Observation List

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                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 1.0 Data",
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                },
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                    "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available"
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                    "vocabService": "clipc_skos_vocab",
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                    "resolvedTerm": "Plymouth Marine Laboratory"
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                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_k_490",
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                    "resolvedTerm": "Orbview-2"
                },
                {
                    "ob_id": 10293,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_seaWiFs",
                    "resolvedTerm": "SeaWiFS"
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                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/product/prod_merged",
                    "resolvedTerm": "MERGED"
                },
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                    "ob_id": 10488,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_eos",
                    "resolvedTerm": "EOS"
                },
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                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_oceanCol",
                    "resolvedTerm": "ocean colour"
                },
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                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_meris",
                    "resolvedTerm": "MERIS"
                },
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                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level3S",
                    "resolvedTerm": "Level 3S"
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                {
                    "ob_id": 13548,
                    "uuid": "93aecb2607294e25bc4638adc800f8e7",
                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI) Dataset Collection",
                    "abstract": "Datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collection currently holds Version 1.0 data products, and later versions will be added in the future.   Note, version 2.0 data products are now currently available directly from the Ocean Colour CCI team (see link in the documentation section)."
                },
                {
                    "ob_id": 13330,
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                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 1.0 Data",
                    "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available"
                },
                {
                    "ob_id": 30128,
                    "uuid": "7fe9f59731ab47b6a20e792e0cba4641",
                    "short_code": "coll",
                    "title": "National Centre for Earth Observation (NCEO) partnered datasets",
                    "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)."
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            "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global remote sensing reflectance gridded on a geographic projection, Version 1.0",
            "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 1.0 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a daily time resolution.  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",
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                    "title": "ESA Ocean Colour Climate Change Initiative Project",
                    "abstract": "The European Space Agency Ocean Colour Climate Change Initiative (Ocean Colour CCI) project aims to produce long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n \r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided."
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                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_aqua",
                    "resolvedTerm": "Aqua"
                },
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                    "ob_id": 10242,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_modis",
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                },
                {
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                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org49",
                    "resolvedTerm": "Plymouth Marine Laboratory"
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                },
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                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_rrs",
                    "resolvedTerm": "remote sensing reflectance"
                },
                {
                    "ob_id": 10293,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_seaWiFs",
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                },
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                },
                {
                    "ob_id": 10488,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_eos",
                    "resolvedTerm": "EOS"
                },
                {
                    "ob_id": 10234,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_oceanCol",
                    "resolvedTerm": "ocean colour"
                },
                {
                    "ob_id": 10250,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_meris",
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                },
                {
                    "ob_id": 10175,
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                    "ob_id": 13548,
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                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI) Dataset Collection",
                    "abstract": "Datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collection currently holds Version 1.0 data products, and later versions will be added in the future.   Note, version 2.0 data products are now currently available directly from the Ocean Colour CCI team (see link in the documentation section)."
                },
                {
                    "ob_id": 13330,
                    "uuid": "f1a4a1d1208244c682603502d554bc12",
                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 1.0 Data",
                    "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available"
                },
                {
                    "ob_id": 30128,
                    "uuid": "7fe9f59731ab47b6a20e792e0cba4641",
                    "short_code": "coll",
                    "title": "National Centre for Earth Observation (NCEO) partnered datasets",
                    "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)."
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                    "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available"
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                    "ob_id": 13548,
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                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI) Dataset Collection",
                    "abstract": "Datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collection currently holds Version 1.0 data products, and later versions will be added in the future.   Note, version 2.0 data products are now currently available directly from the Ocean Colour CCI team (see link in the documentation section)."
                },
                {
                    "ob_id": 13330,
                    "uuid": "f1a4a1d1208244c682603502d554bc12",
                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 1.0 Data",
                    "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available"
                },
                {
                    "ob_id": 30128,
                    "uuid": "7fe9f59731ab47b6a20e792e0cba4641",
                    "short_code": "coll",
                    "title": "National Centre for Earth Observation (NCEO) partnered datasets",
                    "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)."
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            "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): 8-day global ocean colour data products gridded on a sinusoidal projection (All Products), Version 1.0",
            "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 all their Version 1.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at an 8-day time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\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 sinusoidal projection.)",
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                    "resolvedTerm": "Environmental Satellite"
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                    "vocabService": "clipc_skos_vocab",
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                    "resolvedTerm": "Plymouth Marine Laboratory"
                },
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                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_orbview2_prog",
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                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_seaWiFs",
                    "resolvedTerm": "SeaWiFS"
                },
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                    "resolvedTerm": "EOS"
                },
                {
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                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_oceanCol",
                    "resolvedTerm": "ocean colour"
                },
                {
                    "ob_id": 10175,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level3S",
                    "resolvedTerm": "Level 3S"
                },
                {
                    "ob_id": 10250,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_meris",
                    "resolvedTerm": "MERIS"
                },
                {
                    "ob_id": 10238,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_ocProd",
                    "resolvedTerm": "multiple products (chla, nlw, IOPs, etc)"
                },
                {
                    "ob_id": 10341,
                    "vocabService": "clipc_skos_vocab",
                    "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_8day",
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                    "ob_id": 13548,
                    "uuid": "93aecb2607294e25bc4638adc800f8e7",
                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI) Dataset Collection",
                    "abstract": "Datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collection currently holds Version 1.0 data products, and later versions will be added in the future.   Note, version 2.0 data products are now currently available directly from the Ocean Colour CCI team (see link in the documentation section)."
                },
                {
                    "ob_id": 13330,
                    "uuid": "f1a4a1d1208244c682603502d554bc12",
                    "short_code": "coll",
                    "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 1.0 Data",
                    "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available"
                },
                {
                    "ob_id": 30128,
                    "uuid": "7fe9f59731ab47b6a20e792e0cba4641",
                    "short_code": "coll",
                    "title": "National Centre for Earth Observation (NCEO) partnered datasets",
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                    "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI).     The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of  wavelength 490 nm.   Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available"
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                    "title": "European Space Agency (ESA) GlobSnow Snow Water Equivalent (SWE) v2.0 products",
                    "abstract": "The GlobSnow SWE product is the first satellite based daily SWE dataset for the non-alpine northern hemisphere that extends from 1979 to 2014. The previous existing daily SWE records have spanned a shorter time period (2002-2014) or described the snow conditions on a monthly basis for a similar period (1978-2014). \r\n\r\nThe GlobSnow SWE record utilizes a novel data-assimilation based approach for SWE estimation which combines weather station measurements of snow depth with satellite passive microwave measurements. This approach was shown to be superior to alternative algorithms which solely utilize satellite data through comparison with extensive ground reference datasets.\r\n\r\nThe GlobSnow-1 and -2 projects have developed a long term data record of SWE products covering the non-alpine Northern Hemisphere, based on a time series of remotely sensed observations from the Nimbus-7 SMMR, DMSP F8/F11/F13/F17 SSM/I(S) instruments and ground-based weather station measurements from 1979 until 2014. \r\n\r\nThere are three SWE products (all on the EASE model grid; see Armstrong and Brodzik, 1995):\r\n\r\n- Daily Snow Water Equivalent (Daily L3A SWE), snow water equivalent (mm) for each grid cell for all evaluated land areas of the Northern Hemisphere.\r\n\r\n- Weekly Aggregated Snow Water Equivalent (Weekly L3B SWE), calculated for each day based on a 7-day sliding time window aggregation of the daily SWE product.\r\n\r\n- Monthly Aggregated Snow Water Equivalent (Monthly L3B SWE), a single product for each calendar month, providing the average and maximum SWE, calculated from the weekly aggregated SWE product.\r\n\r\nThe GlobSnow-1 project resulted in two versions of the data record, SWE v1.0 and SWE v1.3 (available from FMI). The dataset produced in GlobSnow-2 is identified as the GlobSnow SWE v2.0 data record.\r\n\r\nIn addition to the SWE retrievals, the SWE products include information on the overall extent of snow cover. The information on snow extent is included in the product by utilizing the following coding for the SWE product, whereby SWE values of:\r\n - 0 mm denotes snow-free areas (Snow Extent 0%)\r\n - 0.001 mm denote areas with melting snow (Snow Extent undefined between 0% and 100%; no SWE retrieval because of the wet state of the snow cover)\r\n - > 0.001 mm denote areas with full snow cover (Snow Extent 100%)\r\n\r\nThe areas that have been flagged as snow-free or melted are identified using a time-series melt detection approach described in Takala et al. (2009). The areas that are identified as wet snow or have no SWE retrieval, but are identified as snow covered with the time-series melt-detection approach, are denoted with a SWE value of 0.001 mm. The areas that are determined as snow-free or melted by the melt-detection approach, are denoted with a SWE value of 0 mm. All the other areas show a retrieved SWE value (that is in all cases greater than 0.001 mm).\r\n\r\nThe project was coordinated by the Finnish Meteorological Institute (FMI). Other project partners involved are NR (Norwegian Computing Centre), ENVEO IT GmbH, GAMMA Remote Sensing AG, Finnish Environment Institute (SYKE), Environment Canada (EC), Northern Research Institute (Norut), University of Bern, Meteoswiss and ZAMG.\r\n"
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            "abstract": "The Quantifying the Amazon Isoprene Budget: Reconciling Top-down versus Bottom-up Emission Estimates project produced a unique high resolution model (GEOS-Chem version v8-03-01 - with modifications) for the Amazon, which simulated isoprene emissions and atmospheric chemistry. \r\n\r\nA nested-grid version of the GEOS-Chem chemistry transport model, constrained by isoprene emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN), and the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) bottom-up inventories, was used to evaluate the impact that surface isoprene emissions have on formaldehyde (HCHO) air-mass factors (AMFs) and vertical column densities (VCDs) over tropical South America during 2006, as observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI).\r\n\r\nResults of this project are presented in the following publication:\r\n\r\nBarkley, M. P., T. P. Kurosu, K. Chance, I. De Smedt, M. Van Roozendael, A. Arneth, D. Hagberg,\r\nand A. Guenther: Assessing sources of uncertainty in formaldehyde air mass factors over tropical\r\nSouth America: Implications for top-down isoprene emission estimates, J. Geophys. Res.,\r\n117, D13304, doi:10.1029/2011JD016827. 2012\r\n\r\nand model outputs associated to this project are archived at CEDA.\r\n\r\nThis was a NERC funded project.",
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                    "abstract": "The term climate change is now a household phrase and we are used to hearing about rising greenhouse gas levels and global warming. One of the first events that increased the public's awareness of environmental issues was the discovery of the Antarctic ozone hole in the 1980s. Ozone is a gas that comprises only a tiny fraction of all the gases that make up the atmosphere but it is very important in climate. At high altitudes (about 15 to 30 km), there is lots of ozone which is good thing for the planet, as it shields the Sun's harmful UV radiation. However, ozone is a toxic substance and if it builds up within the troposphere (the lowermost part of the atmosphere) and at the surface then this is not good. Tropospheric ozone is bad for us because it is (a) a greenhouse gas, and (b) and air pollutant that affects the human respiratory system and agricultural crop yields. Ozone is produced near the surface when substances known as volatile organic compounds (VOCs) are emitted from the surface and subsequently react within the atmosphere. VOCs can be emitted from human activities, but they are predominantly emitted by vegetation that grows on land. Of all the biogenic VOCs emitted into the atmosphere, none is more important than isoprene owing to its ability to quickly react with other compounds (to produce tropospheric ozone) and because it is emitted in large amounts. Isoprene is also important, as it is a source of very small particles called secondary organic aerosol (SOA) that scatter light, which influences how the Earth warms, and which also have adverse health effects. We need to know (a) when, (b) where and (c) how much isoprene is emitted into the atmosphere in order to better understand tropospheric ozone and SOA. Currently we use generic computer models that are based on observations to simulate the amount of isoprene emitted from different types of vegetation, such as trees or grasses. Isoprene emissions from the Amazon Basin, which contains the world's largest rain forest and is thought to be one of the biggest isoprene sources, are poorly quantified since it is very difficult to measure the emissions in this largely inaccessible and remote region. Satellite observations of a gas called formaldehyde (HCHO), contain information on isoprene emissions, and can be used to determine the amount of isoprene emitted from terrestrial vegetation. The overall goal of my proposal is to use satellite observations of HCHO to accurately quantify isoprene emissions from the Amazon Basin. To achieve this goal I will develop a new unique high resolution model for the Amazon, which will be able to simulate isoprene emissions and atmospheric chemistry at finer spatial scales than have been able previously. I will then compare the isoprene emissions from this 'bottom-up' model with the 'top-down' isoprene emissions inferred from the satellite observations of HCHO, to identify regions or time periods where there is significant disagreement between the model and the observations, which highlights where we have poor understanding of the isoprene emissions. I will then develop an improved isoprene emission model by fine tuning the 'bottom-up' emission model to the inferred 'top-down' emissions, taking into account individual scenes (utilizing the high spatial resolution of the nested-grid) and different seasons. By reconciling the differences between the 'bottom-up' model and the 'top-down' emissions we will gain a more accurate estimate of how much isoprene is emitted from the Amazon, and more importantly gain a better understanding of the factors that influence when it is emitted. This research is important because the Amazon Basin is also one of the regions identified as being most susceptible to climate change, and it is crucial we determine the key factors that influence its isoprene emissions in order to improve confidence in our ability to predict future climate. \r\n\r\nObjectives: \r\n\r\n1) Develop a high resolution, nested-grid chemistry-transport model, centred over the Amazon, which will be driven using two bottom-up isoprene emission models that are based on fundamentally different approaches to simulate isoprene fluxes \r\n\r\n2) Compare the simulated isoprene emissions and oxidation products, from the two bottom-up inventories, against each other and in situ observations to assess which is more accurate \r\n\r\n3) Optimally estimate Amazon isoprene emissions using a Bayesian approach constrained by satellite observations of formaldehyde \r\n\r\n4) Develop emission model parameterizations that will reconcile the spatial and temporal differences between the top-down and bottom-up estimates \r\n\r\n5) Quantify the difference of the bottom-up and top-down isoprene emissions on the Amazonian atmospheric chemistry\r\n\r\nThis project was funded by NERC under grant NE/G013810/1."
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                    "title": "Limb Infra-red Monitor of the Stratosphere (LIMS) Instrument: Vertical Profiles of Temperature and Concentration of Ozone, Water Vapour, Nitrogen Dioxide, and Nitric Acid",
                    "abstract": "Infrared radiances from the Limb Infrared Monitor of the Stratosphere (LIMS) instrument, mounted on the Nimbus-7 satellite, were stored on a Radiance Archive Tape (RAT). RAT data was used to derive a series of products, two of which are held here. Firstly, the LIMS Inverted Profile Archival Tape (LAIPAT). This dataset contains radiances (from RAT), which are used to derive daily inverted profiles of temperature, and mixing ratios, water vapour, nitric acid, and nitrogen dioxide. Profiles are geolocated. Secondly, the LIMS Map Archival Tape (LAMAT). This dataset is processed to create daily maps in the form of Fourier coefficients for each parameter at 18 pressure levels (from 0.05 to 100 mbar). Data are organised into 38 4 deg. latitude bands. Data for the daily maps are interpolated to the two synoptic time (0000 GMT for night and 1200 GMT for day). Also included is the day/night combined (averaged) data. This dataset is public. Please note that a major reprocessing of the Nimbus 7 LIMS data has recently been completed. The purpose of this activity is to take advantage of the changes in the spectral line parameters that have occurred since the original archived version was created and to generate a data version that is compatible with the UARS data sets. Improvements in the algorithm have also been made. More information is available from the LIMS homepage at http://lims.gats-inc.com/ and version 6 data can be downloaded from GES DAAC."
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