Result List

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        {
            "ob_id": 25037,
            "uuid": "5bddcd8938814aea9c3519ae3eeb6a39",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2017/acid-pruf/data",
            "numberOfFiles": 2,
            "volume": 4815,
            "fileFormat": "Data are BADC-CSV formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25036,
                "uuid": "131174cdad804dd1a51e79d7dbd1d2b0",
                "short_code": "ob",
                "title": "ACID-PRUF: Measurements of freezing fraction of water solution droplets solute and suspended matter during the immersion freezing of pollen extracts",
                "abstract": "ACID-PRUF was a three year NERC directed programme that investigated the complex interaction of aerosols and clouds. The overall aims of ACID-PRUF were to reduce the uncertainty in the radiative forcing associated with the aerosol indirect effects though a targeted laboratory and modelling programme. \r\n\r\nThis dataset collection contains measurements of freezing fraction of water solution droplets-solute and suspended matter during the immersion freezing of pollen extracts (birch pollen, Betula fontinalis occidentalis, Sigma-Aldrich, P6895-1G), with a  new cold electrodynamic balance (CEDB)."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25040,
            "uuid": "94493496576c448da8af0304d241ed81",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/glocaem/data/bristol-uni",
            "numberOfFiles": 1,
            "volume": 829,
            "fileFormat": "Data are BADC_CSV formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": null,
            "onlineresource_set": []
        },
        {
            "ob_id": 25042,
            "uuid": "980ba6a1c862462fbe01d0e8597b3238",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/weather_at_home/data/marius_time_series",
            "numberOfFiles": 422,
            "volume": 1104985878692,
            "fileFormat": "NetCDF",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25043,
                "uuid": "0cea8d7aca57427fae92241348ae9b03",
                "short_code": "ob",
                "title": "Managing the Risks, Impacts and Uncertainties of drought and water Scarcity (MaRIUS) project: Large set of   potential past and future climate time series for the UK from the weather@home2 model",
                "abstract": "Large data sets created within the MaRIUS project (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity). \r\nThree time periods are covered: historical baseline (BS: 1900-2006), near-future (NF: 2020-2049) and far-future (FF: 2070-2099), whereby the RCP8.5 is assumed for future time slices. The 30-year baseline to which future time slices should be compared to are years 2075-2004 of the historical baseline, since oceanic variability in future time slices is based on these years.\r\nOne set of 100 time series is available for the historical baseline, while 5 sets of about 85-100 time series are available for each future time slice. The five sets sample climate model uncertainty by sampling a range of sea surface temperature warming patterns as follows: nf and ff use the median warming pattern of CMIP5 climate models. The four others sets are called nf-pYYz (near future) and ff-pYYz (far future) whereby 'YY' stands for the percentile of global mean SST warming (YY=10 or 90) and 'z' stands for the North Atlantic SST gradient (z=n for minimum, z=x for maximum). All natural forcings (e.g., volcanoes) in the future time slices are replications of years 1975-2004, while anthropogenic forcings (e.g., CO2 concentrations) follow the high-emission scenario RCP8.5.\r\nThe time series were created from single-year simulations that have been stitched together while ensuring continuity in the slowly-evolving variability (see Guillod et al., Hydrol. Earth Syst. Sci., 2017 for details). Therefore, for each set (e.g., near_future_p10n), a 'stitching table' is provided alongside with data from individual yearly simulations, which contains the simulation ID ('umid') for each year and each individual time series (i.e., each column within the table list the umid for each year of the time series).\r\nData are gridded NetCDF V3 files, provided on a rotated longitude-latitude grid at a 0.22 degree resolution (European CORDEX grid) over a domain encompassing the United Kingdom. A subset of variables are available at daily, 5-days, and monthly temporal resolutions, based on a calendar with 360 days a year (30 days per month). Included are only data from HadRM3P, the regional climate model within weather@home2. After unpacking yearly *tgz files for a given time slice and scenario (e.g., near_future_p10n) within a directory with the relevant name, the data are structured as follows:\r\ntimeslice / year / umid / temporalResolution / WAH_umid_variable_temporalResolution_g2_year.nc\r\nwhere:\r\n- The temporal resolution ('temporalResolution') available depends on the variable, but it can be 'daily', 'monthly', or '5days'\r\n- 'timeslice' can be one of: 'baseline', 'near_future', 'near_future_p10n', 'near_future_p10x', 'near_future_p90n', 'near_future_p90x', 'far_future', 'far_future_p10n', 'far_future_p10x', 'far_future_p90n', 'far_future_p90x'.\r\n- 'year' is the year of the simulation and data.\r\n- 'umid' is the ID of the simulation, to be read from the stitching table.\r\n- 'variable' is the variable, following CMOR conventions (see also Table 3 in Guillod et al., Hydrol. Earth Syst. Sci., 2017).\r\nFurther details about the data, including validation of the climate time series and analyses of some changes in the future projections, can be found in the PDF documentation as well as in Guillod et al., 2017b. A detailed validation of the model (weather@home2) can be found in Guillod et al., 2017a (see list of references below).\r\n"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25047,
            "uuid": "b630fcb89aa34c25b64bd75fd767c685",
            "short_code": "result",
            "curationCategory": "C",
            "dataPath": "/badc/ukmo-lidarnet/data/brize-norton/vaisala-cl31",
            "numberOfFiles": 72612,
            "volume": 39961876154,
            "fileFormat": "Data are netCDF formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25046,
                "uuid": "886f3142adac4acb8ed4a64328d2031d",
                "short_code": "ob",
                "title": "Met Office LIDARNET Brize Norton Vaisala CL31 ceilometer cloud base and backscatter data",
                "abstract": "Cloud base and backscatter data from the Met Office's Vaisala CL31 ceilometer located at Brize Norton, Oxfordshire. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns 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. This instrument replaced a Vaisala CT25k ceilometer at the site in January 2017.\r\n"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25050,
            "uuid": "5a76ccd96d714c02b51a6360450ed140",
            "short_code": "result",
            "curationCategory": "C",
            "dataPath": "/badc/ukmo-lidarnet/data/northolt/vaisala-cl31/",
            "numberOfFiles": 72338,
            "volume": 39812963541,
            "fileFormat": "Data are netCDF formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25049,
                "uuid": "df2b4915b1b84d31b7032f8eeecf6b10",
                "short_code": "ob",
                "title": "Met Office LIDARNET Northolt Vaisala CL31 ceilometer cloud base and backscatter data",
                "abstract": "Cloud base and backscatter data from the Met Office's Vaisala CL31 ceilometer located at RAF Northolt, near Heathrow, southern England. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns 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. The Vaisala CL31 instrument replaced the Vaisala Ct25k instrument previously deployed at the site in October 2016.\r\n"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25052,
            "uuid": "969a594289074eedaef9056953c1078e",
            "short_code": "result",
            "curationCategory": "C",
            "dataPath": "/badc/ukmo-lidarnet/data/wittering/vaisala-cl31",
            "numberOfFiles": 68764,
            "volume": 37860932237,
            "fileFormat": "Data are netCDF formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25054,
                "uuid": "e014754be8014e4294c0f5d1a86ce545",
                "short_code": "ob",
                "title": "Met Office LIDARNET Wittering Vaisala CL31 ceilometer cloud base and backscatter data",
                "abstract": "Cloud base and backscatter data from the Met Office's Vaisala CL31 ceilometer located at Wittering,  Sussex. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns 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. The Vaisala CL31 instrument replaced a Vaisala CT25k instrument previously operated at the site until November 2016.\r\n"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25067,
            "uuid": "de463dbf14e148aab04ebfe89109b9ca",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cru/data/cru_ts/cru_ts_4.01",
            "numberOfFiles": 394,
            "volume": 34203448478,
            "fileFormat": "Data are provided in ASCII and NetCDF formats.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25066,
                "uuid": "58a8802721c94c66ae45c3baa4d814d0",
                "short_code": "ob",
                "title": "CRU TS4.01: Climatic Research Unit (CRU) Time-Series (TS) version 4.01 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2016)",
                "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.01 data are month-by-month variations in climate over the period 1901-2016, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.01 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2016.\r\n\r\nThe CRU TS4.01 data were produced using angular-distance weighting (ADW) interpolation. All version 3 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. CRU TS4.01 is a full release, differing only in methodology from the parallel release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3.\r\n\r\nThe CRU TS4.01 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25068,
            "uuid": "a4a82998615340dcb1e502578c925b77",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cru/data/cru_ts/cru_ts_3.25",
            "numberOfFiles": 607,
            "volume": 8304901978,
            "fileFormat": "Data are provided in ASCII and NetCDF formats.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25063,
                "uuid": "c311c7948e8a47b299f8f9c7ae6cb9af",
                "short_code": "ob",
                "title": "CRU TS3.25: Climatic Research Unit (CRU) Time-Series (TS) Version 3.25 of High-Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2016)",
                "abstract": "This version of CRU TS is superseded by version 4.01. It is being made available to assist with users moving to the new process. No further releases of version 3 are planned.\r\n\r\nThe gridded CRU TS (time-series) 3.25 data are month-by-month variations in climate over the period 1901-2016, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.25 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2016.\r\n\r\nCRU TS 3.25 data were produced using the same methodology as for the 3.21, 3.22, 3.23 and 3.24.01 datasets. This version contains updates the dataset with 2016 data, some new stations have been added for TMP and PRE only. This release is the latest release of the CRU TS data.  Known issues predating this release remain.\r\n\r\nThe CRU TS 3.25 data are monthly gridded fields based on monthly observational data, which are calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25069,
            "uuid": "6fb382672acf4ddd9852d2e5d8aa6603",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cru/data/cru_cy/cru_cy_3.25",
            "numberOfFiles": 2923,
            "volume": 49331502,
            "fileFormat": "The CRU CY data are provided as text files with the extension \".per\", most text editors will open these files. See the linked file formats guide for more information.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25064,
                "uuid": "237c618d8b2e49cf8e61d01780f11650",
                "short_code": "ob",
                "title": "CRU CY3.25: Climatic Research Unit (CRU) Year-by-Year Variation of Selected Climate Variables by CountrY (CY) version 3.25 (Jan. 1901 - Dec. 2016)",
                "abstract": "This version of CRU CY is superseded by version 4.01. It is being made available to assist with users moving to the new process. No further releases of version 3 are planned. \r\n\r\nAn updated set of country definitions have been introduced with this version. Please see the appropriate Release Notes. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nThe CRU CY version 3.25 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. \r\n\r\nThis dataset was produced in 2017 by the Climatic Research Unit (CRU) at the University of East Anglia and extends CRU CY 3.24.01.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY3.25 is derived directly from the CRU TS3.25 dataset. CRU CY version 3.25 spans the period 1901-2016 for 289 countries.\r\n\r\nTo understand the CRU-CY3.25 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS3.25. It is therefore recommended that all users read the Harris et al, 2014 paper listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users."
            },
            "onlineresource_set": [
                26435
            ]
        },
        {
            "ob_id": 25070,
            "uuid": "dd3d8e7a55f8416eb387ffaff8b2e990",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cru/data/cru_cy/cru_cy_4.01",
            "numberOfFiles": 2923,
            "volume": 49331502,
            "fileFormat": "The CRU CY data are provided as text files with the extension \".per\", most text editors will open these files. See the linked file formats guide for more information.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25065,
                "uuid": "d4e823f0172947c5ae6e6b265656c273",
                "short_code": "ob",
                "title": "CRU CY4.01: Climatic Research Unit (CRU) year-by-year variation of selected climate variables by country (CY) version 4.01 (Jan. 1901 - Dec. 2016)",
                "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.01 dataset consists of ten climate variables for  country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2017 by CRU at the University of East Anglia and extends the CRU CY4.00 data to include 2016. CRU CY4.01 is a full release, differing only in methodology from the existing current version 3 release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.01 is derived directly from the CRU TS4.01 dataset. CRU CY version 4.01 spans the period 1901-2016 for 289 countries.\r\n\r\nTo understand the CRU CY4.01 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.01. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.01 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users."
            },
            "onlineresource_set": [
                26436
            ]
        },
        {
            "ob_id": 25072,
            "uuid": "8d0b658450ea469198e90774d30f4b82",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/ugamp-o3-climatology/data/y86",
            "numberOfFiles": 13,
            "volume": 13891868,
            "fileFormat": "Data are ASCII formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25071,
                "uuid": "9b8f99f449c649778cb3febb14c0408c",
                "short_code": "ob",
                "title": "UGAMP: 3-D ozone column monthly average 1986",
                "abstract": "The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This  dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1986.\r\n\r\nEach file contains a ligne of text followed by the variable itself, in free format.\r\n\r\nEvery single three-dimensional field var is stored as\r\n\r\n(((var(i, j, k), i=1, 144), j=1, 73), k=1, 47)\r\nwhere\r\ni is the longitude index (from 0°E to 357.5°E by 2.5°);\r\nj is the latitude index (from South Pole to North Pole by 2.5°);\r\nk is the level index (from top to bottom).\r\n\r\nEvery two-dimensional field (zonal means) is stored as\r\n\r\n((var(j, k), j=1, 73), k=1, 47)\r\nwith the same conventions as above."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25074,
            "uuid": "709cc24926e348a4ac8211f48d76527c",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/ugamp-o3-climatology/data/y87",
            "numberOfFiles": 13,
            "volume": 13906880,
            "fileFormat": "Data are ASCII formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25073,
                "uuid": "bdbe4e3f4b464cb5b5912d770127dfbe",
                "short_code": "ob",
                "title": "UGAMP: 3-D ozone column monthly average 1987",
                "abstract": "The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This  dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1987.\r\n\r\nEach file contains a ligne of text followed by the variable itself, in free format.\r\n\r\nEvery single three-dimensional field var is stored as\r\n\r\n(((var(i, j, k), i=1, 144), j=1, 73), k=1, 47)\r\nwhere\r\ni is the longitude index (from 0°E to 357.5°E by 2.5°);\r\nj is the latitude index (from South Pole to North Pole by 2.5°);\r\nk is the level index (from top to bottom).\r\n\r\nEvery two-dimensional field (zonal means) is stored as\r\n\r\n((var(j, k), j=1, 73), k=1, 47)\r\nwith the same conventions as above."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25076,
            "uuid": "7d2a7cee26f142ac8b9fcb90bb14a68f",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/ugamp-o3-climatology/data/y88",
            "numberOfFiles": 13,
            "volume": 13960373,
            "fileFormat": "Data are ASCII formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25075,
                "uuid": "10ba8b8b61094c1b83940d8b49c39601",
                "short_code": "ob",
                "title": "UGAMP: 3-D ozone column monthly average 1988",
                "abstract": "The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This  dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1988.\r\n\r\nEach file contains a ligne of text followed by the variable itself, in free format.\r\n\r\nEvery single three-dimensional field var is stored as\r\n\r\n(((var(i, j, k), i=1, 144), j=1, 73), k=1, 47)\r\nwhere\r\ni is the longitude index (from 0°E to 357.5°E by 2.5°);\r\nj is the latitude index (from South Pole to North Pole by 2.5°);\r\nk is the level index (from top to bottom).\r\n\r\nEvery two-dimensional field (zonal means) is stored as\r\n\r\n((var(j, k), j=1, 73), k=1, 47)\r\nwith the same conventions as above."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25078,
            "uuid": "db2b8208a0f940dcbc48cd2dcbb696fa",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/ugamp-o3-climatology/data/y89",
            "numberOfFiles": 13,
            "volume": 13921669,
            "fileFormat": "Data are ASCII formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25077,
                "uuid": "05852218fdb142cc9a146e6e70656f5e",
                "short_code": "ob",
                "title": "UGAMP: 3-D ozone column monthly average 1989",
                "abstract": "The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This  dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1989.\r\n\r\nEach file contains a ligne of text followed by the variable itself, in free format.\r\n\r\nEvery single three-dimensional field var is stored as\r\n\r\n(((var(i, j, k), i=1, 144), j=1, 73), k=1, 47)\r\nwhere\r\ni is the longitude index (from 0°E to 357.5°E by 2.5°);\r\nj is the latitude index (from South Pole to North Pole by 2.5°);\r\nk is the level index (from top to bottom).\r\n\r\nEvery two-dimensional field (zonal means) is stored as\r\n\r\n((var(j, k), j=1, 73), k=1, 47)\r\nwith the same conventions as above."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25080,
            "uuid": "3d5d4d3eafb94889840274e259a72cab",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ugamp-o3-climatology/data/yr5",
            "numberOfFiles": 13,
            "volume": 13884433,
            "fileFormat": "Data are ASCII formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25079,
                "uuid": "3346e0a6ed884989bd025ba72ab3d8dd",
                "short_code": "ob",
                "title": "UGAMP: 3-D ozone column 5 year average",
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                "title": "UGAMP: 3-D ozone column zonal means",
                "abstract": "The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This  dataset contains a 3-dimensional climatology of ozone zonal monthly averages, combining various satellite observations and ozone sonde data. The data are global and covers 1985-1989.\r\n\r\nEach file contains a ligne of text followed by the variable itself, in free format.\r\n\r\nEvery single three-dimensional field var is stored as\r\n\r\n(((var(i, j, k), i=1, 144), j=1, 73), k=1, 47)\r\nwhere\r\ni is the longitude index (from 0°E to 357.5°E by 2.5°);\r\nj is the latitude index (from South Pole to North Pole by 2.5°);\r\nk is the level index (from top to bottom).\r\n\r\nEvery two-dimensional field (zonal means) is stored as\r\n\r\n((var(j, k), j=1, 73), k=1, 47)\r\nwith the same conventions as above."
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                "title": "Auchencorth Moss Atmospheric Observatory (AU): Annual half-hourly meteorology since 1995, Near Edinburgh, UK - Version 1",
                "abstract": "The site was setup in 1995 to measure meteorology, trace gases, aerosols and their fluxes. It is (55ᵒ47’36” N, 3°14’41” W) an ombrotrophic peatland with an extensive fetch at an elevation of 270 m, lying 18 km SSW of Edinburgh, and can be categorised as a transitional lowland raised bog. The site is grazed with < 1 sheep ha^-1.\r\n\r\nDuring 2000s the site activity has increased and was established in 2006 as EMEP (European Monitoring and Evaluation Program, Level 2/3) supersite for the UK. Long term monitoring is led by NERC CEH with contributions from other organisations/research institutes including Ricardo AEA, BureauVeritas, NPL, the University of Birmingham and University of Edinburgh. In April 2014 the site was awarded WMO GAW regional station (World Meteorological Orgamisation Global Atmospheric Watch). In 2017 the site joined the ICOS network (Integrated Carbon Observation System).\r\n\r\nThe meteorological measurements were initially made to assist with interpretation of the fluxes and as such weren't installed with the intention of providing WMO standard measurements but since 2014 we have been moving towards these standards as well as enhancing instrumentation.\r\n\r\nThe dataset includes the following parameters at half hourly intervals, although not every variable is available from 1995 to 2016:\r\n-T_upper_Avg - initially used to estimate senisble heat fluxes, fine wire type-E thermocouple.\r\n-T_lower_Avg - initially used to estimate senisble heat fluxes, fine wire type-E thermocouple.\r\n-T_RHT_Avg - Temperature measured by a Vailsala relative humidity and temperature probe.\r\n-RH_RHT_Avg - Relative humidity measured by a Vailsala relative humidity and temperature probe.\r\n-P_Avg - atmospheric pressure at the sites elevation.\r\n-Tot_Solar_Avg - Total solar radiation measured by a Skye SKS1110.\r\n-PAR_Avg - Photosynthetically Averaged Radiation measured by a Skye SKP215.\r\n-NetRad_Avg - Net radiation, Kipp & Zonen NrLite.\r\n-Rainfall - tipping bucket rainfall.\r\n-SoilTavg - Average soil temperature from four type-E thermocouple probes.\r\n-Soil Heat Flux - calculated from two measurements of soil heat flux with Hukseflux HFP01 plates, corrected to surface flux using the standard formula.\r\n-Cs = Bd(Cd+fSWC.Cw)\r\n-SC = DTs.Cs.d/Dtime\r\n-SHF = Plate Average + SC\r\n-DTs = change in average soil temperature from start to end of measurement period (first and last two minutes); d = plate depth 0.2 m; Bd = soil bulk density, 100 kg m-3; cd = Specific Heat Dry Soil, 840J kg-1 K-1; fSWC = fractional soil water content, measured or 0.9; cw = Specific Capacilty Heat of Water, 4190 J kg-1 K-1; Dtime = measurement period, 1800 s\r\n-Soil Moisture - soil water content measured with TDR probes, campbell CS616\r\n-WindSpd (measured) - measured by a Gill R3 then Windmaster sonic anemometer at 3.6 m\r\n-WindSpd 10 m - for most of the time period this is estimated from the turbulence measurements and 3.6 m windspeed but from 22/06/2016 a Gill Windsonic 2D anemeometer measures at 10 m\r\n-Wind Dir - measured by the sonic anemometer at 3.6 m\r\n-snow_depth_Avg - Campbell Scientific SR50A-L Sonic Ranging Sensor\r\n-Present Weather - Vaisala FD12P Present Weather Sensor\r\n-1 hr Past Weather - Vaisala FD12P Present Weather Sensor\r\n-Visibility - Vaisala FD12P Present Weather Sensor\r\n-Evaporation - to be estimated from the water-vapout flux measurements\r\n\r\nFor modelling purposes gapfilled (variables with _gf suffixes) times series will be included, they are created by linearly initially interpolating across upto an hours missing data, filling with colocated measurements (adjusted by linear interpolation with the core data), filling with measurements from nearby sites (adjusted by linear interpolation with the core data).\r\nTa_gf\r\nP_gf\r\nRH_gf\r\nTotal_Solar_gf\r\nRainfall_gf\r\nWindspd 10m_gf\r\nWind Dir_gf"
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                "abstract": "The dataset provides a Climate Data Record of Sea Ice Concentration (SIC) for the polar regions, derived from medium resolution passive microwave satellite data from the Advanced Microwave Scanning Radiometer series (AMSR-E and AMSR-2).  It is processed with an algorithm using coarse resolution (6 GHz and 37 GHz) imaging channels, and has been gridded at 50km grid spacing. This version of the product is v2.1, which is an extension of the version 2.0 Sea_Ice_cci dataset and has identical data until 2015-12-25.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea_Ice_CCI project. The EUMETSAT OSI SAF contributed with access and re-use of part of its processing software and facilities.\r\n\r\nA SIC CDR at 25km grid spacing is also available."
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                "short_code": "ob",
                "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci):  Sea Ice Concentration Climate Data Record from the AMSR-E and AMSR-2 instruments at 25km grid spacing, version 2.1",
                "abstract": "The dataset provides a Climate Data Record of Sea Ice Concentration (SIC) for the polar regions, derived from medium resolution passive microwave satellite data from the Advanced Microwave Scanning Radiometer series (AMSR-E and AMSR-2).  It is processed with an algorithm using medium resolution (19 GHz and 37 GHz) imaging channels, and has been gridded at 25km grid spacing.   This version of the product is v2.1, which is an extension of the v2.0 Sea_Ice_cci data and has identical data until 2015-12-25.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project. The EUMETSAT OSI SAF contributed with access and re-use of part of its processing software and facilities.\r\n\r\nA SIC CDR at 50 km grid spacing is also available."
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                "title": "MICROSCOPE: NCAS mobile X-band radar scan data from Davidstow Airfield - Version 2",
                "abstract": "This dataset contains scan data from the National Centre for Atmospheric Science's (NCAS) mobile X-band radar collected at the Davidstow Airfield, Cornwall, between June and August 2013 as part of the MICROphysicS of COnvective PrEcipitation (MICROSCOPE) project.\r\n\r\nThis version 2 dataset contains improved metadata and uses a revised processing method to improve data accuracy. Users should also note the change in filenaming convention for this instrument whereby the volume number given after the date-time part is no longer provided.\r\n\r\nThe X-band radar is operated as part of the NCAS Atmospheric Measurement Facility's (AMF)."
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                "short_code": "ob",
                "title": "CMIP5 20-Year AR5 Climatology Data for the IPCC DDC",
                "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013).  The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013).  Twenty-year AR5 climatologies and climatological anomalies are calculated for the averaging periods 2016-2035, 2046-2065, 2081-2100 for the CMIP5 scenario experiments rcp26, rcp45, rcp60 and rcp85. The climatologies are of global scope and are provided on latitude-longitude grids."
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                "short_code": "ob",
                "title": "CMIP5 30-Year Climatology Data for the IPCC DDC",
                "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013).  The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013).  Thirty-year climatologies and climatological anomalies are calculated for the CMIP5 experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85. The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids."
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                "short_code": "ob",
                "title": "CMIP5 20-Year Climatology Data for the IPCC DDC",
                "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013).  The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013).  Twenty-year climatologies and climatological anomalies are calculated for the CMIP5 experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85. The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids."
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                "short_code": "ob",
                "title": "ICE-D: NCAS mobile X-band radar scan data from the Praia International Airport, Santiago, Cape Verde, Version 1",
                "abstract": "This dataset contains scan data from the National Centre for Atmospheric Science's (NCAS) mobile X-band radar collected at Praia International Airport, Santiago, Cape Verde between July and August 2015 as part of the Ice in Clouds Experiment - Dust (ICE-D). The radar has Doppler and dual-polarisation capability and measures the location and intensity of precipitation, radial winds and polarisation parameters.\r\n\r\nThe X-band radar is operated as part of the NCAS Atmospheric Measurement Facility (AMF)."
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                "short_code": "ob",
                "title": "FAAM C026 CLARIFY Test 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 CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project."
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                "short_code": "ob",
                "title": "FAAM C017 STANCO 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 STANCO School and Training on Aircraft New and well-established techniques for Atmospheric Composition Observation project."
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                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for STANCO School and Training on Aircraft New and well-established techniques for Atmospheric Composition Observation project."
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                "title": "FAAM C019 Oil and Gas 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 NCAS general FAAM flying (SeptEx, Winter 2010, Oil & Gas) (Oil and Gas) project."
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                "title": "FAAM C016 STANCO 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 STANCO School and Training on Aircraft New and well-established techniques for Atmospheric Composition Observation project."
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                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ICARE-2 International Conference on Airborne Research for the Environment and EmeRGe-EU - Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global Scales  EUFAR project  projects."
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                "ob_id": 25141,
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                "short_code": "ob",
                "title": "FAAM C022 EMeRGe 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 EmeRGe-EU - Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global Scales  EUFAR project  (EMeRGe) project."
            },
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                "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a geographic projection (All Products), Version 3.1",
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                "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 3.1",
                "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 3.1 inherent optical properties dataset at 490 nm and the solar zenith angle.   Note, these data are also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320.   (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available."
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                "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a geographic projection, Version 3.1",
                "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites).  Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data.    Note, this dataset is also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320.   (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available."
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                "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 3.1",
                "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 3.1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available."
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                "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites).   Note, the chlorophyll-a data are also included in the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available."
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                "title": "S-RIP: Zonal-mean dynamical variables of global atmospheric reanalyses on pressure levels",
                "abstract": "This dataset contains zonal-mean atmospheric diagnostics computed from reanalysis datasets on pressure levels. Primary variables include temperature, geopotential height, and the three-dimensional wind field. Advanced diagnostics include zonal covariance terms that can be used to compute, for instance, eddy kinetic energy and eddy fluxes. Terms from the primitive zonal-mean momentum equation and the transformed Eulerian momentum equation are also provided.\r\n\r\nThis dataset was produced to facilitate the comparison of reanalysis datasets for the collaborators of the SPARC- Reanalysis Intercomparison Project (S-RIP) project. The dataset is substantially smaller in size compared to the full three dimensional reanalysis fields and uses unified numerical methods. The dataset includes all global reanalyses available at the time of its development and will be extended to new reanalysis products in the future."
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                "abstract": "The Geostationary Earth Radiation Budget (GERB-1) Level 2 High Resolution (L2HR) dataset contains accurate measurements of the Earth Radiation Budget.  Broadband measurements of earth-leaving radiances are made from which the emitted thermal and reflected solar components of the Earth Radiation Budget are derived. These data are available at a time resolution of 15 minutes for the region 60E to 60W, 60N to 60S and area are ideal for studying fast variations in the radiation budget such as those associated with changing cloud conditions, aerosol events and the diurnal cycle. Time and pixel centres matched with METEOSAT imager SEVIRI.\r\n\r\nThe level 2 HR (High Resolution) data are resolution enhanced snapshots of the top of atmosphere radiances and fluxes every 15 minutes. They are provided at the product acquisition time of the METEOSAT narrowband SEVIRI imager on a fixed equal viewing angle grid matched to 3x3 SEVIRI pixel grid-boxes.  This gives the HR product a temporal resolution of 15 minutes and a grid spacing of 9 km at the sub-satellite point. The time in the product name is the same as the SEVIRI product name time. Instantaneous accuracy at the HR scale is expected to be lower than for the lower spatial resolution GERB products as additional noise is introduced by the resolution enhancement, particularly for very inhomogeneous scenes and extreme angles. However, the HR product is recommended as the basis for users wishing to create custom averages over time and space and its production ensures that after appropriate averaging its accuracy is commensurate with the other GERB products\r\n\r\nThe GERB instrument was specifically designed to be mounted on a geostationary satellite and was carried onboard the Meteosat Second Generation satellite operated by European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). The second GERB instrument, GERB-1, was onboard Meteosat Second Generation satellite, MSG-2, and covers the period May 2007 to January 2013. \r\n\r\nUsers must read the quality summary associated with these data and will find details of user applied correction that are recommended to be applied to these datasets before using. Please cite Harries et al., 2005: The Geostationary Earth Radiation Budget Project, Bull. Amer. Meteorol. Soc., Vol. 86, 945-960, doi: 10.1175/BAMS-86-7-945."
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                "short_code": "ob",
                "title": "GERB-2: Level 2 High resolution (L2hr) top of atmosphere radiance and flux data",
                "abstract": "The Geostationary Earth Radiation Budget (GERB-2) Level 2 High Resolution (L2HR) dataset contains accurate measurements of the Earth Radiation Budget.  Broadband measurements of earth-leaving radiances are made from which the emitted thermal and reflected solar components of the Earth Radiation Budget are derived. These data are available at a time resolution of 15 minutes for the region 60E to 60W, 60N to 60S and area are ideal for studying fast variations in the radiation budget such as those associated with changing cloud conditions, aerosol events and the diurnal cycle. Time and pixel centres matched with METEOSAT imager SEVIRI.\r\n\r\nThe level 2 HR (High Resolution) data are resolution enhanced snapshots of the top of atmosphere radiances and fluxes every 15 minutes. They are provided at the product acquisition time of the METEOSAT narrowband SEVIRI imager on a fixed equal viewing angle grid matched to 3x3 SEVIRI pixel grid-boxes.  This gives the HR product a temporal resolution of 15 minutes and a grid spacing of 9 km at the sub-satellite point. The time in the product name is the same as the SEVIRI product name time. Instantaneous accuracy at the HR scale is expected to be lower than for the lower spatial resolution GERB products as additional noise is introduced by the resolution enhancement, particularly for very inhomogeneous scenes and extreme angles. However, the HR product is recommended as the basis for users wishing to create custom averages over time and space and its production ensures that after appropriate averaging its accuracy is commensurate with the other GERB products\r\n\r\nThe GERB instrument was specifically designed to be mounted on a geostationary satellite and was carried onboard the Meteosat Second Generation satellite operated by European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). The first GERB instrument, GERB-2, was onboard Meteosat Second Generation satellite, MSG-1, and covers the period March 2004 to May 2007. \r\n\r\nUsers must read the quality summary associated with these data and will find details of user applied correction that are recommended to be applied to these datasets before using. Please cite Harries et al., 2005: The Geostationary Earth Radiation Budget Project, Bull. Amer. Meteorol. Soc., Vol. 86, 945-960, doi: 10.1175/BAMS-86-7-945."
            },
            "onlineresource_set": []
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        {
            "ob_id": 25395,
            "uuid": "680f1f64c3b34502b344c63c6284496b",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/env-baseline/data/kirby-misperton/ghg/",
            "numberOfFiles": 44,
            "volume": 47337855,
            "fileFormat": "Data are NASA Ames formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25394,
                "uuid": "cd57ab55291c421799d75c795a87277d",
                "short_code": "ob",
                "title": "Environmental Baseline Project: Greenhouse gas analyser measurements from Kirby Misperton",
                "abstract": "This dataset contains carbon dioxide and methane measurements from the Kirby Misperton site.\r\n\r\nBritish Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public. \r\n\r\n-----------------------------------------------------------------------------------------------\r\nIf you use these data, please note the requirement to acknowledge use.\r\n\r\nUse of data and information from the project:\r\n\"Science-based environmental baseline monitoring associated with shale gas development in the Vale of Pickering, Yorkshire (including supplementary air quality monitoring in Lancashire)\", led by the British Geological Survey\r\n\r\nPermission for reproduction of data accessed from the CEDA website is granted subject to inclusion of the following acknowledgement:\r\n\"These data were produced by the Universities of Manchester and York (National Centre for Atmospheric Science) in a collaboration with the British Geological Survey and partners from the Universities of Birmingham, Bristol and Liverpool and Public Health England, undertaking a project grant-funded by the Department for Energy & Climate Change (DECC), 2015-2016. \"\r\n----------------------------------------------------------------------------------------------------------"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25399,
            "uuid": "6731ac42512b48d08d4adefc5d0c7ce7",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/env-baseline/data/kirby-misperton/hc",
            "numberOfFiles": 3,
            "volume": 14294,
            "fileFormat": "Data are NASA Ames formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25398,
                "uuid": "74d9b58cc12e48e08344068014de65b7",
                "short_code": "ob",
                "title": "Environmental Baseline Project: Volatile Organic Compounds (VOCs) measurements from Kirby Misperton",
                "abstract": "This dataset contains weekly volatile organic compounds (VOCs) measurements from the Kirby Misperton site.\r\n\r\nBritish Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public. \r\n\r\n-----------------------------------------------------------------------------------------------\r\nIf you use these data, please note the requirement to acknowledge use.\r\n\r\nUse of data and information from the project:\r\n\"Science-based environmental baseline monitoring associated with shale gas development in the Vale of Pickering, Yorkshire (including supplementary air quality monitoring in Lancashire)\", led by the British Geological Survey\r\n\r\nPermission for reproduction of data accessed from the CEDA website is granted subject to inclusion of the following acknowledgement:\r\n\"These data were produced by the Universities of Manchester and York (National Centre for Atmospheric Science) in a collaboration with the British Geological Survey and partners from the Universities of Birmingham, Bristol and Liverpool and Public Health England, undertaking a project grant-funded by the Department for Energy & Climate Change (DECC), 2015-2016. \"\r\n----------------------------------------------------------------------------------------------------------"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 25403,
            "uuid": "5f5b4d3c1d094e0b95407fdb92e88cd1",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/env-baseline/data/little-plumpton/aq/",
            "numberOfFiles": 61,
            "volume": 187111657,
            "fileFormat": "Data are NASA Ames formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 25402,
                "uuid": "4878d1fcd0694c07a0dc08ceaccae9e1",
                "short_code": "ob",
                "title": "Environmental Baseline Project: Air quality measurements from Little Plumpton",
                "abstract": "This dataset contains air quality measurements: atmospheric ozone, NOx and particulate matter, for the Little Plumpton site.\r\n\r\nBritish Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public. \r\n\r\n-----------------------------------------------------------------------------------------------\r\nIf you use these data, please note the requirement to acknowledge use.\r\n\r\nUse of data and information from the project:\r\n\"Science-based environmental baseline monitoring associated with shale gas development in the Vale of Pickering, Yorkshire (including supplementary air quality monitoring in Lancashire)\", led by the British Geological Survey\r\n\r\nPermission for reproduction of data accessed from the CEDA website is granted subject to inclusion of the following acknowledgement:\r\n\"These data were produced by the Universities of Manchester and York (National Centre for Atmospheric Science) in a collaboration with the British Geological Survey and partners from the Universities of Birmingham, Bristol and Liverpool and Public Health England, undertaking a project grant-funded by the Department for Energy & Climate Change (DECC), 2015-2016. \"\r\n----------------------------------------------------------------------------------------------------------"
            },
            "onlineresource_set": []
        }
    ]
}