline Documents.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27145,
            "uuid": "0f6d3fc3f6984e75a05aebcf334e32c0",
            "title": "Met Office Hadley Centre regional climate models HadGEM3-RA and HadRM3P for CORDEX AFR-44",
            "abstract": "Met Office Hadley Centre regional climate models HadGEM3-RA and HadRM3P running simulations of the Africa domain at 0.44 degree resolution (AFR-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadGEM3-RA is a regional atmospheric model that is based on the atmospheric component of  the HadGEM3 Global Environment Model. \r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, Africa, AFR-44, HadGEM3-RA, HadRM3P, HadGEM3, HadCM3, region 4",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27146,
            "uuid": "1d791e601e4d4cafb83db2244b8a3821",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX AFR-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the Africa domain at 0.44 degree resolution (AFR-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, Africa, AFR-44, HadRM3P, HadCM3, region 4",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27161,
            "uuid": "d9ede438de31435a96fd946e0b8bf7f1",
            "title": "Met Office Hadley Centre regional climate model HadRM3P for CORDEX WAS-44",
            "abstract": "Met Office Hadley Centre regional climate model HadRM3P running simulations of the West Asia domain at 0.44 degree resolution (WAS-44) for the Co-Ordinated Regional Downscaling Experiment (CORDEX).\r\n\r\nHadRM3P is a regional climate model based on the HadCM3 Coupled Climate Model.",
            "keywords": "CORDEX, West Asia, WAS-44, HadRM3P, HadCM3, region 4",
            "inputDescription": 6,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27171,
            "uuid": "021e524dfb064502b3eec9434514ff7b",
            "title": "Derivation of the EUSTACE/AASTI global clear-sky ice surface temperature data from the AVHRR series on the satellite swath with estimates of uncertainty components",
            "abstract": "Global clear-sky ice surface temperature data has been derived from thermal infrared satellite measurements from the AVHRR (Advanced Very High Resolution Radiometer) series.\r\n\r\nFor information on the algorithms used to derive this data see e.g. the EUSTACE scientific user guide (coming soon).",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27185,
            "uuid": "9692143d57aa413eab1277193361de77",
            "title": "Climatic Research Unit (CRU) procedure to produce the CRU JRA data.",
            "abstract": "The CRU JRA (Japanese reanalysis) data is a replacement to the CRU NCEP dataset, CRU JRA data follows the style of Nicolas Viovy's original dataset rather than that which is available from UCAR.\r\n\r\nThe CRU JRA dataset is based on the JRA-55 reanalysis dataset and aligned where appropriate with the CRU TS dataset version 3.26 (1901-2017).\r\n\r\nAll JRA variables are regridded from their native TL319 Gaussian grid to the CRU regular 0.5° x 0.5° grid, using the g2fsh spherical harmonics routine from NCL (NCAR Command Language), based on the 'Spherepack' code. The exception is precipitation, which is regridded using ESMF 'nearest neighbour': all other algorithms tried exhibited unwanted artifacts.\r\n\r\nThe JRA-55 reanalysis dataset starts in 1958. The years 1901-1957 are constructed using randomly-selected years between 1958 and 1967. Where alignment with CRU TS occurs, the relevant CRU TS data is used.\r\n\r\nOf the ten variables listed above, the last four do not have analogs in the CRU TS dataset. These are simply regridded, masked for land only, and output as CRUJRA. The other six are aligned with CRU TS as follows:\r\n\r\nTMP is aligned with CRU TS TMP. A monthly mean for the JRA data is\r\ncalculated and compared with the equivalent CRU TS mean. The difference\r\nbetween the means is added to every JRA value.\r\n\r\n---\r\n\r\nTMAX and TMIN are aligned with CRUJRA TMP and CRU TS DTR. Firstly, at\r\neach time step, the TMAX-TMP-TMIN triplets are checked and adjusted so\r\nthat TMAX is always >= TMP, and TMIN is always <= TMP. This triplet\r\nalignment is prioritised above DTR alignment. Secondly, monthly JRA DTR\r\nis calculated by first establishing the daily maxima and minima (max and\r\nmin of the subdaily values in TMAX and TMIN respectively), then monthly\r\nmaxima and minima, (means of the daily DTR values), giving JRA monthly\r\nDTR. This is compared with CRU TS DTR and the fractional difference\r\n(factor) calculated as (CRU TS DTR) / (JRA monthly DTR). This factor is\r\nthen used to adjust the DTR of each pair of subdaily TMAX and TMIN\r\nvalues, though not if the triplet alignment would be broken.\r\n\r\n---\r\n\r\nPRE is aligned with CRU TS PRE and WET (rain day counts). Firstly, the\r\nmonthly total precipitation is calculated for JRA and compared to CRU TS\r\nPRE; an adjustment factor is acquired (crupre/jrapre) and all values\r\nadjusted. Precipitation amounts are now aligned at a monthly level, and\r\nthis alignment is prioritised above WET alignment. Secondly, the number\r\nof rain days is calculated for JRA: a day is declared wet if the total\r\nprecipitation is equal to, or exceeds, 0.1mm (the same threshold as CRU\r\nTS WET). If JRA has more wet days than CRU TS, then the driest of those\r\nare reduced to a random amount below 0.1 (an adjustment factor is\r\ncalculated and applied to each time step, to preserve the subdaily\r\ndistribution). If JRA has fewer wet days than CRU TS, then sufficient\r\ndry days are set to a random amount equal to or closely above 0.1mm,\r\nagain using an adjustment factor to preserve the subdaily distribution. \r\nWhere wet day alignment threatens precipitation alignment, the process\r\nis abandoned and the cell/month reverts to the previously-aligned\r\nprecip version. Exception handling is very complicated and cannot be\r\nsummarised here.\r\n\r\n---\r\n\r\nSPFH is aligned with CRU TS VAP. VAP is converted to SPFH, and JRA mean\r\nmonthly SPFH is calculated. The fractional difference (factor) is\r\ncalculated as (CRU TS SPFH) / (JRA monthly SPFH), this factor is then\r\napplied to the JRA subdaily humidity values.\r\n\r\n---\r\n\r\nDSWRF is aligned with CRU TS CLD. CLD is converted to shortwave\r\nradiation, and JRA mean monthly DSWRF is calculated. The fractional\r\ndifference (factor) is calculated as (CRU TS SWR) / (JRA monthly DSWRF),\r\nthis factor is then applied to the JRA subdaily radiation values.\r\n\r\n---\r\n\r\nWhere appropriate, CRUJRA values are kept within physically-appropriate\r\nconstraints (such as negative precipitation), which could result from\r\nregridding as well as adjustments.",
            "keywords": "Climatic Research Unit, CRU, TS, CY",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27210,
            "uuid": "7bf0c1516a6b4698954288f61f0bd2c9",
            "title": "Met Office unified model (UM) Vn7.3 deployed in a climate model configuration (HadGEM3-UKCA) on the Met Office CRAY HPC facility",
            "abstract": "Met Office unified model Vn7.3 (UM) deployed in a climate model configuration (HadGEM3-UKCA) on the Met Office CRAY HPC facility",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27369,
            "uuid": "44691ecfb5c7420f9e93dea1070d3e86",
            "title": "Global sulphur dioxide (SO2) column amounts from the Infrared Atmospheric Sounding Interferometer (IASI)",
            "abstract": "The Walker et al. (2011, 2012) linear retrieval developed for the Infrared Atmospheric Sounding Interferometer (IASI) on the Metop satellites has been used to process the IASI Metop-A data to produce an effect SO2 column amount. The linear retrieval output for each orbit has then been averaged for each month to obtain an average effective SO2 column amount in Dobson Units (DU). In this application, the retrieval uses the ν3 absorption band (centred at 7.3 μm) and SO2 was assumed to be evenly distributed between the surface and 20 km. Literature: Taylor et al. (2018) Exploring the utility of IASI for monitoring volcanic SO2 emissions, in review at JGR: Atmospheres. Walker et al. (2011) An effective method for the detection of trace species demonstrated using the MetOp Infrared Atmospheric Sounding Interferometer, Atmospheric Measurement Techniques, 4: 1567-1580, doi:10.5194/amt-4-1567-2011. Walker et al. (2012) Improved detection of sulphur dioxide in volcanic plumes using satellite-based hyperspectral infrared",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27396,
            "uuid": "28195716468d459f9d3c3860dcfa8cf9",
            "title": "ESA Fire_cci AVHRR-LTDR Burned Area algorithm",
            "abstract": "The Burned Area (BA) algorithm used for producing the Fire_CCI AVHRR-LTDR Burned Area product is described in the Fire_cci  Algorithm Theoretical Basis Document (ATBD) for the AVHRR LTDR data, available from https://climate.esa.int/projects/fire/key-documents .",
            "keywords": "",
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            "identifier_set": []
        },
        {
            "ob_id": 27402,
            "uuid": "be1daa81f36b4befa090894daec5bbef",
            "title": "Derivation of the EUSTACE European land station daily air temperature measurements, bias adjusted for 1951-2015",
            "abstract": "Details of the derivation of these datasets are given in the following papers: \r\n\r\n1) Homogenization of daily ECA&D temperature series Antonello Angelo Squintu, Gerard van der Schrier, Yuri Brugnara, Albert Klein Tank: 2018, Intern. J. Climatology (published on line), doi:10.1002/joc.5874 https://www.ecad.eu/publications/index.php. \r\n\r\n2) Building long homogeneous temperature series across Europe: a new approach for the blending of neighboring series Antonello A. Squintu, Gerard van der Schrier, Else J. M. van den Besselaar, Richard C. Cornes, Albert Klein Tank, submitted",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27404,
            "uuid": "156440fab651474498f786a80e30d023",
            "title": "Derivation of the EUSTACE in-filled analysis of European surface air temperature based on homogenised meteorological station records since 1950",
            "abstract": "This dataset has been derived by gridding European Homogenised Station data using the E-OBS methodology, as described in Cornes, R. C., van der Schrier, G., Besselaar, E. J. M., & Jones, P. D. \r\n( 2018). An ensemble version of the E‐OBS temperature and precipitation data sets. /Journal of Geophysical Research: Atmospheres/, 123, 9391– 9409. https://doi.org/10.1029/2017JD028200",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27428,
            "uuid": "86bae05470f6453eb3d3c5ceef60a031",
            "title": "TRACK computation for CMIP6 HighResMIP storm tracks",
            "abstract": "The storm tracking algorithm TRACK (Hodges, et. al., 2017) uses 850 hPa vorticity, averaged over 850, 700, 600 hPa, and filtered to T63 spectral grid, to find storm candidates. It then uses the vertical gradient of vorticity to determine if there is a warm core this with other conditions determine whether a tropical storm is identified.\r\n\r\nThe algorithm used for the storm-tracking is also described in the metadata of the track files and full details can be found in the linked documentation. \r\n\r\nThe storm tracks were calculated using the Lotus cluster at on the JASMIN compute facility at the Centre for Environmental Data Analysis (CEDA).",
            "keywords": "CMIP6, HighResMIP, TRACK, tropical, cyclone, storm tracking",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27453,
            "uuid": "c6b7896243de4f4c91eed735e61d4b69",
            "title": "Derivation of the EUSTACE globally gridded clear-sky daily air temperature estimates from satellites with uncertainty estimates for land, ocean and ice, 1995-2016",
            "abstract": "Surface air temperature estimates have been calculated from satellite-derived surface skin temperature measurements within the EUSTACE project.   Research was done to investigate the relationship between these air and skin temperatures based on temporally and spatially collocated observations, and empirical relationships have been derived.   These have then been applied to the satellite skin temperatures used in the EUSTACE project to estimate surface air temperatures.   The relationships have been derived separately for the land, ice and ocean regions, and are described further in the EUSTACE Scientific and Product User Guides.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27472,
            "uuid": "5874ad23f5cf445ea251dd1649ec1acd",
            "title": "Level 2 Methane (CH4) total column processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data",
            "abstract": "This computation involves the Level 2 processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data. The algorithm for retrieval of methane columns from the SENTINEL-5P instrument is based on earlier developments of a CO2 and CH4 retrieval algorithm from GOSAT, called RemoTeC [Butz et al., 2009; 2010; 2011; Schepers et al, 2012; Guerlet et al, 2013a].\r\n\r\nIn order to account for the effect of aerosols and cirrus, the algorithm retrieves the CH4 column simultaneously with the aerosol/cirrus amount (column integrated particle number concentration), a parameter related to the particle size distribution, and a parameter describing the height distribution. Here, the particle size distribution is described by a power-law function [Mishchenko et al, 1999] which only has two free parameters (related to amount and size). The choice of aerosol/cirrus parameters reflects the information content of the measurements as closely as possible. The retrieval algorithm uses the Level-1B reflectance measurements in the SWIR band and additionally in the NIR band between 757-774 nm (O2 A-band). Additional fit parameters are the surface albedo and its first-order spectral dependence in the two bands, and the total columns of carbon-monoxide and water vapor, respectively.\r\n\r\nIn order to obtain a proper characterisation of the retrieved CH4 column, it is important to first retrieve a vertical profile (layer averaged number density in different layers of the model atmosphere) and use this retrieved vertical profile to calculate the vertical column. It has been chosen to provide the vertical column as a product, and not the full profile because the Degrees of Freedom for Signal (DFS) of the retrieved CH4 profile is approximately 1. The inversion is performed using Phillips-Tikhonov regularization in combination with a reduced step size Gauss-Newton iteration scheme.\r\n\r\nThe forward model of the retrieval algorithm uses online radiative transfer calculations, fully including multiple scattering. Here, the radiative transfer model developed by Landgraf et al. [2001], and Hasekamp and Landgraf [2002; 2005] is being used. This model uses the Gauss-Seidel iterative method to solve the radiative transfer equation in a plane-parallel, vertically inhomogeneous atmosphere. To avoid time-consuming line-by-line calculations, the linear-k method developed by Hasekamp and Butz [2008] is employed. Absorption cross-sections of the relevant atmospheric trace gases are tabulated in a look-up table as functions of pressure and temperature. The optical properties of aerosols are also calculated from look-up tables as described in Dubovik et al. [2006].\r\n\r\nCloud Filtering\r\n\r\nAs for the CO vertical column retrieval, a pre-processing step is performed to discard ground pixels contaminated by clouds. For CH4, only cloud-free ground pixels will be kept. The baseline approach for cloud/cirrus flagging is to use the cloud mask from the VIIRS instrument (on Suomi-NPP satellite, flying in close formation with SENTINEL-5P). With its 1 km x 1 km ground pixel size, the VIIRS cloud mask is much more flexible in defining the area that is required to be cloud-free than the cloud flagging from TROPOMI itself. However, in case VIIRS data are not available, the cloud mask will be obtained from TROPOMI measurements using either:\r\n\r\n- A comparison between the apparent surface pressure in the TROPOMI Cloud Level-2 product with the \"true\" surface pressure in ECMWF.\r\n- The \"Two-band CH4 cloud filter\" and the \"Two-band H2O cloud filter\".",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27487,
            "uuid": "df039b8b3fb543fdaf9a030e8be3d507",
            "title": "TOMCAT/SLIMCAT three-dimensional offline chemical transport model used for ozone monthly data",
            "abstract": "Data were simulated using the TOMCAT/SLIMCAT three-dimensional offline chemical transport model, using σ-p vertical coordinates and identical stratospheric chemistry and aerosol loading, solar flux input and surface mixing ratios of long-lived source gases.\r\n\r\nThe long-term simulation (1979-2016) was performed with a T42 horizontal resolution of approximately 2.8° latitude × 2.8° longitude and 32 levels from the surface to 60 km. The model input used horizontal winds and temperature from the reanalysis data of the European Centre for Medium-Range Weather Forecasts.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27500,
            "uuid": "e59b793270b640b196d10c6e90292527",
            "title": "AWI-Stan0 computer",
            "abstract": "A vector super computer based on Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27504,
            "uuid": "a8a2432b702c482d86c6d4f299c0c110",
            "title": "Derivation of the EUSTACE Global daily air temperature combining surface and satellite data, with uncertainty estimates, for 1850-2015, v1.0",
            "abstract": "Global mean surface air temperature measurements have been derived daily for the period between 1850-2015 based on combined information from satellite and in-situ data sources. This data has been derived using a statistical method to estimate air temperatures at all places and times. It takes into account uncertainty in the input data sets covering errors in the in situ measurements, land station homogenisation and errors in the air temperatures estimated from satellite data . Although the statistical model estimates temperatures at all locations, the product is not globally complete, as areas with too few data to provide a reliable air temperature estimate have been masked out.   The derivation of this dataset and the statistical model used has been described further in the EUSTACE Scientific and Product User Guides.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27507,
            "uuid": "0b6dd27f98b848f2b4e92c248f86467a",
            "title": "Derivation of the EUSTACE coincident daily air temperature estimates and reference measurements, for validation",
            "abstract": "To validate the EUSTACE globally gridded clear-sky daily air temperature estimates from satellites and the the EUSTACE global daily air temperature product a set of match-up datasets containing in-situ reference and EUSTACE temperature estimates have been produced.   The matchups were produced separately for each test-reference dataset pairing. Therefore each file contains only matchups of one EUSTACE product to one in situ dataset.\r\n\r\nThe matchup process varied between platforms and as a consequence the filename format, file format and variables contained within each file depend on the matched datasets.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27543,
            "uuid": "de7376f4f7fc45b8bd4d096af5781b8c",
            "title": "Analysis Ready Sentinel 1 data using SNAP toolbox.",
            "abstract": "Using the Sentinel SNAP toolbox to process Sentinel 1 GRD products. Each file had the following workflow applied to it: Apply orbit file, Correct for border anomalies, Thermal noise correction, Radiometric calibration, Terrain correction, Geometry.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27582,
            "uuid": "932aaec12406492c8735db30ec3fa347",
            "title": "TempestExtremes computation for CMIP6 HighResMIP storm tracks",
            "abstract": "The storm tracking algorithm TempestExtremes (Ullrich and Zarzycki 2017; Zarzycki and Ullrich 2017) uses sea level pressure minima to find storm candidates. It then uses an upper level difference in geopotential height (or temperature) to determine if there is a warm core, and this together with other conditions are used to stitch the candidate points together into tracks. \r\n\r\nThe algorithm used for the storm-tracking is also described in the metadata of the track files and full details can be found in the linked documentation. \r\n\r\nThe storm tracks were calculated using the Lotus cluster at on the JASMIN compute facility at the Centre for Environmental Data Analysis (CEDA).",
            "keywords": "CMIP6, HighResMIP, TempestExtremes, tropical, cyclone, storm tracking",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27591,
            "uuid": "3ed17f86f27c4e2b863366565f2d3014",
            "title": "Derivation of the ESA CCI Sea Surface Temperature Level 4 product (CDR v2)",
            "abstract": "The L4 Sea Surface Temperature Analysis data produced by the ESA Climate Change Initiative (CCI) consistes of daily, spatially complete estimated daily SST data, derived using the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) processing system.  This creates the L4 data from the ATSR and AVHRR Level 2 and Level 3 data sets also produced in the SST CCI.\r\n\r\nFor further information please see the SST CCI product user guide.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27612,
            "uuid": "9bcc836d46314fba8cdb81f07ae9a280",
            "title": "Fast-JX photolysis model",
            "abstract": "The Fast-JX column photolysis model was used at Lancaster University to simulate column profiles of photolysis rates (JO3 and JNO2) centred on the Institute of Atmospheric Physics (IAP) tower site in Beijing for use by the projects under the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. The photolysis rate profiles are simulated under different aerosol loadings to represent the optical effects of individual species and cloud cover on photochemistry.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27625,
            "uuid": "dacf4b75c9f44a3ebe52e9a093eb397a",
            "title": "Standardized Precipitation Evapotranspiration Index (SPEI)",
            "abstract": "The Standardized Precipitation Evapotranspiration Index (SPEI) is an extension of the widely used Standardized Precipitation Index (SPI).",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27642,
            "uuid": "9a33d1b3c6da4aeba3e530dd3efb03e3",
            "title": "Global Land Cover Maps, Version 2.0.7",
            "abstract": "The set of annual land cover (LC) maps are  derived from a unique baseline LC map which is generated thanks to the entire MERIS FR (Full Resolution) and RR (Reduced Resolution) archive from 2003 to 2012. Independently from this baseline, LC changes are detected at 1 km based on a time series of annual global classifications generated from AVHRR HRPT (1992 - 1999), SPOT-Vegetation (1999 - 2012) and PROBA-V (2013 - 2015). Systematic analysis of the temporal trajectory of each pixel allowed the depiction of the major changes for a simplified land cover typology matching the IPCC classes. These classes are: cropland, forest, grassland, wetlands, settlements and other lands; the latter class being further split into shrubland, sparse vegetation, bare area and water.\r\n\r\nWhen MERIS FR or PROBA-V time series are available, the changes detected at 1km are re-mapped at 300 meters. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27650,
            "uuid": "a64ba9f637e2480281b82b8b08385391",
            "title": "UK Met Office Daily Weather Reports (DWR)",
            "abstract": "UK Met Office Daily Weather Reports (DWR) digitised from the Met Office.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27704,
            "uuid": "5a3bc525bb384291881b16c9aff89365",
            "title": "BACI State Surface Vector Computation (SSV)",
            "abstract": "The main requirement for BACI SSV dataset was  to provide frequent time series of remote sensing information in different domains of electromagnetic spectrum covering largest possible regions. It was important to have data which allows  change detection to be as precise as possible without attribution. The dataset  combines layers of optical, thermal infrared and microwave data providing comprehensive set of information. \r\n\r\nThe process used MODIS reflectance, MODIS land surface temperature and Sentinel-1 VV/VH backscatter. It also employed  linear Kernel BRDF models to normalise reflectance to nadir view. i.e.and an inversion of the Kernel models to obtain kernels and then it is easy to calculate reflectance at nadir. In the case of thermal and SAR information the process used identity operator i.e. smoother to fill gaps and estimate uncertainty. This allows minimum loss of information and makes data sets compatible.\r\nThe main difference between SSV datasets and conventional way of representing data is availability of information about associated uncertainties.  This allows to see the extent to which we can trust specific pixel at specific date/time. Most of the conventional change detection and time series decomposition methods do not take uncertainty into account. This can lead to misinterpretation of data due to atmospheric effects, processing or model errors. The result was smooth continuous time series with associated uncertainties and restored time/space gaps. We exploit temporal regularization which was presented in see {Quaife2010} and {Lewis2012a} in data set documentation). This technique allows filling gaps in the time series of parameters and explicitly characterize the output uncertainties.\r\n\r\nInputs to the BACI SSV are MODIS daily reflectance and LST data, Sentinel 1 backscatter and historical microwave (ENVISAT ASAR). A  key  innovation  of  the  BACI  SSV  processing  chain  is  the  use  of  the  multitasking  facilities  of  CEMS/JASMIN cluster to process almost 20 years of EO data across domains .",
            "keywords": "BACI, SSV",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27708,
            "uuid": "e0118026c51243aca67de54a777648bb",
            "title": "HadGEM3 GC2",
            "abstract": "The Hadley Centre Global Environmental Model version 3 at the Global Coupled model 2.0 (HadGEM3 GC2) configuration (Williams et al 2015). HadGEM3 GC2 has atmospheric resolution of 0.83° longitude by 0.55° latitude (about 60km at mid-latitudes), with 85 atmospheric levels, and an ocean resolution is 0.25° with 75 quasi-horizontal levels. The simulations are all prescibed with preindustrial CO2 and a 1850 climatological estimate of ozone.\r\n\r\nEach set is from the same initial conditions (ocean and ice initial conditions from the HadGEM3 GC2 simulation anude, year specified below)\r\nExperiment set 1 is comprised of:\r\nCONTROL EXPERIMENT (C)\r\nTSI = 1361\r\nLOWERED TSI EXPERIMENT (T)\r\nTSI lowered by 0.5\r\nUV PERTURBATION EXPERIMENT (U) \r\nTSI lowered by 0.5 plus P, UV lowered by P\r\nCOMPENSATION UV PERTURBATION (P).\r\nTSI lowered by 0.5, UV lowered by P, Compensatory increase in other spectral bands by total of P\r\nExperiment sets 2-4 are comprised of C, U and P, and experiment sets 5? 8 are comprised of C, T and U. \r\nSet 1: ar181 (C), as241 (T ), as838 (U), at451 (P), initialised from 2300 of anude\r\nSet 2: av313 (C), av314 (U), ax732 (P), initialised from 2390 of anude\r\nSet 3: ax378 (C), ay335 (U), az416 (P), initialised from 2350 of anude\r\nSet 4: ax610 (C), az258 (U), az780 (P), initialised from 2410 of anude\r\nSet 5: ba394 (C), ba397 (U),  bg183 (T), initialised from 2380 of anude\r\nSet 6: ba695 (C), bb689 (U),  bg162 (T), initialised from 2360 of anude\r\nSet 7: bc059 (C), bc456 (U),  bg189 (T), initialised from 2320 of anude\r\nSet 8: bd385 (C), bd389 (U),  bg190 (T), initialised from 2360 of anude}",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27724,
            "uuid": "cf673e91bd70404c9b255d37635b525a",
            "title": "Chemical Ablation Model (CABMOD)",
            "abstract": "CABMOD computes the temperature, velocity, altitude and elemental composition as a function of time for a particle entering the Earth’s atmosphere with a given initial velocity, size and zenith angle. At each iteration, the ablation into the gas phase of elemental and molecular species is calculated.\nGiven a specific temperature profile, it can compute the ablation of elements if this temperature profile is applied to a particle (allows direct comparison with laboratory data).\n",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27741,
            "uuid": "707d3c37b8874838bfb50fd00c60154b",
            "title": "FIDUCEO Project Microwave FCDR Computation V4.1",
            "abstract": "Generated with FCDR_generator.m v4.1 (AMSU-B, MHS, SSMT2): See project docs for software and computation process and link to V4.1 processing software on Git Hub",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27749,
            "uuid": "4478a940b5d8482c9ebf4f5b115285c3",
            "title": "FIDUCEO UTH CDR computation V1.2",
            "abstract": "FIDUCEO UTH CDR computation V1.2 was generated from the FIDUCEO microwave FCDR",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27758,
            "uuid": "311661a2624a495080d9bbbf43874a66",
            "title": "FIDUCEO AOT and Albedo CDR v0.1.1",
            "abstract": "The FIDUCEO Aerosol Optical Depth and Albedo V0.1.1 data sets where generated in the same computational processed from  the FIDUCEO MVIRI FCDRs archived at EUMETSAT.  See MVIRI report and software links in documnetation for further detail.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27765,
            "uuid": "fda98d94c3af4c76841525845e1d93dd",
            "title": "UKCP18 Climate Simulations from Europe Regional Climate Model Realisations",
            "abstract": "The climate model projections are all variants of the limited-area atmosphere-only version of the Met Office Hadley Centre Global Environmental model (HadGEM3). They provide downscaled projections for the UK or Europe, driven by an ensemble of 60km Hadley Centre global coupled models HadGEM3-GC3.05.\n \nThis dataset consists of 12 projections from the 12km HadREM3-RA11M model. The model spans the UK and is driven by perturbed variants of the Met Office Unified Model Global Atmosphere GA7 model (HadREM3-GA705) at 12km resolution.  The HadREM3-GA705 models were driven by perturbed variants of the global climate model, HadGEM3-GC3.05. Perturbations applied to the 12km RCM are consistent with the driving global climate model.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27768,
            "uuid": "78d77d6837254d7790e584dc4fed846f",
            "title": "UKCP18 Climate Realisations for UK Administrative Regions from Europe Regional Climate Model Realisations",
            "abstract": "The climate model projections are all variants of the limited-area atmosphere-only version of the Met Office Hadley Centre Global Environmental model (HadGEM3). They provide downscaled projections for the UK or Europe, driven by an ensemble of 60km Hadley Centre global coupled models HadGEM3-GC3.05.\n \nThis dataset consists of 12 projections from the 12km HadREM3-RA11M model. The model spans the UK and is driven by perturbed variants of the Met Office Unified Model Global Atmosphere GA7 model (HadREM3-GA705) at 12km resolution.  The HadREM3-GA705 models were driven by perturbed variants of the global climate model, HadGEM3-GC3.05. Perturbations applied to the 12km RCM are consistent with the driving global climate model.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27771,
            "uuid": "423bfcc12ed448fc9f4d78edadcf363d",
            "title": "UKCP18 Climate Realisations for UK Country Regions from Europe Regional Climate Model Realisations",
            "abstract": "The climate model projections are all variants of the limited-area atmosphere-only version of the Met Office Hadley Centre Global Environmental model (HadGEM3). They provide downscaled projections for the UK or Europe, driven by an ensemble of 60km Hadley Centre global coupled models HadGEM3-GC3.05.\n \nThis dataset consists of 12 projections from the 12km HadREM3-RA11M model. The model spans the UK and is driven by perturbed variants of the Met Office Unified Model Global Atmosphere GA7 model (HadREM3-GA705) at 12km resolution.  The HadREM3-GA705 models were driven by perturbed variants of the global climate model, HadGEM3-GC3.05. Perturbations applied to the 12km RCM are consistent with the driving global climate model.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27774,
            "uuid": "9444fd31801d4745802ff6ac8b7d0a61",
            "title": "UKCP18 Climate Realisations for UK River Basin Regions from Europe Regional Climate Model Realisations",
            "abstract": "The climate model projections are all variants of the limited-area atmosphere-only version of the Met Office Hadley Centre Global Environmental model (HadGEM3). They provide downscaled projections for the UK or Europe, driven by an ensemble of 60km Hadley Centre global coupled models HadGEM3-GC3.05.\n \nThis dataset consists of 12 projections from the 12km HadREM3-RA11M model. The model spans the UK and is driven by perturbed variants of the Met Office Unified Model Global Atmosphere GA7 model (HadREM3-GA705) at 12km resolution.  The HadREM3-GA705 models were driven by perturbed variants of the global climate model, HadGEM3-GC3.05. Perturbations applied to the 12km RCM are consistent with the driving global climate model.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 27777,
            "uuid": "9afb0d55f4ca4410822417d6c524d292",
            "title": "UKCP18 Climate Realisations for UK on OSGB grid from Europe Regional Climate Model Realisations",
            "abstract": "The climate model projections are all variants of the limited-area atmosphere-only version of the Met Office Hadley Centre Global Environmental model (HadGEM3). They provide downscaled projections for the UK or Europe, driven by an ensemble of 60km Hadley Centre global coupled models HadGEM3-GC3.05.\n \nThis dataset consists of 12 projections from the 12km HadREM3-RA11M model. The model spans the UK and is driven by perturbed variants of the Met Office Unified Model Global Atmosphere GA7 model (HadREM3-GA705) at 12km resolution.  The HadREM3-GA705 models were driven by perturbed variants of the global climate model, HadGEM3-GC3.05. Perturbations applied to the 12km RCM are consistent with the driving global climate model.\n \nThe convection-permitting climate model data has been interpolated using a conservative regridding scheme to the Ordnance Survey's British National grid.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28022,
            "uuid": "aee5aafba1564245ba1e0d0590e47f85",
            "title": "UoL_FP: University of Leicester Full-Physics retrieval algorithm for retrieval of Solar Induced Fluorescence",
            "abstract": "The UoL-FP algorithm has been specially modified for use with Solar Induced Fluorescence (SIF).  See the linked documentation for a description on both.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28036,
            "uuid": "9d1f81e93ebd495286431a42dde0d459",
            "title": "Regional GA7 configuration of Met Office unified model (UM)",
            "abstract": "These simulations used the Met Office Unified Model (UM) deployed on Met Office Computer network. The Unified Model is the name given to the suite of atmospheric and oceanic numerical modelling software developed and used at the Met Office. For these experiments the regional GA7 configuration of Unified Model is used over Africa with either a 4.5 km or 25 km horizontal grid spacing at the equator.",
            "keywords": "ukmo, um",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28084,
            "uuid": "c1314c3bd26d4b3abbe61bc2209b035f",
            "title": "National Center for Atmospheric Research (NCAR) running: experiment ssp126 using the CESM2 model.",
            "abstract": "National Center for Atmospheric Research (NCAR) running the ssp126 experiment using the CESM2 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, NCAR, CESM2,ssp126, AERmon, AERmonZ, Amon, CFmon, Eday, EdayZ, Emon, LImon, Lmon, Oday, Ofx, Omon, Oyr, SIday, SImon, day, fx",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28089,
            "uuid": "e420397bfa0c430db23807b8ac60f0b2",
            "title": "Met Office Hadley Centre (MOHC) running: experiment 1pctCO2 using the HadGEM3-GC31-LL model.",
            "abstract": "Met Office Hadley Centre (MOHC) running the 1pctCO2 experiment using the HadGEM3-GC31-LL model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, MOHC, HadGEM3-GC31-LL,1pctCO2, AERday, AERmon, AERmonZ, Amon, CFday, CFmon, Eday, EdayZ, Emon, EmonZ, LImon, Lmon, Oday, Omon, SIday, SImon, day",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28092,
            "uuid": "14a8098d70714cc1bf38f9dbcb82e5ed",
            "title": "FIDUCEO: AVHRR Fundamental Climate Data Record V1.0",
            "abstract": "The L1B data were generated from the onboard AVHRR instrument flying on various NOAA satellites, and subsequently processed by NOAA and archived in CLASS.  The FIDUCEO team obtained the L1B data from the NOAA CLASS archive and processed it version v1.00 of the FCDR_AVHRR software. Please see the documentation for further information The data was produced using PATMOS-x Nov 2015 set of coefficients from CSPP.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28104,
            "uuid": "dd3bf5ee0cf14645af95ac5aff7eb39a",
            "title": "FIDUCEO: HIRS Fundamental Climate Data Record V1.0",
            "abstract": "Core input data are L1B data files obtained from the NOAA CLASS archive, Spectral response functions are  obtained from NOAA NESDIS STAR, PRT coefficients are obtained from CPIDS and also provided by NOAA and it was processed using version v1.00 of the FCDR_HIRS software. Please see documentation for further information",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28108,
            "uuid": "afce14d2a21c4d3592a63c4ae60a5703",
            "title": "FIDUCEO: AVHRR Enseble Fundamental Climate Data Record V1.0",
            "abstract": "The ensemble dataset was generated by first perturbing all of the input values (recorded counts, temperatures etc.) as well as model values (calibration coefficients and ICT temperature corrections) using their individual uncertainties as the standard deviation used in the random generation process. For single error sources which are uncorrelated a random generation scheme was used which samples the Gaussian distribution in 10 equal area segments and enables a small number of samples (in this case 10) to give a mean and variance that is closer to the expected values of zero and one than if a purely Gaussian random number generator was used. In the case of those parameters where a covariance matrix exists (the calibration parameters themselves) this was also sampled so as to capture the correct covariance with a small number of samples. The actual values of the Harmonisation/calibration parameters used for the infrared channels were generated in a two stage process. First, estimates of the non-linearity and instrument temperature terms were determined using SNO matchups using the AATSR as a reference. Then in a separate process small corrections to the bias and emissivity correction terms were found using sea surface temperature (SST) retrievals compared to the drifting buoy network to ensure that the Ensemble SST would be accurate. This was needed because the SNO matchups were concentrated at cloud like temperatures (240K-250K) and so had not sampled many SST like temperatures (>270K) leading to a small error in the Harmonised calibration for SST retrievals. When the new FCDR values are combined with the perturbed input values from the Ensemble files it is possible to generate a new set of perturbed Radiances/Brightness Temperatures which capture the underlying sources of uncertainty. These were then used as input into the AVHRR ESA CCI SST/Lake Water Surface Temperature (LWST) algorithms which also included a perturbation to the cloud detection threshold to derive a new baseline SST/LWST data together with perturbed SST/LWST values to create the SST/LWST Ensemble dataset. \r\n\r\nRelationship between the SST CDR and the ensemble\r\nThe FCDR ensemble is used to generate an SST ensemble product where the complete SST retrieval process is applied to each of the ensemble members directly generating 10 SST perturbations to the baseline SST. Also included in the SST ensemble is a variation in the cloud detection threshold which adds extra uncertainty to the ensemble in an attempt to capture uncertainties in the cloud detection process.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28111,
            "uuid": "dabd286122454a2abfd92884b6ff2f3f",
            "title": "Derivation of Ocean Colour v4 data from the ESA Climate Change Initiative Ocean Colour project (Ocean_Colour_cci)",
            "abstract": "The ocean colour CCI has calculated ocean colour Essential Climate Variable data, using input data from various satellite instruments, as part of the ESA Climate Change Initiative program.\r\n\r\nThe v4 dataset has been created by band-shifting and bias-correcting MERIS, MODIS and VIIRS data to\r\nmatch SeaWiFS data, merging the datasets and computing per-pixel uncertainty estimates.\r\n\r\nFor more information see the Ocean Colour v4 Product User Guide.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28117,
            "uuid": "2707021606b94c3d915f36f54c5bed6a",
            "title": "Met Office Hadley Centre (MOHC) running: experiment 1pctCO2-rad using the UKESM1-0-LL model.",
            "abstract": "Met Office Hadley Centre (MOHC) running the 1pctCO2-rad experiment using the UKESM1-0-LL model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, MOHC, UKESM1-0-LL, 1pctCO2-rad, AERday, AERmon, Amon, Eday, Emon, LImon, Lmon, Omon, SIday, SImon, day",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28122,
            "uuid": "16857548e5d74753a9d83e09ee652d72",
            "title": "Institut Pierre-Simon Laplace (IPSL) running: experiment piClim-aer using the IPSL-CM6A-LR model.",
            "abstract": "Institut Pierre-Simon Laplace (IPSL) running the piClim-aer experiment using the IPSL-CM6A-LR model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, IPSL, IPSL-CM6A-LR, piClim-aer, Amon, Lmon, day",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28127,
            "uuid": "b6def44b39f64906ad415f133eb69f9a",
            "title": "Institut Pierre-Simon Laplace (IPSL) running: experiment dcppC-ipv-pos using the IPSL-CM6A-LR model.",
            "abstract": "Institut Pierre-Simon Laplace (IPSL) running the dcppC-ipv-pos experiment using the IPSL-CM6A-LR model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, IPSL, IPSL-CM6A-LR, dcppC-ipv-pos, Amon, LImon, Lmon, Ofx, Omon, SImon, day",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28134,
            "uuid": "ccf861712efe4e50bf8586eb6203adf0",
            "title": "Canadian Centre for Climate Modelling and Analysis (CCCma) running: experiment faf-passiveheat using the CanESM5 model.",
            "abstract": "Canadian Centre for Climate Modelling and Analysis (CCCma) running the faf-passiveheat experiment using the CanESM5 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CCCma, CanESM5, faf-passiveheat, Amon, Eday, Lmon, Oday, Ofx, Omon, SImon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28216,
            "uuid": "fc2409b5a4974a4fa1ff0187dd2033be",
            "title": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment agzka using the HadGEM2-AO model",
            "abstract": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment, model run agzka, using the HadGEM2-AO model. See linked documentation for more information.",
            "keywords": "MOHC, HadGEM2-AO, agzka",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28217,
            "uuid": "0c1b0458cab448f88da4f04b76e2f5c7",
            "title": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment agzkb using the HadGEM2-AO model",
            "abstract": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment, model run agzkb, using the HadGEM2-AO model. See linked documentation for more information.",
            "keywords": "MOHC, HadGEM2-AO, agzkb",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28218,
            "uuid": "bd8c5c2d67934db8b3dcb0d10f488223",
            "title": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment aiklc using the HadGEM2-AO model",
            "abstract": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment, model run aiklc, using the HadGEM2-AO model. See linked documentation for more information.",
            "keywords": "MOHC, HadGEM2-AO, aiklc",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28219,
            "uuid": "e4eb21b8289a4a2a8bf7fa0e4d8c00ec",
            "title": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment ahhpa using the HadGEM2-AO model",
            "abstract": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment, model run ahhpa, using the HadGEM2-AO model. See linked documentation for more information.",
            "keywords": "MOHC, HadGEM2-AO, ahhpa",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28220,
            "uuid": "e25a68372d36489eb7e865ec5ced5b52",
            "title": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment ahisj using the HadGEM2-AO model",
            "abstract": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment, model run ahisj, using the HadGEM2-AO model. See linked documentation for more information.",
            "keywords": "MOHC, HadGEM2-AO, ahisj",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28221,
            "uuid": "f8a671760f5a4c4889b4d85835a5421e",
            "title": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment ahisb using the HadGEM2-AO model",
            "abstract": "Met Office Hadley Centre (MOHC) running Historic Anthropogenic experiment, model run ahisb, using the HadGEM2-AO model. See linked documentation for more information.",
            "keywords": "MOHC, HadGEM2-AO, ahisb",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28224,
            "uuid": "58f3982ed29f4f948160849b972bb784",
            "title": "Met Office Hadley Centre (MOHC) running: experiment abrupt-4xCO2 using the HadGEM3-GC31-LL model.",
            "abstract": "Met Office Hadley Centre (MOHC) running the abrupt-4xCO2 experiment using the HadGEM3-GC31-LL model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, MOHC, HadGEM3-GC31-LL, abrupt-4xCO2, AERmon, Amon, CFday, CFmon, Eday, EdayZ, Emon, EmonZ, LImon, Lmon, Oday, Omon, SIday, SImon, day",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28227,
            "uuid": "67ef3e67d6e7499b913df164443c54ae",
            "title": "Institut Pierre-Simon Laplace (IPSL) running: experiment ssp534-over using the IPSL-CM6A-LR model.",
            "abstract": "Institut Pierre-Simon Laplace (IPSL) running the ssp534-over experiment using the IPSL-CM6A-LR model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, IPSL, IPSL-CM6A-LR, ssp534-over, day",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28232,
            "uuid": "ef37654bf2da412099390bd2d43c8fd0",
            "title": "the CNRM-CERFACS team running: experiment 1pctCO2 using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the 1pctCO2 experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, 1pctCO2, 3hr, Amon, CFday, Lmon, Oday, Ofx, Omon, SImon, day",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28238,
            "uuid": "45966b4fcfd94bcfbc93e00cc4b43851",
            "title": "the CNRM-CERFACS team running: experiment piClim-2xdust using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with doubled emissions of dust\" (piClim-2xdust) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-2xdust, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28243,
            "uuid": "b7d30f0de38b414fb5deefce4e17cab0",
            "title": "FIDUCEO: AVHRR Lake and Sea Surface Temperature Climate Data Record V1.0",
            "abstract": "The FIDUCEO AVHRR FCDR for MetOp-A has updated calibration parameters which have been harmonised using SNO (Simultaneous Nadir Overpass) matches using the AATSR as a reference as well as corrections for some of the dominant error sources. The Ensemble version has had corrections to two of the calibration parameters (this bias term and the emissivity correction term) to improve SSTs retrieved using the FIDUCEO brightness temperatures when compared to the drifting buoy network. It therefor has mixed references, one a satellite reference and another a virtual reference consisting of radiative transfer modelled brightness temperatures derived using the SST in-situ reference data.\r\n\r\nFor full information and links to software please see the documentation section",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28250,
            "uuid": "22a24f7f6aa74fac81fdab262e460df9",
            "title": "Beijing Climate Center (BCC) running: experiment piClim-NTCF using the BCC-ESM1 model.",
            "abstract": "Beijing Climate Center (BCC) running the \"pre-industrial climatological SSTs and forcing, but with 2014 NTCF emissions\" (piClim-NTCF) experiment using the BCC-ESM1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, BCC, BCC-ESM1, piClim-NTCF, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28259,
            "uuid": "a66bbd85ccfe4d5d9227ca9085ac8b7f",
            "title": "NASA Goddard Institute for Space Studies (NASA GISS) running: experiment abrupt-4xCO2 using the GISS-E2-1-G model.",
            "abstract": "NASA Goddard Institute for Space Studies (NASA GISS) running the \"abrupt quadrupling of CO2\" (abrupt-4xCO2) experiment using the GISS-E2-1-G model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, NASA-GISS, GISS-E2-1-G, abrupt-4xCO2, 6hrPlev, 6hrPlevPt, Amon, LImon, Lmon, Omon, SImon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28264,
            "uuid": "296059622c9943af9c94fd11720f9731",
            "title": "Institut Pierre-Simon Laplace (IPSL) running: experiment omip1 using the IPSL-CM6A-LR model.",
            "abstract": "Institut Pierre-Simon Laplace (IPSL) running the \"OMIP experiment forced by Large and Yeager (CORE-2, NCEP) atmospheric data set and initialized with observed physical and biogeochemical ocean data\" (omip1) experiment using the IPSL-CM6A-LR model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, IPSL, IPSL-CM6A-LR, omip1, Oday, Odec, Ofx, Omon, SImon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28269,
            "uuid": "374c2e85a32948dbadd0aa1c2077fec9",
            "title": "Beijing Climate Center (BCC) running: experiment histSST using the BCC-ESM1 model.",
            "abstract": "Beijing Climate Center (BCC) running the \"historical prescribed SSTs and historical forcing\" (histSST) experiment using the BCC-ESM1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, BCC, BCC-ESM1, histSST, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28272,
            "uuid": "57cf8373e56542b4abd005159828ff47",
            "title": "Beijing Climate Center (BCC) running: experiment histSST-piCH4 using the BCC-ESM1 model.",
            "abstract": "Beijing Climate Center (BCC) running the \"historical SSTs and historical forcing, but with pre-industrial methane concentrations\" (histSST-piCH4) experiment using the BCC-ESM1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, BCC, BCC-ESM1, histSST-piCH4, Amon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28275,
            "uuid": "de5ef049ea1c4a11b09419c10f80ccf6",
            "title": "Beijing Climate Center (BCC) running: experiment histSST-piNTCF using the BCC-ESM1 model.",
            "abstract": "Beijing Climate Center (BCC) running the \"historical SSTs and historical forcing, but with pre-industrial NTCF emissions\" (histSST-piNTCF) experiment using the BCC-ESM1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, BCC, BCC-ESM1, histSST-piNTCF, Amon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28278,
            "uuid": "2130d577bccf46d08ce5ffe52168e2e1",
            "title": "Beijing Climate Center (BCC) running: experiment piClim-CH4 using the BCC-ESM1 model.",
            "abstract": "Beijing Climate Center (BCC) running the \"pre-industrial climatological SSTs and forcing, but with 2014 methane concentrations (including chemistry)\" (piClim-CH4) experiment using the BCC-ESM1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, BCC, BCC-ESM1, piClim-CH4, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28283,
            "uuid": "9d473d14a69e4cf790c095c26c2f7087",
            "title": "Beijing Climate Center (BCC) running: experiment ssp370SST using the BCC-ESM1 model.",
            "abstract": "Beijing Climate Center (BCC) running the \"SSP3-7.0, with SSTs prescribed from ssp370\" (ssp370SST) experiment using the BCC-ESM1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, BCC, BCC-ESM1, ssp370SST, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28286,
            "uuid": "b38e9fe3f08949d989b6bc42cfcc0f35",
            "title": "Beijing Climate Center (BCC) running: experiment ssp370SST-lowNTCF using the BCC-ESM1 model.",
            "abstract": "Beijing Climate Center (BCC) running the \"SSP3-7.0, prescribed SSTs, with low NTCF emissions\" (ssp370SST-lowNTCF) experiment using the BCC-ESM1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, BCC, BCC-ESM1, ssp370SST-lowNTCF, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28291,
            "uuid": "85d24a48778a49fca9ad23ab63082eac",
            "title": "the CNRM-CERFACS team running: experiment hist-1950HC using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"historical forcing, but with1950s halocarbon concentrations; initialized in 1950\" (hist-1950HC) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, hist-1950HC, Amon, Lmon, Omon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28294,
            "uuid": "5e5587a1bedf4601920e0e7c9680299d",
            "title": "the CNRM-CERFACS team running: experiment hist-piNTCF using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"historical forcing, but with pre-industrial NTCF emissions\" (hist-piNTCF) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, hist-piNTCF, Amon, Lmon, Omon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28297,
            "uuid": "48d94806e92b495aa7008e6cf8468937",
            "title": "the CNRM-CERFACS team running: experiment histSST-1950HC using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"historical SSTs and historical forcing, but with 1950 halocarbon concentrations. Experiment is initialized from histSST (AerChemMIP) simulation from January 1950\" (histSST-1950HC) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, histSST-1950HC, Amon, Lmon",
            "inputDescription": null,
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            "identifier_set": []
        },
        {
            "ob_id": 28300,
            "uuid": "9feb4625bca040b5bc390ae804b952ed",
            "title": "the CNRM-CERFACS team running: experiment histSST using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"historical prescribed SSTs and historical forcing\" (histSST) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, histSST, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
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            "identifier_set": []
        },
        {
            "ob_id": 28303,
            "uuid": "790f7a8dc1f748c0aa7a46af4365a371",
            "title": "the CNRM-CERFACS team running: experiment histSST-piCH4 using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"historical SSTs and historical forcing, but with pre-industrial methane concentrations\" (histSST-piCH4) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, histSST-piCH4, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
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            "identifier_set": []
        },
        {
            "ob_id": 28306,
            "uuid": "6af4f33c2aad4a5d80bbc7fd4b2136e6",
            "title": "the CNRM-CERFACS team running: experiment histSST-piNTCF using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"historical SSTs and historical forcing, but with pre-industrial NTCF emissions\" (histSST-piNTCF) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, histSST-piNTCF, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28309,
            "uuid": "5b826320d7ea4815ae14ffe54b204bf5",
            "title": "the CNRM-CERFACS team running: experiment piClim-2xDMS using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with doubled emissions of DMS\" (piClim-2xDMS) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-2xDMS, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28314,
            "uuid": "de2406b50a684c288a5cf94032e8e517",
            "title": "the CNRM-CERFACS team running: experiment piClim-2xfire using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with doubled emissions from fires\" (piClim-2xfire) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-2xfire, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28317,
            "uuid": "fc0d10269dbb44ce8dcbd06d1149d8f8",
            "title": "the CNRM-CERFACS team running: experiment piClim-2xss using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with doubled emissions of sea salt\" (piClim-2xss) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-2xss, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28320,
            "uuid": "6efe908f242241988f872b92b42587f2",
            "title": "the CNRM-CERFACS team running: experiment piClim-BC using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with 2014 black carbon emissions\" (piClim-BC) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-BC, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28323,
            "uuid": "a08cc7233de944dfafb1976ea40c3609",
            "title": "the CNRM-CERFACS team running: experiment piClim-CH4 using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with 2014 methane concentrations (including chemistry)\" (piClim-CH4) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-CH4, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28326,
            "uuid": "f66e5ad452414ede8c080836a00424cb",
            "title": "the CNRM-CERFACS team running: experiment piClim-HC using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with 2014 halocarbon concentrations (including chemistry)\" (piClim-HC) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-HC, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        },
        {
            "ob_id": 28329,
            "uuid": "ddb1265267d1474b9c720dd4b4947b3c",
            "title": "the CNRM-CERFACS team running: experiment piClim-N2O using the CNRM-ESM2-1 model.",
            "abstract": "The the CNRM-CERFACS team team consisted of the following agencies: Centre National de Recherches Météorologiques (CNRM) and Centre Européen de Recherche et Formation Avancée en Calcul Scientifique (CERFACS).the CNRM-CERFACS team running the \"pre-industrial climatological SSTs and forcing, but with 2014 N2O concentrations (including chemistry)\" (piClim-N2O) experiment using the CNRM-ESM2-1 model. See linked documentation for available information for each component.",
            "keywords": "CMIP6, WCRP, climate change, CNRM-CERFACS, CNRM-ESM2-1, piClim-N2O, Amon, Lmon",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        }
    ]
}