Result List

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            "dataPath": "/badc/aphh/data/beijing/leeds-specrad",
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                "ob_id": 26177,
                "uuid": "76b4ad364d71465d8f8b61e302eb2c4c",
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                "title": "APHH: Solar actinic UV flux photolysis rates made at the IAP-Beijing site during the summer and winter campaigns",
                "abstract": "This dataset contains direct measurement of solar actinic UV flux from which photolysis frequencies are calculated  made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the summer and winter APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nPhotolysis rates were derived from the product of absorption cross-section of the precursor molecule, the quantum yield of the photo-product and the actinic flux density (cm-2s-1nm-1). The actinic flux is measured between 280 - 650 nm (<1 nm resolution) using a spectral radiometer attached to a quartz receiver optic. Absorption cross sections and quantum yields are taken from the latest IUPAC recommendations. The instrument was calibrated between 250 - 750 nm using a spectral Irradiance of Standard Tungsten-Halogen lamp before and after the campaign."
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                "title": "UKCP18 Global Projections by Administrative Regions over the UK for 1899-2099",
                "abstract": "Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe set of 28 projections is a combination of 15 coupled model simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5 contributed by different climate modelling centres.\r\n\r\nThis data set provides information on changes in climate across the entire globe from 1899 to 2099 for RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across many climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 16 administrative regions across the UK. Further information on this dataset and UKCP18 can be found in the documentation section."
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                "ob_id": 26195,
                "uuid": "9775420633994c5f88b20c0bd1cff548",
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                "title": "UKCP18 Global Projections for UK Countries for 1900-2100",
                "abstract": "Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe set of 28 projections is a combination of 15 coupled model simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5 contributed by different climate modelling centres.\r\n\r\nThis data set provides information on changes in climate across the entire globe from 1900 to 2100 for RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across many climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 8 \"\"country\"\" regions across the UK including England, England and Wales, Northern Ireland, Scotland, United Kingdom, Wales. Further information on this dataset and UKCP18 can be found in the documentation section."
            },
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            "dataPath": "/badc/ukcp18/data/land-gcm/uk/river",
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                "ob_id": 26198,
                "uuid": "ca1066dfa1a34b88b7774b9df6d76f6e",
                "short_code": "ob",
                "title": "UKCP18 Global Projections by UK River Basins for 1899-2099",
                "abstract": "Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe set of 28 projections is a combination of 15 coupled model simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5 contributed by different climate modelling centres.\r\n\r\nThis data set provides information on changes in climate across the entire globe from 1899 to 2099 for RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across many climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 23 river basin regions across the UK. Further information on this dataset and UKCP18 can be found at https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/using-ukcp/guidance.\""
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            "dataPath": "/badc/ukcp18/data/land-gcm/uk/60km",
            "numberOfFiles": 21415,
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                "ob_id": 26201,
                "uuid": "854bb0de8a5e4bfaafe322bbfc57ea57",
                "short_code": "ob",
                "title": "UKCP18 Global Projections on a 60km grid over the UK for 1900-2100",
                "abstract": "Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe set of 28 projections is a combination of 15 coupled model simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5 contributed by different climate modelling centres.\r\n\r\nThis data set provides information on changes in climate across the entire globe from 1900 to 2100 for RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across many climate variables at different times and spatial locations. \r\n\r\nThis dataset contains 60km for the UK only on the Ordnance Survey's British National Grid. Further information on this dataset and UKCP18 can be found in the documentation section."
            },
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            "uuid": "57de3cd6675645799899862d4d96d702",
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            "dataPath": "/badc/ukcp18/data/land-rcm/uk/region",
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            "volume": 1449539881,
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            "observation": {
                "ob_id": 26204,
                "uuid": "eabb6bced80049e790c7fe1c9e917d1e",
                "short_code": "ob",
                "title": "UKCP18 Regional Projections by Administrative Regions over the UK for 1980-2080",
                "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980,-30/11/2080 for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 16 administrative regions across the UK. Further information on this dataset and UKCP18 can be found in the documentation section."
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            "dataPath": "/badc/ukcp18/data/land-rcm/uk/country",
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            "observation": {
                "ob_id": 26207,
                "uuid": "b70faeaf5f7a445cbfde3fc968150767",
                "short_code": "ob",
                "title": "UKCP18 Regional Projections for UK Countries for 1980-2080",
                "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 8 \"\"country\"\" regions including Channel Islands, England, England and Wales, Isle of Man, Northern Ireland, Scotland, United Kingdom, Wales. Further information on this dataset and UKCP18 can be found in the documentation section."
            },
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        {
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            "dataPath": "/badc/ukcp18/data/land-rcm/uk/river",
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            "observation": {
                "ob_id": 26210,
                "uuid": "22a3c9e91b4446df9569a44e43bbfffc",
                "short_code": "ob",
                "title": "UKCP18 Regional Projections by UK River Basins for 1980-2080",
                "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 23 river basin regions across the UK. Further information on this dataset and UKCP18 can be found in the documentation section."
            },
            "onlineresource_set": []
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        {
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            "dataPath": "/badc/ukcp18/data/land-rcm/uk/12km",
            "numberOfFiles": 9801,
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            "observation": {
                "ob_id": 26213,
                "uuid": "589211abeb844070a95d061c8cc7f604",
                "short_code": "ob",
                "title": "UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080",
                "abstract": "\"Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains 12km data for the United Kingdom, the Isle of Man and the Channel Islands provided on the Ordnance Survey's British National Grid. Further information on this dataset and UKCP18 can be found in the documentation section."
            },
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        {
            "ob_id": 26217,
            "uuid": "5416c116aa7549658289f598281dda17",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/aphh/data/beijing/leeds-lif",
            "numberOfFiles": 3,
            "volume": 594072,
            "fileFormat": "Data are NASA Ames formatted",
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            "observation": {
                "ob_id": 26181,
                "uuid": "8ed84f3c770544c49329df9b068ab662",
                "short_code": "ob",
                "title": "APHH: Laser induced fluorescence (LIF) OH reactivity measurements made at the IAP-Beijing site during the winter and summer campaigns",
                "abstract": "This dataset contains Laser induced fluorescence (LIF) OH reactivity measurements made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe Leeds OH reactivity instrument measures OH reactivity by photolysing ozone at 266 nm to produce OH, decay of OH with ambient air is measured with LIF (laser induced fluorescence) at 308 nm. The results generate a bi-exponential curve and a line of best fit can be used to calculate OH lifetime. The instrument is calibrated by flowing air zero through the instrument. The units for OH reactivity is in s-1. The data has been filtered for instrument instabilities such as pressure, laser power, high background (laser scatter) and laser alignment"
            },
            "onlineresource_set": []
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        {
            "ob_id": 26218,
            "uuid": "9388e3929fb5431fbc7ba68a0da7a121",
            "short_code": "result",
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            "dataPath": "/neodc/metop_ims_ral/data/v2.1/",
            "numberOfFiles": 741201,
            "volume": 5448896138598,
            "fileFormat": "NetCDF",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26136,
                "uuid": "489e9b2a0abd43a491d5afdd0d97c1a4",
                "short_code": "ob",
                "title": "RAL Infrared Microwave Sounder (IMS) temperature, water vapour, ozone and surface spectral emissivity",
                "abstract": "The Rutherford Appleton Laboratory (RAL) Infrared Microwave Sounder (IMS) data set contains vertical profiles of temperature, water vapour, and ozone as well as surface spectral emissivity spanning infrared and microwave, surface temperature, cloud fraction and height. Data are retrieved from co-located measurements by the Infrared Atmospheric Sounding Interferometer (IASI), the Microwave Humidity Sounder (MHS) and the Advanced Microwave Sounding Unit (AMSU) on board the Eumetsat Metop satellites.\r\n\r\nDevelopment of the IMS scheme and data production were funded by the UK’s National Centre for Earth Observation (NCEO) under the Natural Environment Research Council (NERC), with additional funding from EUMETSAT contract EUM/CO/13/4600001252/THH.\r\n\r\nData were produced by the Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL).\r\n\r\nThis first public release consists of a full processing of the Metop A mission from 2007 to the end of 2016, using version 2.1 of the algorithm.\r\n\r\nIMS data are produced with the horizontal sampling of IASI, ~25 x 25 km"
            },
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        {
            "ob_id": 26223,
            "uuid": "ef0536ad2edd40feb2a46a25a15fd487",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/acites/data/htap_data",
            "numberOfFiles": 19,
            "volume": 12481830,
            "fileFormat": "Data are NetCDF formatted.",
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            "observation": {
                "ob_id": 26224,
                "uuid": "89a34bc430834422bef1f72e2172e3b9",
                "short_code": "ob",
                "title": "ACITES: Monthly global surface ozone concentration and ozone dry deposition flux fields from models",
                "abstract": "Monthly global surface ozone concentration and ozone dry deposition flux fields from models participating in the UN/ECE Task Force on Hemispheric Transport of Air Pollution (TF HTAP) intercomparison.  Models were driven by meteorological fields for the year 2001.\r\n\r\nData are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format."
            },
            "onlineresource_set": []
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        {
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            "uuid": "6ed989a8af2f4ee683a90ab206e324a7",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/acites/data/land_surface_data",
            "numberOfFiles": 5,
            "volume": 789647,
            "fileFormat": "netCDF",
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            "observation": {
                "ob_id": 26225,
                "uuid": "b117e4bd7f754d22a65fc823694fa388",
                "short_code": "ob",
                "title": "ACITES: Land cover data for the Olson and Global Land Cover Facility data sets",
                "abstract": "Model grid cell areas and land cover data for the Olson and Global Land Cover Facility. Data are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format.\r\nThe Olson land cover dataset was developed from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993.\r\nThe Global Land Cover Facility dataset was developed from monthly satellite sensor data of NDVI values for 1987."
            },
            "onlineresource_set": [
                24891,
                24892,
                24893
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        },
        {
            "ob_id": 26228,
            "uuid": "453028abc87a455b9beb9daa920bbdc7",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/acites/data/measurement_data",
            "numberOfFiles": 86,
            "volume": 429206,
            "fileFormat": "netCDF",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26227,
                "uuid": "b7953003f065461c9568e3fd9a13460f",
                "short_code": "ob",
                "title": "ACITES: Monthly ozone observations from European and North American sites and CASTNET data.",
                "abstract": "Monthly surface ozone concentration and ozone dry deposition flux fields from observations in Europe and North America and from CASTNET data saved in NetCDF format."
            },
            "onlineresource_set": [
                24896,
                24897
            ]
        },
        {
            "ob_id": 26230,
            "uuid": "868c610e45484aa0a69fbfc47a47f4d2",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/aphh/data/beijing/leeds-fage/",
            "numberOfFiles": 3,
            "volume": 547061,
            "fileFormat": "Data are NASA Ames formatted",
            "storageStatus": "online",
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            "observation": {
                "ob_id": 26174,
                "uuid": "bb339ff791814fc6a8b9a93d339f5bc1",
                "short_code": "ob",
                "title": "APHH: Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the IAP-Beijing site during the winter and summer campaigns.",
                "abstract": "This dataset contains Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe measurements were taken using the FAGE (Fluorescence Assay by Gas Expansion) technique which is a LIF (laser induced fluorescence) that measures on-resonance fluorescence at 308 nm. HO2 and RO2 are converted to OH via reaction with NO and NO + CO respectively. \r\n\r\nThe instrument is calibrated by photolysis of known concentration of water vapour at 185 nm to generate know concentrations of OH and HO2, same method used for HO2 but NO is injected into the flow to convert HO2 to OH. RO2 is calibrated by photolysing water vapur at 185 nm to generate OH but CH4 is added to convert OH to CH3O2, then CH3O2 is converted to OH using CO and NO. The calibration was preform every three days on campaign, and from this we can convert counts measured into concentration. The units for OH, HO2 and RO2 and there associated errors is molecules cm-3. The data has been filtered for instabilities in data collection including unstable pressure, unstable online, low laser power and not going online correctly. The data has been flagged for when the values were below limit of detection."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26231,
            "uuid": "b9601205c9f346d88de7903a4e1d6112",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/COMBINED/v03.3/",
            "numberOfFiles": 13942,
            "volume": 12075789740,
            "fileFormat": "Data is in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 26173,
                "uuid": "0f4570c780ba41b19a362e774509c883",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 03.3",
                "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v03.3 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document.  Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
            },
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        {
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            "uuid": "b85d66bed5554759a65757825d5abd32",
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            "curationCategory": "A",
            "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v03.3/",
            "numberOfFiles": 9282,
            "volume": 6714124499,
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            "observation": {
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                "uuid": "7f320bf20d9e4c7994031c3b0a2170aa",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 03.3",
                "abstract": "The Soil Moisture CCI 'Active' dataset  is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v03.3 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
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        {
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            "short_code": "result",
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            "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v04.2/",
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            "observation": {
                "ob_id": 26234,
                "uuid": "f77cbcfbb6214448aebaa2119d829692",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 04.2",
                "abstract": "The Soil Moisture CCI 'Active' dataset  is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v04.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
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        {
            "ob_id": 26238,
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                "ob_id": 26237,
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                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 03.3",
                "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v03.3 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
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        {
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            "short_code": "result",
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            "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/PASSIVE/v04.2/",
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            "observation": {
                "ob_id": 26239,
                "uuid": "a4f9546935a644d3b3260b7f6a0a183f",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 04.2",
                "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v04.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
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            "observation": {
                "ob_id": 26242,
                "uuid": "0869e3b34fa4465a911e2588396ff1ec",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 04.2",
                "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v04.2 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document.  Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26246,
            "uuid": "40c1b41bc8db461a8fc9704c3d90155b",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v03.3/",
            "numberOfFiles": 6,
            "volume": 1630198,
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            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26245,
                "uuid": "1d28a3d5d74d4439a2be8938dfb550f8",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 03.3",
                "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask.  This version of the ancillary datasets were used in the production of the v03.3 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using the complete three references as follows:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
            },
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        {
            "ob_id": 26248,
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            "short_code": "result",
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            "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v04.2/",
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            "storageStatus": "online",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 26247,
                "uuid": "55bff4add65d489e86c195edbae8f970",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 04.2",
                "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask.  This version of the ancillary datasets were used in the production of the v04.2 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014"
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            "ob_id": 26251,
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            "short_code": "result",
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            "storageStatus": "online",
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                "short_code": "ob",
                "title": "ESA Fire Climate Change Initiative (Fire CCI): Burned Area Pixel Product Version 3.1",
                "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset consists of maps of global burned areas for years 2006 to 2008, developed from satellite observations. The products are distributed as 6 continental tiles and are based upon thermal information from MODIS active fires product and spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ENVISAT ESA satellite.\r\nThe Pixel product includes maps in raster format, at 300m resolution. Burned area (BA) information is included in 3 layers: date of BA detection, the land cover of the burned pixel and the confidence level, a probability value estimating the confidence that a pixel is actually burned.\r\n\r\nAll files are in standard zip compression format, each yearly compressed file holding a set of monthly compressed files. Files are in Geotiff format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carree projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire CCI product user guide in linked documentation."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26252,
            "uuid": "be3dc3e14cc844ca9619c8d9cc06ab46",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/fire/data/burned_area/MERIS/grid/v3.1/",
            "numberOfFiles": 75,
            "volume": 1663268298,
            "fileFormat": "Data are in NetCDF format. \r\n\r\nThe data is organised into yearly files holding sets of monthly files. These store the raster product for each 15 day period. It is stored in geographical coordinates and each cell has a latitude and longitude assignment which is tied to the centre of the grid cell.",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 12543,
                "uuid": "9821980dc18047f09b9113d44fc2c20b",
                "short_code": "ob",
                "title": "ESA Fire Climate Change Initiative (Fire CCI): Burned Area Grid Product Version 3.1",
                "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset collection consists of maps of global burned areas for years 2006 to 2008, developed from satellite observations. The products are based upon thermal information from the MODIS active fires product and spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ENVISAT ESA satellite.\r\n\r\nThe Grid product is derived from the Pixel product by summarizing its burned area information into a regular grid covering the Earth for 15-day periods with 0.5 degree resolution. Information on burned area is included in 22 individual layers: sum of burned area, standard error, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Globcover (2005) product. For further information on the product and its format see the Fire CCI product user guide in linked documentation."
            },
            "onlineresource_set": []
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        {
            "ob_id": 26253,
            "uuid": "41d15a736b4b4b2f87203c7babbe00e4",
            "short_code": "result",
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            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [
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            "observation": {
                "ob_id": 19672,
                "uuid": "fa493d62c2af4c5cb8e6e3c340cdbf0d",
                "short_code": "ob",
                "title": "ESA Fire Climate Change Initiative (Fire_cci): Burned Area Grid Product Version 4.1",
                "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset collection consists of maps of global burned areas for years 2005 to 2011, developed from satellite observations. The products are based upon spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ESA ENVISAT  satellite, and thermal information from the MODIS active fires product.\r\n\r\nThe Grid product is derived from the Pixel product by summarising its burned area information into a regular grid covering the Earth for 15-day periods with 0.25 degree resolution. Information on burned area is included in 22 individual layers: sum of burned area, standard error, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Land Cover CCI v1.6.1 product. For further information on the product and its format see the Fire_cci product user guide in the linked documentation."
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                "title": "ESA Fire Climate Change Initiative (Fire_cci): Burned Area Pixel Product Version 4.1",
                "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset consists of maps of global burned areas for years 2005 to 2011, developed from satellite observations. The products are distributed as 6 continental tiles and are based upon spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ESA ENVISAT satellite and thermal information from the MODIS active fires product.\r\n\r\nThe Pixel product includes maps at 0.00277778-degree (approx. 300m)  resolution. Burned area (BA) information is included in 3 layers: date of BA detection, the confidence level (a probability value estimating the confidence that a pixel is actually burned), and the land cover information as defined in the Land Cover CCI v1.6.1 product.\r\n\r\nFiles are in GeoTIFF format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carrée projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire_cci Product User Guide in the linked documentation."
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                "title": "Met Office LIDARNET Camborne Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Camborne, Cornwall. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "title": "Met Office LIDARNET Glasgow Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at the Met Office's Bishopton enclosure near Glasgow, Scotland. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Loftus, North Yorkshire. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "title": "Met Office LIDARNET Nottingham Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Nottingham, central England. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "title": "Met Office LIDARNET Rhyl Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at a Met Office instrument enclosure near Rhyl, Denbighshire, on the North Welsh coast. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "title": "Met Office LIDARNET Stornoway Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Stornoway, Isle of Lewis in the Outer Hebrides of Scotland. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "title": "DEMON: Simulation output from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observations into the Lisflood-FP flood forecast model ",
                "abstract": "This dataset contains simulation results from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observation into Lisflood-FP flood forecast model for the the lower Severn-Avon rivers in the South West United Kingdom. This was run over a 30.6 x 49.8 km (1524 km2) domain, as part of Developing enhanced impact models for integration with next generation NWP and climate outputs (DEMON) project (NE/I005242/1).\r\n\r\nCOSMO-Skymed Synthetic Aperture Radar (CSK-SAR) data were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Data from Environment Agency (EA) rain gauges were used to estimate precipitation and combined with potential evapotranspiration data from the Met Office's Met Office Rainfall and Evapo-transpiration Calculation System (MORECS) to generate forcings within the \"topHSPF\" catchment-scale rainfall-runoff hydrologic model. These were used in tern to generate simulated runoff forecast used as the forcing for the coupled Lisflood-FP v5.9 inundation model. \r\n\r\nCSK-SAR based WLO were assimilated into ensemble simulations using the Lisflood-FP v5.9 model, run with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the topHSPF hydrologic model"
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                "title": "Met Office LIDARNET East Malling Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at East Malling, Kent. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
            },
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                "title": "Met Office LIDARNET Lerwick Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Lerwick, Shetland Isles. Data available from July 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "title": "Met Office LIDARNET Portglenone Raymetrics LR111-D300 lidar profile data",
                "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at the Met Office observations enclosure near Portglenone, County Antrim, Northern Ireland. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives."
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                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project."
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                "title": "FAAM C105 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project."
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                "title": "FAAM C077 PICASSO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Parameterizing Ice Clouds using Airborne obServationS and triple-frequency dOppler radar data (PICASSO) project."
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                "title": "FAAM C076 PICASSO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Parameterizing Ice Clouds using Airborne obServationS and triple-frequency dOppler radar data (PICASSO) project."
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                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Parameterizing Ice Clouds using Airborne obServationS and triple-frequency dOppler radar data (PICASSO) project."
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                "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 3 Uncollated (L3U) Climate Data Record, version 2.0",
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                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument) project."
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                "short_code": "ob",
                "title": "FAAM C110 SaddleworthMoor flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for SADDLEWORTHMOOR FAAM Aircraft Project (SaddleworthMoor) project."
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                "title": "FAAM C111 MOYA and SaddleworthMoor flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) and SADDLEWORTHMOOR FAAM Aircraft Project projects."
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                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AEOG - FAAM project project."
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                "title": "Biodiversity and Land Use Impacts on Tropical Forest Ecosystem Function (BALI) : Atmospheric trace gas measurements",
                "abstract": "This dataset contains atmospheric trace gas measurements, including Volitile Organic Compunds (VOCs) for the Biodiversity and Land Use Impacts on Tropical Forest Ecosystem Function (BALI) project. The measurements were taken at the GLobal Atmosphere Watch (GAW) observatory at Burkit Atur, Danum Valley, Borneo. August 2015-August 2016"
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                "title": "GloCAEM: Atmospheric electricity measurements at Nor-Amberd Research Station",
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                "title": "Iceland Greenland seas Project (IGP): Upper air sounding: Profiles of temperature, pressure, humidity, wind speed and wind direction",
                "abstract": "This dataset contains upper air sounding profiles of temperature, pressure, humidity, wind speed and wind direction measurements from the NCAS Vaisala Sounding Station unit 2 radiosonde lauches. The radiosondes were launched over Greenland and Iceland from the Alliance research ship for the Iceland Greenland seas Project (IGP). \r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)"
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                "title": "EUSTACE/GlobTemperature:  Global clear-sky land surface temperature data from MODIS Terra on the satellite swath with estimates of uncertainty components, v2.1, 2000-2016",
                "abstract": "This dataset consists  of Land Surface Temperature (LST) data with uncertainty estimates, from the MODIS instrument on NASA's Terra satellite.   It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.  \r\n\r\nThe Level 2 Land Surface Temperature data in this dataset has been retrieved from MODIS Collection 6 L1B calibrated radiances,  in the context  of the GlobTemperature project, but new uncertainty estimates have been added as part of the EUSTACE project.    This version of the LST dataset is v2.1 of the GT_MOG_2P product, with earlier versions produced under the GlobTemperature project.  It consists of a complete set of LST and accompanying auxiliary (AUX) datafiles for the MODIS-Terra mission for the period 2000 to 2016.  An equivalent dataset is also available for MODIS-Aqua."
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            "fileFormat": "These data are provided in the ESA safe format as downloaded from the Sentinel data hubs.",
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                "title": "Sentinel 1A C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Ocean (OCN) Level 2 data, Instrument Processing Facility (IPF) v3",
                "abstract": "This dataset contains level-2 Interferometric Wide swath (IW) Ocean (OCN) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1A satellite. Level-2 data consists of geolocated geophysical products derived from Level-1. Sentinel 1A was launched on 3rd April 2014 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. These level 2 OCN products provide Ocean Wind field (OWI) and Surface Radial Velocity (RVL).\r\n\r\nThe OWI component is a ground range gridded estimate of the surface wind speed and direction at 10 m above the surface, derived from IW mode. The OWI component contains a set of wind vectors for each processed Level-1 input product. The norm is the wind speed in m/s and the argument is wind direction in degrees (meteorological convention = clockwise direction from where the wind blows with respect to the North). The spatial resolution of the SAR wind speed is 1 km for IW mode.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. The RVL estimates are produced on a ground-range grid.\r\n\r\nThese data are available via CEDA to any registered CEDA user."
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                "short_code": "ob",
                "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Ocean (OCN) Level 2 data, Instrument Processing Facility (IPF) v2",
                "abstract": "This dataset contains level-2 Interferometric Wide swath (IW) Ocean (OCN) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1B satellite. Level-2 data consists of geolocated geophysical products derived from Level-1. Sentinel 1B was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. These level 2 OCN products provide Ocean Wind field (OWI) and Surface Radial Velocity (RVL). \r\n\r\nThe OWI component is a ground range gridded estimate of the surface wind speed and direction at 10 m above the surface, derived from IW mode. The OWI component contains a set of wind vectors for each processed Level-1 input product. The norm is the wind speed in m/s and the argument is wind direction in degrees (meteorological convention = clockwise direction from where the wind blows with respect to the North). The spatial resolution of the SAR wind speed is 1km for IW mode.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. The RVL estimates are produced on a ground-range grid.\r\n\r\nThese data are available via CEDA to any registered CEDA user."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26524,
            "uuid": "543a0f1c80334bfc9ca29573565e6c1b",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/trmm/data/TRMM_3B42",
            "numberOfFiles": 252245,
            "volume": 55468077361,
            "fileFormat": "Data are HDF formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26512,
                "uuid": "92c7a6a0824f4d18afa70aa1b86c103f",
                "short_code": "ob",
                "title": "Tropical Rainfall Measuring Mission (TRMM) Rainfall Estimate L3 3 hour 0.25 degree x 0.25 degree (TRMM_3B42)",
                "abstract": "This dataset contains output from the TMPA (TRMM Multi-satellite Precipitation) Algorithm, and provides precipitation estimates in the TRMM regions that have the (nearly-zero) bias of the ”TRMM Combined Instrument” precipitation estimate and the dense sampling of high-quality microwave data with fill-in using microwave-calibrated infrared estimates. The granule size is 3 hours.\r\n\r\nThe Tropical Rainfall Measuring Mission (TRMM) was a joint mission between NASA and the Japan Aerospace Exploration (JAXA) Agency to study rainfall for weather and climate research."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26525,
            "uuid": "439bbfec242e439ea31ce492c6553712",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/sentinel1b/data/SM/L1_SLC/IPF_v2",
            "numberOfFiles": 0,
            "volume": 0,
            "fileFormat": "Data are in ESA safe file format as downloaded from the Sentinel data hubs.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": null,
            "onlineresource_set": []
        },
        {
            "ob_id": 26526,
            "uuid": "ee531469739947d5a7b682b331df07ee",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/gpm/data/GPM-IMERG",
            "numberOfFiles": 81939,
            "volume": 36033730216,
            "fileFormat": "Data are HDF formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26515,
                "uuid": "ff725747de574f7dbb8236a9c31984e5",
                "short_code": "ob",
                "title": "Global Precipitation Measurements (GPM) Integrated Multi-satellitE Retrievals (IMERG) L3 Half Hourly 0.1 degree x 0.1 degree v5",
                "abstract": "This dataset contains Global Precipitation Measurements (GPM) Integrated Multi-satellitE Retrievals (IMERG) v5. The Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the Day-1 multi-satellite precipitation product. The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2014 version of the Goddard Profiling Algorithm (GPROF2014), then gridded, intercalibrated to the GPM Combined Instrument product, and combined into half-hourly 10x10 km fields.\r\n\r\nThe Global Precipitation Measurement (GPM) mission is an international network of satellites that provide the next-generation global observations of rain and snow."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26534,
            "uuid": "a73a908726b54652a0cf209325c567d6",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/chirps/data/CHIRPS-2.0/global_daily",
            "numberOfFiles": 979,
            "volume": 89245465021,
            "fileFormat": "Data are netCDf formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26531,
                "uuid": "4e53c2aee3fe44e7aa107c163696d2e7",
                "short_code": "ob",
                "title": "CHIRPS: Quasi-global daily satellite and observation based precipitation estimates over land",
                "abstract": "This dataset contains Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) Quasi-global satellite and observation based precipitation estimates over land from 1981 to near-real time. Spanning 50°S-50°N (and all longitudes), starting in 1981 to near-present, CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26535,
            "uuid": "c125e28c2c8b4526a6c492039a5c217e",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/chirps/data/CHIRPS-2.0/global_pentad",
            "numberOfFiles": 39,
            "volume": 37465835589,
            "fileFormat": "Data are netCDF formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26533,
                "uuid": "00bbc115468f459ca05b6f5149ddb4fa",
                "short_code": "ob",
                "title": "CHIRPS: Quasi-global pentadal daily satellite and observation based precipitation estimates over land",
                "abstract": "This dataset contains Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) Quasi-global pentadal satellite and observation based precipitation estimates over land from 1981 to near-real time. Spanning 50°S-50°N (and all longitudes), starting in 1981 to near-present, CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26536,
            "uuid": "a1cb71b0b488462aa883ee56acee4bdd",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/chirps/data",
            "numberOfFiles": 0,
            "volume": 0,
            "fileFormat": "Data are binary formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": null,
            "onlineresource_set": []
        },
        {
            "ob_id": 26539,
            "uuid": "b34270daeea94c70b402db06799bb746",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/sentinel5p/data/L1_RA/",
            "numberOfFiles": 590321,
            "volume": 840668105427159,
            "fileFormat": "These data are in NetCDF format. As downloaded from the ESA data hubs.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25900,
                "uuid": "4e1ed175588d41f193dd6f8f0140e7e3",
                "short_code": "ob",
                "title": "Sentinel 5P: TROPOspheric Monitoring Instrument (TROPOMI) Radiance level 1b data.",
                "abstract": "This dataset contains level 1b earth radiance spectra data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the European Space Agency (ESA) Sentinel 5P satellite. Sentinel 5P was launched on 13th October 2017. Level 1b data is geo-located and radiometrically corrected top of the atmosphere Earth radiances in all spectral bands. There is one L1b radiance product type for each spectral band (product identifiers L1B_RA_BD1 through L1B_RA_BD8). The radiance products are the main input for the Level-2 processors.\r\n\r\nSentinel 5P aims to provide atmospheric measurements relating to air quality, climate forcing, ozone and ultraviolet radiation. This data looks to build on the data from GOME, SCIAMACHY and OMI missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26542,
            "uuid": "ecfc205995244b83bbadf7ed6ebb0b28",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/qa4ecv/data/broadband_albedo",
            "numberOfFiles": 77996,
            "volume": 12978804705910,
            "fileFormat": "These data are in netCDF4 format. As provided by the QA4ECV project.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25938,
                "uuid": "efb5c580d2774a37acf4515cbc5f7bba",
                "short_code": "ob",
                "title": "QA4ECV Global Broadband albedo (1982-2016)",
                "abstract": "Global albedo data of the land surface is produced from data from 1982-2016 from European and US satellites, daily and monthly products with estimated uncertainties for every pixel. This data product is produced from AVHRR+GEO Broadband Albedo at 0.5 and 0.05 degrees. This dataset contains Level-3 daily surface broadband albedo products. Level-3 data are raw observations processed to geophysical quantities, and placed onto a regular grid.\r\n\r\nKnowledge of albedo is of critical importance to land surface monitoring and modelling, particularly with regard to considerations of climate forecasting and energy exchanges within the biosphere. When albedo is used in models, it has often been specified as a fixed number for some given land cover type. However, many years of monitoring from single instruments, such as MODIS, have shown that it can vary significantly both spatially and temporally. That said, being an angular and spectral integral, it is relatively conservative inter-annually, other than due to factors such as snow and possibly fire and dramatic land cover change (e.g. flooding, urbanisation). As particularly high changes in albedo occur due to the presence of absence of snow, modellers tend to consider these two cases separately: a snow free albedo and one with snow included."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26544,
            "uuid": "8574a6d6bc3e4fa3b5e14e8b603efe5e",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/grounding_line_locations/Ferrigno_PineIS_Thwaites_Smith_Pope_Kohler/v2.0_cci_subset/",
            "numberOfFiles": 8,
            "volume": 192023,
            "fileFormat": "ESRI Shapefile, KML and WKT in textfile (CSV)",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26543,
                "uuid": "bdf2cf5a78554a73bf5e57a853e3bbc0",
                "short_code": "ob",
                "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Grounding Line Locations for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers, Antarctica, 1995-2017, v2.0  (CCI subset)",
                "abstract": "Grounding line locations (GLL) data for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers in Antarctica, produced by the ESA Antarctic Ice Sheet Climate Change Initiative (CCI) project. The grounding lines  have been derived from satellite observations from the ERS-1/2 and Copernicus Sentinel-1 instruments, acquired in the period from 1995-2017.\r\n\r\nAn extended dataset of Grounding line locations for these Glaciers is available on the ENVEO CryoPortal (http://cryoportal.enveo.at/data/)"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26545,
            "uuid": "f1895b283cc8439c8dc0c256a90c1dc3",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/specs/data/SPECS/output/MOHC/DePreSys3/decadal",
            "numberOfFiles": 152442,
            "volume": 589201933710,
            "fileFormat": "NetCDF",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 20020,
                "uuid": "030067cfcb664bc0a6edd0542f801135",
                "short_code": "ob",
                "title": "SPECS - MOHC-DePreSys3 model output prepared for SPECS decadal (1960-2005)",
                "abstract": "This dataset includes the Met Office DePreSys model output prepared for SPECS decadal (1960-2005). These data were prepared by the Met Office Hadley Centre, as part of the SPECS project. \r\n      \r\nModel id is DePreSys3 (DePreSys3: HadGEM3-GC2 N216; atmosphere: UM (GA5.0) ; ocean: NEMO (v3.4, ORCA0.25) ; coupler: OASIS3 (v3.3); sea ice: CICE), frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\npr psl tas\r\n\r\nMonthly atmos variables:\r\nhfls hfss mrso pr psl rls rlut rsdt rss rsut ta tas ua va zg\r\n\r\nMonthly seaIce variables:\r\nsic  sit  \r\n\r\nOcean variables:\r\ntos"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26546,
            "uuid": "521485830e984dc0b9d378c4d3c0acc7",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/deposited2018/bitmap/data/era-interim-derived-wd-tracks",
            "numberOfFiles": 2,
            "volume": 8371284,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 24958,
                "uuid": "233cf64c54e946e0bb691a07970ec245",
                "short_code": "ob",
                "title": "BITMAP: Tracks of western disturbances transiting over Pakistan and north India in ERA-Interim reanalysis data (1979-2015)",
                "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation), using data derived from the ERA-Interim reanalysis data. Similar datasets were produced using various model output from the WCRP CMIP5 programme, available within the parent dataset collection.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 450-300 hPa. This differs from those tracks from the CMIP5 data which were carried out on the 500 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions.  Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon.  For further details on the project itself see the linked Project record."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26552,
            "uuid": "edf2c5f652884dc1a5aa3110d40b4889",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/deposited2018/freezing_temperature",
            "numberOfFiles": 9,
            "volume": 77266,
            "fileFormat": "Data are BADC-CSV formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26547,
                "uuid": "858a4b439d7d4466b82ea5215614f135",
                "short_code": "ob",
                "title": "Freezing temperature laboratory experiments of individual droplets each contained in a well plate using InfraRed-Nucleation by Immersed Particles Instrument (IR-NIPI)",
                "abstract": "This dataset contains freezing temperature laboratory measurements of individual droplets each contained in a well of a 96-well plate using InfraRed-Nucleation by Immersed Particles Instrument (IR-NIPI) instrument. IR-NIPI makes use of InfraRed (IR) emissions to determine the freezing temperature of individual 50μL droplets each contained in a well of a 96-well plate. Using an IR camera allows the temperature of individual aliquots to be monitored. Freezing temperatures are determined by detecting the sharp rise in well temperature associated with the release of heat caused by freezing."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 26557,
            "uuid": "581729e5e8b44a2c9f3efe45d0dd89ed",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2018/HadCM3B_60Kyr_Climate/data",
            "numberOfFiles": 223,
            "volume": 725297620051,
            "fileFormat": "NetCDF",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 26559,
                "uuid": "de6591c3d5d44b08b4d954410f353c6e",
                "short_code": "ob",
                "title": "A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years",
                "abstract": "We present a continuous land climate reconstruction dataset extending from 60 kyr before present to the pre-industrial period at 0.5deg resolution on a monthly timestep for 0degN to 90degN. It has been generated from 42 discrete snapshot simulations using the HadCM3B-M2.1 coupled general circulation model. We incorporate Dansgaard-Oeschger (DO) and Heinrich events to represent millennial scale variability, based on a temperature reconstruction from Greenland ice-cores, with a spatial fingerprint based\r\n on a freshwater hosing simulation with HadCM3B-M2.1. Interannual variability is also added and derived from the initial snapshot simulations. Model output has been downscaled to 0.5deg resolution (using simple bilinear interpolation) and bias corrected using either the University of East Anglia, Climate Research Unit observational data (for temperature, precipitation, windchill, and minimum monthly temperature), or the EWEMBI dataset (for incoming shortwave energy). Here we provide datasets for; surface air temperature, precipitation, incoming shortwave energy, wind-chill, snow depth (as snow water equivalent), number of rainy days per month,  minimum monthly temperature, and the land-sea mask and ice fractions used in the simulations. The datasets are in the form of NetCDF files. The variables are represented by a set of 24 files that have been compressed into nine folders: temp, precip, down_sw, wind_chill, snow, rainy_days, tempmonmin, landmask and icefrac. Each file represents 2500 years. The landmask and ice fraction are provided annually, whereas the climate variables are given as monthly files equivalent to 30000 months, between the latitudes 0deg to 90degN at 0.5deg resolution. Each of the climate files therefore have the dimensions 180 (lat) x 720 (lon) x 30000 (month). We also provide an example subset of the temperature dataset, which gives decadal averages for each month for 0-2500 years."
            },
            "onlineresource_set": []
        }
    ]
}