Result List

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                "title": "WCRP CMIP6: the EC-Earth-Consortium team EC-Earth3 model output for the \"ssp534-over\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the EC-Earth-Consortium team EC-Earth3 model output for the \"overshoot of 3.4 W/m**2 branching from ssp585 in 2040\" (ssp534-over) experiment. These are available at the following frequencies: Amon, LImon, Lmon, Omon, SImon and day. The runs included the ensemble member: r101i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the EC-Earth-Consortium team team consisted of the following agencies: La Agencia Estatal de Meteorología (AEMET), Barcelona Supercomputing Centre (BSC), Institute of Atmospheric Sciences and Climate (CNR-ISAC), Danish Meteorological Institute (DMI), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Helmholtz Centre for Ocean Research Kiel (Geomar), Irish Centre for High-End Computing (ICHEC), International Centre for Theoretical Physics (ICTP), Instituto Dom Luiz (IDL), Institute for Marine and Atmospheric research Utrecht (IMAU), Portuguese Institute for Sea and Atmosphere (IPMA), KIT Karlsruhe Institute of Technology, Royal Netherlands Meteorological Institute (KNMI), Lund University, Met Eireann, The Netherlands eScience Center (NLeSC), Norwegian University of Science and Technology (NTNU), University of Oxford, SURFsara, Swedish Meteorological and Hydrological Institute (SMHI), Stockholm University, Unite ASTR, University College Dublin, University of Bergen, University of Copenhagen, University of Helsinki, University of Santiago de Compostela, Uppsala University, University of Utrecht, Vrije Universiteit Amsterdam and Wageningen University.\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"ssp119\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"low-end scenario reaching 1.9 W m-2, based on SSP1\" (ssp119) experiment. These are available at the following frequencies: Amon, Eday, Emon, LImon, Lmon, Oday, Ofx, Omon, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the EC-Earth-Consortium team team consisted of the following agencies: La Agencia Estatal de Meteorología (AEMET), Barcelona Supercomputing Centre (BSC), Institute of Atmospheric Sciences and Climate (CNR-ISAC), Danish Meteorological Institute (DMI), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Helmholtz Centre for Ocean Research Kiel (Geomar), Irish Centre for High-End Computing (ICHEC), International Centre for Theoretical Physics (ICTP), Instituto Dom Luiz (IDL), Institute for Marine and Atmospheric research Utrecht (IMAU), Portuguese Institute for Sea and Atmosphere (IPMA), KIT Karlsruhe Institute of Technology, Royal Netherlands Meteorological Institute (KNMI), Lund University, Met Eireann, The Netherlands eScience Center (NLeSC), Norwegian University of Science and Technology (NTNU), University of Oxford, SURFsara, Swedish Meteorological and Hydrological Institute (SMHI), Stockholm University, Unite ASTR, University College Dublin, University of Bergen, University of Copenhagen, University of Helsinki, University of Santiago de Compostela, Uppsala University, University of Utrecht, Vrije Universiteit Amsterdam and Wageningen University.\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"ssp126\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"update of RCP2.6 based on SSP1\" (ssp126) experiment. These are available at the following frequencies: Amon, Eday, Emon, LImon, Lmon, Oday, Ofx, Omon, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the EC-Earth-Consortium team team consisted of the following agencies: La Agencia Estatal de Meteorología (AEMET), Barcelona Supercomputing Centre (BSC), Institute of Atmospheric Sciences and Climate (CNR-ISAC), Danish Meteorological Institute (DMI), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Helmholtz Centre for Ocean Research Kiel (Geomar), Irish Centre for High-End Computing (ICHEC), International Centre for Theoretical Physics (ICTP), Instituto Dom Luiz (IDL), Institute for Marine and Atmospheric research Utrecht (IMAU), Portuguese Institute for Sea and Atmosphere (IPMA), KIT Karlsruhe Institute of Technology, Royal Netherlands Meteorological Institute (KNMI), Lund University, Met Eireann, The Netherlands eScience Center (NLeSC), Norwegian University of Science and Technology (NTNU), University of Oxford, SURFsara, Swedish Meteorological and Hydrological Institute (SMHI), Stockholm University, Unite ASTR, University College Dublin, University of Bergen, University of Copenhagen, University of Helsinki, University of Santiago de Compostela, Uppsala University, University of Utrecht, Vrije Universiteit Amsterdam and Wageningen University.\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"ssp245\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"update of RCP4.5 based on SSP2\" (ssp245) experiment. These are available at the following frequencies: Amon, Eday, Emon, LImon, Lmon, Oday, Ofx, Omon, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the EC-Earth-Consortium team team consisted of the following agencies: La Agencia Estatal de Meteorología (AEMET), Barcelona Supercomputing Centre (BSC), Institute of Atmospheric Sciences and Climate (CNR-ISAC), Danish Meteorological Institute (DMI), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Helmholtz Centre for Ocean Research Kiel (Geomar), Irish Centre for High-End Computing (ICHEC), International Centre for Theoretical Physics (ICTP), Instituto Dom Luiz (IDL), Institute for Marine and Atmospheric research Utrecht (IMAU), Portuguese Institute for Sea and Atmosphere (IPMA), KIT Karlsruhe Institute of Technology, Royal Netherlands Meteorological Institute (KNMI), Lund University, Met Eireann, The Netherlands eScience Center (NLeSC), Norwegian University of Science and Technology (NTNU), University of Oxford, SURFsara, Swedish Meteorological and Hydrological Institute (SMHI), Stockholm University, Unite ASTR, University College Dublin, University of Bergen, University of Copenhagen, University of Helsinki, University of Santiago de Compostela, Uppsala University, University of Utrecht, Vrije Universiteit Amsterdam and Wageningen University.\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"ssp370\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"gap-filling scenario reaching 7.0 based on SSP3\" (ssp370) experiment. These are available at the following frequencies: Amon, Eday, LImon, Lmon, Oday, Ofx, Omon, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the EC-Earth-Consortium team team consisted of the following agencies: La Agencia Estatal de Meteorología (AEMET), Barcelona Supercomputing Centre (BSC), Institute of Atmospheric Sciences and Climate (CNR-ISAC), Danish Meteorological Institute (DMI), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Helmholtz Centre for Ocean Research Kiel (Geomar), Irish Centre for High-End Computing (ICHEC), International Centre for Theoretical Physics (ICTP), Instituto Dom Luiz (IDL), Institute for Marine and Atmospheric research Utrecht (IMAU), Portuguese Institute for Sea and Atmosphere (IPMA), KIT Karlsruhe Institute of Technology, Royal Netherlands Meteorological Institute (KNMI), Lund University, Met Eireann, The Netherlands eScience Center (NLeSC), Norwegian University of Science and Technology (NTNU), University of Oxford, SURFsara, Swedish Meteorological and Hydrological Institute (SMHI), Stockholm University, Unite ASTR, University College Dublin, University of Bergen, University of Copenhagen, University of Helsinki, University of Santiago de Compostela, Uppsala University, University of Utrecht, Vrije Universiteit Amsterdam and Wageningen University.\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"ssp585\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the EC-Earth-Consortium team EC-Earth3-Veg-LR model output for the \"update of RCP8.5 based on SSP5\" (ssp585) experiment. These are available at the following frequencies: Amon, Eday, Emon, LImon, Lmon, Oday, Ofx, Omon, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the EC-Earth-Consortium team team consisted of the following agencies: La Agencia Estatal de Meteorología (AEMET), Barcelona Supercomputing Centre (BSC), Institute of Atmospheric Sciences and Climate (CNR-ISAC), Danish Meteorological Institute (DMI), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Helmholtz Centre for Ocean Research Kiel (Geomar), Irish Centre for High-End Computing (ICHEC), International Centre for Theoretical Physics (ICTP), Instituto Dom Luiz (IDL), Institute for Marine and Atmospheric research Utrecht (IMAU), Portuguese Institute for Sea and Atmosphere (IPMA), KIT Karlsruhe Institute of Technology, Royal Netherlands Meteorological Institute (KNMI), Lund University, Met Eireann, The Netherlands eScience Center (NLeSC), Norwegian University of Science and Technology (NTNU), University of Oxford, SURFsara, Swedish Meteorological and Hydrological Institute (SMHI), Stockholm University, Unite ASTR, University College Dublin, University of Bergen, University of Copenhagen, University of Helsinki, University of Santiago de Compostela, Uppsala University, University of Utrecht, Vrije Universiteit Amsterdam and Wageningen University.\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Institut Pierre-Simon Laplace (IPSL) IPSL-CM5A2-INCA model output for the \"update of RCP2.6 based on SSP1\" (ssp126) experiment. These are available at the following frequencies: 3hr, 6hrLev, 6hrPlev, AERmon, AERmonZ, Amon, CFmon, E3hr, Eday, EdayZ, Efx, Emon, LImon, Lmon, Oday, Odec, Ofx, Omon, Oyr, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: Institut Pierre-Simon Laplace (IPSL) IPSL-CM5A2-INCA model output for the \"ssp370\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Institut Pierre-Simon Laplace (IPSL) IPSL-CM5A2-INCA model output for the \"gap-filling scenario reaching 7.0 based on SSP3\" (ssp370) experiment. These are available at the following frequencies: 3hr, 6hrLev, 6hrPlev, AERday, AERhr, AERmon, AERmonZ, Amon, CFday, CFmon, CFsubhr, E3hr, Eday, EdayZ, Efx, Emon, LImon, Lmon, Oday, Odec, Ofx, Omon, Oyr, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: the MIROC team MIROC-ES2L model output for the \"ssp534-over\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the MIROC team MIROC-ES2L model output for the \"overshoot of 3.4 W/m**2 branching from ssp585 in 2040\" (ssp534-over) experiment. These are available at the following frequencies: 3hr, 6hrPlev, 6hrPlevPt, AERmon, Amon, CFmon, Eday, LImon, Lmon, Ofx, Omon, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f2.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the MIROC team team consisted of the following agencies: Atmosphere and Ocean Research Institute (AORI), Centre for Climate System Research - National Institute for Environmental Studies (CCSR-NIES) and Atmosphere and Ocean Research Institute (AORI).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: Met Office Hadley Centre (MOHC) HadGEM3-GC31-MM model output for the \"ssp126\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Met Office Hadley Centre (MOHC) HadGEM3-GC31-MM model output for the \"update of RCP2.6 based on SSP1\" (ssp126) experiment. These are available at the following frequencies: 3hr, 6hrLev, 6hrPlev, 6hrPlevPt, AERday, AERmon, AERmonZ, Amon, CFmon, E3hr, Eday, EdayZ, Emon, EmonZ, LImon, Lmon, Oday, Omon, SIday, SImon and day. The runs included the ensemble member: r1i1p1f3.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "title": "WCRP CMIP6: NASA Goddard Institute for Space Studies (NASA GISS) GISS-E2-1-G model output for the \"ssp434\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the NASA Goddard Institute for Space Studies (NASA GISS) GISS-E2-1-G model output for the \"gap-filling scenario reaching 3.4 based on SSP4\" (ssp434) experiment. These are available at the following frequencies: Amon, LImon, Lmon, Omon, SImon and day. The runs included the ensemble members: r1i1p1f2 and r1i1p3f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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                "short_code": "ob",
                "title": "WCRP CMIP6: NASA Goddard Institute for Space Studies (NASA GISS) GISS-E2-1-G model output for the \"ssp460\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the NASA Goddard Institute for Space Studies (NASA GISS) GISS-E2-1-G model output for the \"update of RCP6.0 based on SSP4\" (ssp460) experiment. These are available at the following frequencies: Amon, LImon, Lmon, Omon, SImon and day. The runs included the ensemble members: r1i1p1f2 and r1i1p3f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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        {
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                "short_code": "ob",
                "title": "WCRP CMIP6: Norwegian Climate Centre (NCC) NorESM2-LM model output for the \"ssp534-over\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Norwegian Climate Centre (NCC) NorESM2-LM model output for the \"overshoot of 3.4 W/m**2 branching from ssp585 in 2040\" (ssp534-over) experiment. These are available at the following frequencies: AERmon, Amon, CFmon, Emon, LImon, Lmon, Oday, Ofx, Omon, Oyr, SIday, SImon and fx. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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            "onlineresource_set": []
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        {
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            "observation": {
                "ob_id": 34551,
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                "title": "WCRP CMIP6: the NIMS-KMA team UKESM1-0-LL model output for the \"ssp126\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the NIMS-KMA team UKESM1-0-LL model output for the \"update of RCP2.6 based on SSP1\" (ssp126) experiment. These are available at the following frequencies: AERday, AERmon, AERmonZ, Amon, CFmon, Eday, EdayZ, Emon, EmonZ, LImon, Omon, SIday, SImon and day. The runs included the ensemble members: r13i1p1f2, r14i1p1f2 and r15i1p1f2.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the NIMS-KMA team team consisted of the following agencies: National Institute of Meteorological Sciences (NIMS) and Korea Meteorological Administration (KMA).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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        {
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            "observation": {
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                "short_code": "ob",
                "title": "WCRP CMIP6: the NIMS-KMA team UKESM1-0-LL model output for the \"ssp585\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the NIMS-KMA team UKESM1-0-LL model output for the \"update of RCP8.5 based on SSP5\" (ssp585) experiment. These are available at the following frequencies: 3hr, AERday, AERmon, AERmonZ, Amon, CFmon, E3hr, Eday, EdayZ, Emon, EmonZ, LImon, Omon, SIday, SImon and day. The runs included the ensemble members: r13i1p1f2, r14i1p1f2 and r15i1p1f2.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe the NIMS-KMA team team consisted of the following agencies: National Institute of Meteorological Sciences (NIMS) and Korea Meteorological Administration (KMA).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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            "onlineresource_set": []
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        {
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cmip6/data/CMIP6/CMIP/KIOST/KIOST-ESM/1pctCO2",
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                "ob_id": 34563,
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                "short_code": "ob",
                "title": "WCRP CMIP6: Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"1pctCO2\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"1 percent per year increase in CO2\" (1pctCO2) experiment. These are available at the following frequencies: 3hr, Amon, Oday, Omon, SIday, SImon and day. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cmip6/data/CMIP6/CMIP/KIOST/KIOST-ESM/abrupt-4xCO2",
            "numberOfFiles": 78,
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            "oldDataPath": [],
            "observation": {
                "ob_id": 34567,
                "uuid": "41e95a4652b140198b51d7061efdf69e",
                "short_code": "ob",
                "title": "WCRP CMIP6: Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"abrupt-4xCO2\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"abrupt quadrupling of CO2\" (abrupt-4xCO2) experiment. These are available at the following frequencies: 3hr, Amon, Oday, Omon, SIday, SImon and day. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
            },
            "onlineresource_set": []
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            "curationCategory": "A",
            "dataPath": "/badc/cmip6/data/CMIP6/CMIP/KIOST/KIOST-ESM/amip",
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            "observation": {
                "ob_id": 34570,
                "uuid": "1c98e90bab734709b3cc906aa24550c5",
                "short_code": "ob",
                "title": "WCRP CMIP6: Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"amip\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"AMIP\" (amip) experiment. These are available at the following frequencies: 3hr, Amon, LImon, Lmon, SImon and day. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
            },
            "onlineresource_set": []
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        {
            "ob_id": 34574,
            "uuid": "179efce23e224358aebbe0efdd424b12",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cmip6/data/CMIP6/CMIP/KIOST/KIOST-ESM/historical",
            "numberOfFiles": 452,
            "volume": 1328568774734,
            "fileFormat": "Data are netCDF formatted.",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 34573,
                "uuid": "1b1131f6298541be8d5fa58a3b5c8c28",
                "short_code": "ob",
                "title": "WCRP CMIP6: Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"historical\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"all-forcing simulation of the recent past\" (historical) experiment. These are available at the following frequencies: 3hr, 6hrLev, 6hrPlevPt, AERmon, Amon, E3hr, Eday, Emon, LImon, Lmon, Oday, Ofx, Omon, Oyr, SIday, SImon and day. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
            },
            "onlineresource_set": []
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        {
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            "uuid": "90f410df5e0c4f75a17088bbd28db7b0",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cmip6/data/CMIP6/CMIP/KIOST/KIOST-ESM/piControl",
            "numberOfFiles": 853,
            "volume": 2403755792214,
            "fileFormat": "Data are netCDF formatted.",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 34576,
                "uuid": "39eb4743f37443288efd18a07179d83b",
                "short_code": "ob",
                "title": "WCRP CMIP6: Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"piControl\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Korea Institute of Ocean Science and Technology (KIOST) KIOST-ESM model output for the \"pre-industrial control\" (piControl) experiment. These are available at the following frequencies: 3hr, 6hrPlevPt, Amon, Eday, LImon, Lmon, Oday, Ofx, Omon, Oyr, SIday, SImon and day. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34581,
            "uuid": "cc90a0cb39f24d0ba2df491b16bd7591",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/cmip6/data/CMIP6/HighResMIP/CAMS/CAMS-CSM1-0/highresSST-present",
            "numberOfFiles": 2,
            "volume": 920186038,
            "fileFormat": "Data are netCDF formatted.",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 34580,
                "uuid": "37c6f1c90f86427297b4e0dfa2fce11e",
                "short_code": "ob",
                "title": "WCRP CMIP6: Chinese Academy of Meteorological Sciences (CAMS) CAMS-CSM1-0 model output for the \"highresSST-present\" experiment",
                "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Chinese Academy of Meteorological Sciences (CAMS) CAMS-CSM1-0 model output for the \"forced atmosphere experiment for 1950-2014\" (highresSST-present) experiment. These are available at the following frequency: Amon. The runs included the ensemble member: r1i1p1f1.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
            },
            "onlineresource_set": []
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        {
            "ob_id": 34592,
            "uuid": "6bbbbf81b0864c2899157dde405a0798",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/ar6_wg1/data/spm/spm_09/v20220105",
            "numberOfFiles": 4,
            "volume": 6562,
            "fileFormat": "Data are netCDF formatted.",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 34591,
                "uuid": "e1ff6e07cd624c59a7e7983ce60add44",
                "short_code": "ob",
                "title": "Summary for Policymakers of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure SPM.9 (v20220105)",
                "abstract": "Data for Figure SPM.9 from the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure SPM.9 provides a synthesis of the number of AR6 WGI reference regions where climatic impact-drivers are projected to change.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\n\r\nIPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001.\r\n\r\n\r\n---------------------------------------------------\r\nTemporal range\r\n---------------------------------------------------\r\n\r\nNumber of land & coastal regions and open-ocean regions where each Climatic Impact-Drivers (CID) is projected to increase or decrease with high confidence or medium confidence. Changes refer to a 20–30 year period centred around 2050 and/or consistent with 2°C global warming compared to a similar period within 1960-2014, except for hydrological drought and agricultural and ecological drought which is compared to 1850-1900. \r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels, with data provided for all panels in a single file named consolidated_data_figure_SPM9.csv\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\nThis dataset contains the number of AR6 WGI regions where climatic impact-drivers are projected to change if a global warming level of 2°C is reached compared to a climatological reference period included within 1960-2014.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\nData file: consolidated_data_figure_SPM.9.csv (count of regions with increasing or decreasing changes in climatic impact-drivers); relates to panel (a) and panel (b) and it's shown by the bars in the figure. The first row of data relates to the darker purple bars, the second row to the lighter purple bars, the third row to the lighter brown bars and the fourth row to the darker brown bars. Row 5 represents the maximum number of regions for which each climatic impact-driver is relevant. It is shown on the figure as the lighter-shaded ‘envelope’.\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n\r\n - Link to origin of figure (IPCC WG1 Summary for Policy Makers)\r\n - Link to the report webpage, which includes the report component containing the figure (Summary for Policymakers)\r\n - Link to the Interactive Atlas webpage\r\n - Link to the figure on the IPCC AR6 website"
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            "short_code": "result",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 34603,
                "uuid": "d1c2018e17d54df384fdbf562d2a9e8b",
                "short_code": "ob",
                "title": "ESA Water Vapour Climate Change Initiative (Water_Vapour_cci): Total Column Water Vapour monthly gridded data over land at 0.05 degree resolution, version 3.2",
                "abstract": "This dataset consists of monthly averaged total column water vapour (TCWV) over land, at a 0.05 degree resolution, observed by various satellite instruments.   It has been produced by the European Space Agency Water Vapour Climate Change Initiative (Water_Vapour_cci), and forms part of their TCVW over land Climate Data Record -1  (TCWV-land (CDR-1).\r\n\r\nThis version of the data is v3.2.  This is an updated dataset, which fixes an issue with the filtering of the v3.1 data."
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            "onlineresource_set": []
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        {
            "ob_id": 34638,
            "uuid": "6d51dfc061904c968c73b98489f8541d",
            "short_code": "result",
            "curationCategory": "A",
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            "observation": {
                "ob_id": 34639,
                "uuid": "8194b416cbee482b89e0dfbe17c5786c",
                "short_code": "ob",
                "title": "CHESS-SCAPE: Future projections of meteorological variables at 1 km resolution for the United Kingdom 1980-2080 derived from UK Climate Projections   2018",
                "abstract": "Gridded daily meteorological variables over the United Kingdom at 1 km resolution for the years 1980-2080. This dataset is an ensemble of four different realisations of future climate for each of four different representative concentration pathway scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5), provided both with and without bias correction. This dataset contains time series of daily mean values of air temperature (K), specific humidity (kg kg-1), relative humidity (%), wind speed (m s-1), downward longwave radiation (W m-2), downward shortwave radiation (W m-2), precipitation (kg m-2 s-2) and surface air pressure (Pa). It also contains time series of daily minimum air temperature (K), daily maximum air temperature (K) and daily temperature range (K). The data are provided in gridded netCDF files at 1 km resolution aligned to the Ordnance Survey / British National Grid. There is one file for each variable for each month of the daily data. Also provided are monthly, seasonal and annual means, for which there is one file for each variable for each time resolution. Additionally twenty year mean-monthly (Jan-Dec) climatologies at ten year intervals are provided, for which there is one file for each variable for each twenty year time slice. The projections use a 360-day calendar, where each month consists of 30 days."
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            "onlineresource_set": []
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        {
            "ob_id": 34646,
            "uuid": "0d607c03dff245c6a9d2a2bb41ba91a0",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/iasi_ch4_ral/data/metop-b/l2/tir/v2.0/",
            "numberOfFiles": 242324,
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            "observation": {
                "ob_id": 33460,
                "uuid": "4bbcb1722f2842c1b0a5ebc19160a863",
                "short_code": "ob",
                "title": "STFC RAL methane retrievals from IASI on board MetOp-B, version 2.0",
                "abstract": "This Infrared Atmospheric Sounding Interferometer (IASI) methane dataset contains height-resolved and column-averaged volume mixing ratios of atmospheric methane (CH4) retrieved from the IASI instrument on the MetOp-B satellite. It also includes column-averaged water vapour (H2O), a scale factor for the HDO (water vapour isotopologue) volume mixing ratio profile, surface temperature, effective cloud fraction, effective cloud-top pressure and scale factors for two systematic residual spectra which are jointly retrieved from the spectral range 1232.25-1290.00 cm-1.   This dataset was produced by Version 2.0 of the Rutherford Appleton Laboratory's (RAL's) IASI optimal estimation scheme to retrieve methane, which takes as input temperature and water vapour profiles and surface spectral emissivity pre-retrieved by RAL's Infrared and Microwave Scheme applied to IASI, MHS and AMSU-A on MetOp-B. The dataset additionally contains selected a priori values and uncertainties adopted in the optimal estimation scheme and retrieval output diagnostics such as the retrieval cost and the averaging kernels.\r\n\r\nDevelopment of the Version 2.0 scheme and its application to MetOp-A (2007-2017, http://dx.doi.org/10.5285/f717a8ea622f495397f4e76f777349d1)  was funded by the National Centre for Earth Observation (NCEO) under the UK Natural Environment Research Council (NERC) with additional funding from EUMETSAT. Adaptation to MetOp-B and production of the IASI MetOp-B methane dataset 01/2018-03/2021 were funded by NCEO and ESA Contract No. 4000129987/20/I-DT Methane+.\r\n\r\nData were produced by the United Kingdom Research and Innovation (UKRI) Science and Technology Facilities Council (STFC) Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL)."
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            "oldDataPath": [],
            "observation": {
                "ob_id": 33060,
                "uuid": "8847a05eeda646a29da58b42bdf2a87c",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2020), version 2.0",
                "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from MODIS, produced by the Snow project of the ESA Climate Change Initiative programme.\r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. \r\n\r\nThe SCFG time series provides daily products for the period 2000 – 2020. \r\n\r\nThe SCFG product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the Snow_cci SCFG product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFG product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 µm and 1.6 µm, and an emissive band centred at about 11 µm.   The Snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. \r\n\r\nThe main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the usage of spatially variable background reflectance and forest reflectance maps instead of global constant values for snow free land and forest, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data, and (v) the update of the global forest canopy transmissivity based on forest density from Hansen et al. (2013) and forest type layers from Land Cover CCI (Defourny, 2019) to assure in forested areas consistency of the SCFG and the SCFV CRDP v2.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/ebe625b6f77945a68bda0ab7c78dd76b) using the same retrieval approach.\r\n\r\nImprovements of the Snow_cci SCFG version 2.0 compared to the Snow_cci version 1.0 include (i) the utilisation of an updated background reflectance map derived from statistical analyses of an extended MODIS time series, (ii) an update of the forest canopy transmissivity map, and (iii) an update of the constant reflectance value for wet snow based on the analysis of time series of the MODIS reflectance at 0.55 µm.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFG product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nThe SCFG product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nENVEO is responsible for the SCFG product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFG products are available but have data gaps."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34650,
            "uuid": "f48e32d382b14adc8e28e2943a87842f",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/TROPBGC/data/",
            "numberOfFiles": 10,
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            "fileFormat": "Data are netCDF formatted",
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            "observation": {
                "ob_id": 34649,
                "uuid": "fbf06d6f3c9b4469926d79be38a5cf63",
                "short_code": "ob",
                "title": "Anomalies of Biogeochemical Parameters in the Tropical Region (TROPBGC)",
                "abstract": "This dataset contains biogeochemical parameter anomalies, calculated from Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua) (Chlorophyll Concentration), GLOBAL_MULTIYEAR_BGC_001_029 and MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008 datasets. \r\n\r\nData was taken from existing datasets, from National Aeronautics and Space Administration (NASA) the MODIS-Aqua satellite (chlorophyll) and from Copernicus Marine System 2 biogeochemical sets called GLOBAL_MULTIYEAR_BGC_001_029 (https://doi.org/10.48670/moi -00019) and MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008 (https://doi.org/10.48670/moi-00047) from which the anomalies were computed and the files were created using the following Matlab functions:\r\n\r\n1- Humberto L. Varona. (2021). mNC: A tool for Oceanographers and Meteorologists to easily create their NetCDF files using Matlab (1.0). Zenodo. https://doi.org/10.5281/zenodo.5572749\r\n2- Humberto L. Varona. (2021). CalcPlotAnomaly: Matlab function set for the calculation and plotting of anomalies (1.01). Zenodo. https://doi.org/10.5281/zenodo.5576889\r\n\r\nAnomalies were computed for the entire tropic.\r\n\r\nThe parameters are: Chlorophyll concentration, pH, Surface aqueous partial pressure of CO2 , NO3, Surface downward flux of total CO2, PO4, SI, O2, Fe and concentration of phytoplankton.\r\n\r\nAll files are in NetCDF format\r\n\r\nThis dataset was produced for the project Tropical and South Atlantic climate-based marine ecosystem predictions for sustainable management, to Tropical Atlantic Interdisciplinary Laboratory on physical, biogeochemical, ecological and human dynamics (IJL TAPIOCA) and the Brazilian Research Network on Global Climate Change (Rede CLIMA)."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34663,
            "uuid": "b82e12873e334f6ab33536be7a04eded",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/water_vapour/data/TCWV-land/L3/v3.2/0.5deg/monthly/",
            "numberOfFiles": 187,
            "volume": 224072064,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
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            "observation": {
                "ob_id": 34604,
                "uuid": "80ad33b237084a8dbfb81ec5414e68dd",
                "short_code": "ob",
                "title": "ESA Water Vapour Climate Change Initiative (Water_Vapour_cci): Total Column Water Vapour monthly gridded data over land at 0.5 degree resolution, version 3.2",
                "abstract": "This dataset consists of monthly averaged total column water vapour (TCWV) over land, at a 0.5 degree resolution, observed by various satellite instruments. It has been produced by the European Space Agency Water Vapour Climate Change Initiative (Water_Vapour_cci), and forms part of their TCVW over land Climate Data Record -1 (TCWV-land (CDR-1).\r\n\r\nThis version of the data is v3.2.  This is an updated dataset, which fixes an issue with the filtering of the v3.1 data."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34665,
            "uuid": "4221814d4b604862918b0f75c2cca67f",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISD/subdaily/HadISDTable/r1/v3-2-0-2021f",
            "numberOfFiles": 9291,
            "volume": 47620160822,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34664,
                "uuid": "5fb94c8e37f64c95b671278b0e55cdd4",
                "short_code": "ob",
                "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2021, v3.2.0.2021f",
                "abstract": "This is version v3.2.0.2021f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20220101_v3.2.1.2021f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34670,
            "uuid": "a50a78a4c9cb412d98d776f8de39be3d",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-hadobs/data/derived/MOHC/HadOBS/HadEX3/v3-0-4/",
            "numberOfFiles": 63,
            "volume": 4115603887,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34669,
                "uuid": "115d5e4ebf7148ec941423ec86fa9f26",
                "short_code": "ob",
                "title": "HadEX3: Global land-surface climate extremes indices v3.0.4 (1901-2018)",
                "abstract": "HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). \r\n\r\nSpatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010.\r\n\r\nAll indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110').\r\n\r\nVersion 3.0.4 was added due to an error in how the Rx1day and Rx5day data were being handled for one of the West African data sources. More details can be found in the HadEX3 blog under 'Details/Docs' tab.\r\n\r\nAdditionally, an extension to HadEX3, comprising additional indices recommended by the WMO Expert Team on Sector-specific Climate Indices (ET-SCI), has been produced. These data are available in a separate dataset connected to this record, marked as supplemental to this dataset."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34671,
            "uuid": "afc352441ffa42678a80114a70052e19",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/sams",
            "numberOfFiles": 101,
            "volume": 66846932,
            "fileFormat": "Unknown",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34672,
                "uuid": "a8ebefa818e44f5a8bd259f561ad1555",
                "short_code": "ob",
                "title": "Legacy data from Nimbus-7 Stratospheric and Mesospheric Sounder (SAMS)",
                "abstract": "Legacy data from Nimbus-7 Stratospheric and Mesospheric Sounder (SAMS).\r\n\r\nThese data are as found. They are a legacy from the Geophysical Data Facility (GDF). There is some fortran software which may help decode it."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34673,
            "uuid": "0d9d4e24216d4a9abe05cf1a0e814ca2",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/snow/data/scfv/AVHRR_MERGED/v2.0/",
            "numberOfFiles": 13405,
            "volume": 27651048076,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33061,
                "uuid": "763eb87e0682446cafa8c74488dd5fb8",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable (SCFV) from AVHRR (1982 - 2018), version 2.0",
                "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme.  \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFV time series provides daily products for the period 1982-2018. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\n\r\nThe retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre- and post-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.630 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied.  Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water; permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFV product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation. \r\n\r\nThe SCFV AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 37 years."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34675,
            "uuid": "9b540c4fac04495ea97bd74fd308dc35",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISD/subdaily/HadISDTable/r1/v1-0-4-2015f",
            "numberOfFiles": 6117,
            "volume": 20345458505,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34674,
                "uuid": "f0f32cf3e7884950a585b7a4fda9dcb6",
                "short_code": "ob",
                "title": "HadISD: Global sub-daily, surface meteorological station data, 1973-2015, v1.0.4.2015f",
                "abstract": "This is version 1.0.4.2015f of HadISD (27 April 2015) the Met Office Hadley Centre's global sub-daily data, extending v1.0.3.2014f to span 1/1/1973 - 31/12/2015.  \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed in the quality control process are also provided along with a station listing with IDs, names and location information. The data are provided as one NetCDF file per station. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20151231_v1-0-4-2015f.nc (note, the filenames incorrectly show the start date of 19310101, instead of 19730101). The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Climate of the Past\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34676,
            "uuid": "2d5d2fe76ede4861ae37207af51a1035",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig04/v20211028",
            "numberOfFiles": 6,
            "volume": 107476,
            "fileFormat": "netCDF",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33161,
                "uuid": "06a4ad1656774087a5b6db3c7a57211e",
                "short_code": "ob",
                "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.4 (v20211028)",
                "abstract": "Data for Figure 3.4 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 3.4 shows observed and simulated time series of the anomalies in annual and global mean near-surface air temperature (GSAT). \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels, with data provided for all panels in subdirectories named panel_a and panel_b.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n Observed and simulated global near-surface air temperature change (1850-2014) with uncertainty range for simulated time series.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\npanel_a/fig_3_4_panel_a.nc\r\n- black line: model = 60\r\n- red line: model = 59\r\n- colored lines: model = 0, 1, ..., 58\r\npanel_b/tsline_collect_tasa.nc:\r\n- red line: experiment = 0, stat = 0\r\n- blue line: experiment = 1, stat = 0\r\n- red shaded region: experiment = 0, stat = 1 and stat = 2\r\n- blue shaded region: experiment = 1, stat = 1 and stat = 2\r\npanel_b/tsline_collect_tasa_ref.nc\r\n- HadCRUT5: dataset = 0\r\n- BerkleyEarth: dataset = 1\r\n- NOAAGlobalTemp-Interim: dataset = 2\r\n- Kadow: dataset =3\r\n\r\nWhere HadCRUT5, BerkleyEarth, NOAAGlobalTemp-Interim, and Kadow are gridded datasets of global historical surface temperature.\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34687,
            "uuid": "e39e89417d3b40a6a6790e6abf9a91f4",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/igp/data/SNOWPACE_stations/",
            "numberOfFiles": 5,
            "volume": 4309997,
            "fileFormat": "Data are NetCDF and CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34686,
                "uuid": "2db9a5613f634329bc581d3e00045cf5",
                "short_code": "ob",
                "title": "Iceland Greenland Seas Project (IGP): water isotope measurements from the University of Iceland vapour isotope analyzer at Húsavik and samples of precipitation and surface snow in Iceland and southern Norway within SNOWPACE",
                "abstract": "This dataset contains measurements of the water vapour isotope composition of ambient vapour obtained from a water vapour isotope analyzer manufactured by Los Gatos Research (LGR), and from discrete sampling of surface snow and precipitation and subsequent laboratory analysis. The analyzer was installed in the harbour of Húsavik, Iceland. Discrete sampling included precipitation and surface snow from two surface transects in northern Iceland and in several locations in southern Norway. The LGR LWIA analyzer is an off-axis cavity ring-down spectrometer using infrared absorption bands for the retrieval of the water isotope ratios for H216O, H218O, and HDO, quantified as mixing ratio of water vapour (w, ppmv), delta 18-O, and delta-D (permil). The data set for the Húsavik station is accompanied by automatic weather station data (air temperature, relative humidity, wind speed, wind direction, sea-level pressure) from the Icelandic weather service (vedur.is) for several nearby locations. For further details and figures for the vapour measurements, and the surface sample collection during the campaign, and processing thereafter, please read the attached documentation.\r\n\r\nThis research is funded by the Research Council of Norway under the Sources of the Norwegian winter season snow pack constrained by stable water isotopes - SNOWPACE project (Project Nr. 262710) and the Facility for advanced isotopic research and monitoring of weather, climate and biogeochemical cycling (FARLAB) project (Project Nr. 245907)."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34693,
            "uuid": "5c36432980f8461b90544ff0f7b34ec3",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/igp/data/SNOWPACE_Alliance/",
            "numberOfFiles": 5,
            "volume": 5312790,
            "fileFormat": "Data are NetCDF and CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34692,
                "uuid": "705abc2d9988444ba79e942f22219bc0",
                "short_code": "ob",
                "title": "Iceland Greenland Seas Project (IGP): water isotope measurements from the University of Bergen vapour isotope analyzer on board the NATO Research Vessel Alliance within SNOWPACE",
                "abstract": "This dataset contains measurements of the water vapour isotope composition of ambient vapour, surface snow, ocean water, and precipitation obtained from water vapour isotope analyzers manufactured by Picarro Inc., as well as from discrete sampling and subsequent laboratory analysis. The analyzer was installed onboard the NATO Research Vessel Alliance during the Iceland Greenland Seas Project. Discrete sampling included precipitation, sea water, and standards from the R/V Alliance. The Picarro L2140-i analyzer is a cavity ring-down spectrometer that uses infrared absorption bands for the retrieval of the water isotope ratios for H216O, H218O, and HDO, quantified as mixing ratio of water vapour (w, ppmv), delta 18-O, and delta-D (permil) at 1 Hz time native resolution. The data set for the R/V Alliance has been joined  with the meteorological data from R/V Alliance (https://catalogue.ceda.ac.uk/uuid/b4ba8f11459c422d84d7293b9211ccf7) at 60 s averaging. For further details and figures on the Picarro analyzer, and the sample collection during the campaign, and processing thereafter, please read the attached documentation. \r\n\r\nThis research is funded by the Research Council of Norway under the Sources of the Norwegian winter season snow pack constrained by stable water isotopes - SNOWPACE project (Project Nr. 262710) and the Facility for advanced isotopic research and monitoring of weather, climate and biogeochemical cycling (FARLAB) project (Project Nr. 245907)."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34699,
            "uuid": "4f8f656c0d3f40ddba2304f61a81f6d5",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/igp/data/SNOWPACE_MASIN/",
            "numberOfFiles": 48,
            "volume": 58105846,
            "fileFormat": "Data are NetCDF and CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34698,
                "uuid": "7c8ce1c47da548a08146fa62158303c5",
                "short_code": "ob",
                "title": "Iceland Greenland Seas Project (IGP): water isotope measurements from the University of Bergen vapour isotope analyzer on board the BAS research aircraft MASIN within SNOWPACE",
                "abstract": "This dataset contains measurements of the water vapour isotope composition of ambient vapour obtained from a water vapour isotope analyzers manufactured by Picarro Inc, as well as discrete samples of water standards used for calibration. The analyzer was installed onboard the research aircraft MASIN of the British Antarctic Survey. Discrete sampling included standards from the on-board calibration system on the MASIN aircraft. The Picarro L2130-i analyzer is a cavity ring-down spectrometer that uses infrared absorption bands for the retrieval of the water isotope ratios for H216O, H218O, and HDO, quantified as mixing ratio of water vapour (w, ppmv), delta 18-O, and delta-D (permil) at 1 Hz time resolution. The water isotope data set for the MASIN aircraft is joined with the airborne meteorological observations data set from the MASIN aircraft at different averaging times. For further details and figures on the Picarro analyzers, and processing thereafter, please read the attached documentation. \r\n\r\nThis research is funded by the Research Council of Norway under the Sources of the Norwegian winter season snow pack constrained by stable water isotopes - SNOWPACE project (Project Nr. 262710) and the Facility for advanced isotopic research and monitoring of weather, climate and biogeochemical cycling (FARLAB) project (Project Nr. 245907)."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34704,
            "uuid": "043c35f70b784f1b9a129caa4fafcd0b",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/AQUA_MODIS/L3C/0.01/v3.00/daily/",
            "numberOfFiles": 12009,
            "volume": 8680638173212,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33363,
                "uuid": "6babb8d9a8d247bcb3da6aed42f4b59a",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from  MODIS (Moderate resolution Infra-red Spectroradiometer) on Aqua, level 3 collated (L3C) global product (2002-2018), version 3.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System – Aqua (Aqua). Satellite land surface temperatures are skin temperatures which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the daytime and night-time Aqua equator crossing times which are 13:30 and 01:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. MODIS achieves full Earth coverage nearly twice per day so the daily files have small gaps primarily close to the equator where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 4th July 2002 and ends on 31st December 2018. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using a generalised split window retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34708,
            "uuid": "46986939dc7f46f1b4addb9c814b6dff",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/TERRA_MODIS/L3C/0.01/v3.00/daily/",
            "numberOfFiles": 13651,
            "volume": 9991764026044,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33368,
                "uuid": "58a01734f841466daa1837353aee5ff8",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land Surface Temperature from  MODIS (Moderate resolution Infra-red Spectroradiometer) on Terra, level 3 collated (L3C) global product (2000-2018), version 3.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System – Terra (Terra). Satellite land surface temperatures are skin temperatures which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Terra equator crossing times which are 10:30 and 22:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. MODIS achieves full Earth coverage nearly twice per day so the daily files have small gaps primarily close to the equator where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 24th February 2000 and ends on 31st December 2018. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using a generalised split window retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34712,
            "uuid": "934bb1a24e574e759c4b08a1dfe50736",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/ERS-2_ATSR/L3C/0.01/v3.00/daily/",
            "numberOfFiles": 4915,
            "volume": 1183992251953,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33365,
                "uuid": "f1445bde2f1249c99bb5a59b71e9a9d7",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from ATSR-2 (Along-Track Scanning Radiometer 2),  level 3 collated (L3C) global product (1995-2013), version 3.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Along-Track Scanning Radiometer (ATSR-2) on European Remote-sensing Satellite 2 (ERS-2). Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and nighttime temperatures are provided in separate files corresponding to the morning and evening ERS-2 equator crossing times which are 10:30 and 22:30 local solar time. \r\n\r\nPer pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length.\r\n\r\nAlso provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag,  and land cover class.\r\n\r\nThe dataset coverage is near global over the land surface. Small regions were not covered due to downlinking constraints (most noticeably a track extending southwards across central Asia through India – further details can be found on the ATSR project webpages at http://www.atsr.rl.ac.uk/dataproducts/availability/coverage/atsr-2/index.shtml.\r\n\r\nLSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. ATSR-2 achieves full Earth coverage in 3 days so the daily files have gaps where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 1st August 1995 and ends on 22nd June 2003. There are two gaps of several months in the dataset: no data were acquired from ATSR-2 between 23 December 1995 and 30 June 1996 due to a scan mirror anomaly; and the ERS-2 gyro failed in January 2001, data quality was less good between 17th Jan 2001 and 5th July 2001 and are not used in this dataset. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34714,
            "uuid": "1206256e033a485e816c7d63044abec0",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/TRANSITION_Exposure_to_VOCs/",
            "numberOfFiles": 31,
            "volume": 40489771,
            "fileFormat": "Data are BADC-CSV formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34713,
                "uuid": "96c912c7c0094da2a8627d446cb06708",
                "short_code": "ob",
                "title": "TRANSITION Clean Air Network: Exposures to particles and volatile organic compounds across multiple transportation modes",
                "abstract": "This dataset contains volatile organic compounds (VOC) and ultrafine particle measurements collected onboard several vehicles for the TRANSITION Clean air Network during May 2021 in the London and surrounding area. \r\n\r\nThe particles measured include VOCs captured in the field using thermal desorption tubes, and then analysed into the component species using highly sensitive Markes International GCxGC-TOF-MS system, and ultrafines data captured using a V2000 sensor from National Air Quality Testing Services by Emissions Analytics.   Therefore, a much wider range of pollutants have been tested than in standard air quality monitoring. \r\n\r\nThe harm caused by emissions from vehicles to air quality and the health of humans outside is increasing well understood and It is generally accepted that it is a policy priority to remove high-emitting vehicles from the road and to swap for low-emission vehicles or public transport. What is less well understood is the exposure of the occupants in various transportation modes. Aggregate time spent in vehicles is significant, and can be measured in hours per day for certain commuters and professional drivers.  Existing research by Emissions Analytics shows that the worst-performing cars can have particle number concentrations more than three times than in the ambient air. With Net Zero, particles are likely to be the dominant traffic pollutant.\r\n\r\nThis dataset contains interior air quality measurements made on a range of modes of transport including diesel and electric trains, the London Underground, diesel and electric buses, and old and new cars, including a battery electric."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34721,
            "uuid": "f2c1f645d93a472dbaa2dfff53f1dee3",
            "short_code": "result",
            "curationCategory": "C",
            "dataPath": "/badc/msg/data/hritimages/LEDF41_45E",
            "numberOfFiles": 31619,
            "volume": 72967322249,
            "fileFormat": "Images are PNG formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34720,
                "uuid": "906f6d3957f9439c98dfb662cda8a769",
                "short_code": "ob",
                "title": "MSG: Dust imagery in the RGB channels over the full disc at 45.5 degrees East (LEDF41, from 1st June 2022)",
                "abstract": "The Meteosat Second Generation (MSG) satellites, operated by EUMETSAT (The European Organisation for the Exploitation of Meteorological Satellites), provide almost continuous imagery to meteorologists and researchers in Europe and around the world. These include visible, infra-red, water vapour, High Resolution Visible (HRV) images and derived cloud top height, cloud top temperature, fog, snow detection and volcanic ash products. These images are available for a range of geographical areas. \r\n\r\nThis dataset contains RGB dust images from MSG satellites over the full disc at 45.5 degrees East. Imagery available from 1000 UTC 1st June 2022 onwards at a frequency of 15 minutes (some are hourly) and are at least 24 hours old.\r\n\r\nNOTE - this dataset differs from the previous LEDF41 product produced using imagery from Meteosat-8 located at 41.5E. These new data are from Meteosat-9 which was drifted from previous operations over 3.5 E to 45.5 E between 1st February 2022 to 20th April 2022 to take over as the prime IODC (Indian Ocean Data Coverage) satellite by 1st June 2022.  See linked EUMETNET web page regarding this change in operation. The Met Office switched to providing this LEDF41 product from this new satellite at 0915 UTC on 1st June 2022, this dataset. See linked datasets for previous data. These are treated as two distinct datasets due to the shift in locational coverage.\r\n\r\nThe geographic extent for images within this datasets is available via the linked documentation 'MSG satellite imagery product geographic area details'. Each MSG imagery product area can be referenced from the third and fourth character of the image product name giving in the filename. E.g. for EEAO11 the corresponding geographic details can be found under the entry for area code 'AO' (i.e West Africa)."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34722,
            "uuid": "86e38725ead544f6bff16f8bf3cc2e18",
            "short_code": "result",
            "curationCategory": "B",
            "dataPath": "/neodc/tls/data/global/tls_tree_biomass/",
            "numberOfFiles": 2,
            "volume": 52290,
            "fileFormat": "Excel spreadsheet",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34724,
                "uuid": "ddcad11fd71245d3b9d0e669b3fd9169",
                "short_code": "ob",
                "title": "Global dataset of co-incident TLS-derived and harvested tree biomass",
                "abstract": "This dataset contains aboveground biomass estimates generated using terrestrial laser scanning (TLS) techniques for different species of tree. It was used to produce the figures and statistics of the publication \"Estimating forest aboveground biomass with terrestrial laser scanning: current status and future directions\".\r\n\r\nThis dataset contains 391 entries. Each entry is a tree that was terrestrial laser scanned and consecutively harvested to assess its aboveground biomass (AGB). AGB was also obtained from allometric scaling equations. Several ancillary tree properties such as stem diameter, foliage conditions,... and scan metadata (type of scanner, pattern) are included. We refer to the tab 'headers' for an explanation and units of the respective columns. Elaborate method descriptions can be found in the publication or in the following publications, which can be found in the documentation sections"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34725,
            "uuid": "70cf79f4625e4650809f8f587a4498b9",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/ENVISAT_ATSR/L3C/0.01/v3.00/daily/",
            "numberOfFiles": 6911,
            "volume": 1692010964766,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33364,
                "uuid": "1115d8946ba74c7f8a9fc3bfee5513a0",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from AATSR (Advanced Along-Track Scanning Radiometer), level 3 collated (L3C) global product (2002-2012), version 3.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Advanced Along-Track Scanning Radiometer (AATSR) on Environmental Satellite (Envisat). Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Envisat equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. AATSR achieves full Earth coverage in 3 days so the daily files have gaps where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 25th July 2002 and ends on 8th April 2012. There is a twelve day gap in the dataset due to Envisat mission extension orbital manoeuvres from 21st October 2010 to 1st November 2010. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34731,
            "uuid": "9d482dea6d214a21b46bdfa0ae4e953a",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/SENTINEL3A_SLSTR/L3C/0.01/v3.00/daily/",
            "numberOfFiles": 3291,
            "volume": 1354795145452,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33366,
                "uuid": "330b7c922a37420fabb3425671d7d7c6",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3A, level 3 collated (L3C) global product (2016-2020), version 3.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3A. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel-3A equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRA achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 1st May 2016 and ends on 31st December 2020. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34735,
            "uuid": "0874c71d1b214c5fa6ddd31f1c96649b",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/SENTINEL3B_SLSTR/L3C/0.01/v3.00/daily/",
            "numberOfFiles": 1473,
            "volume": 595761744858,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33367,
                "uuid": "5f66a881adf846bfaad58b0e6068f0ea",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land Surface Temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3B, level 3 collated (L3C) global product (2018-2020), version 3.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3B. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel 3B equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRB achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 17th November 2018 and ends on 31st December 2020. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34739,
            "uuid": "c7540133d0f24a04bd516ee6c6cea303",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/MULTISENSOR_IRCDR/L3S/0.01/v2.00/daily/",
            "numberOfFiles": 17403,
            "volume": 4309554055171,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33370,
                "uuid": "ef8ce37b6af24469a2a4bdc31d3db27d",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Multisensor Infra-Red (IR) Low Earth Orbit (LEO) land surface temperature (LST) time series level 3 supercollated (L3S) global product (1995-2020), version 2.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from multiple Infra-Red (IR) instruments on Low Earth Orbiting (LEO) sun-synchronous (a.k.a. polar orbiting) satellites. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to 10:30 and 22:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset is comprised of LSTs from a series of instruments with a common heritage: the Along-Track Scanning Radiometer 2 (ATSR-2), the Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature Radiometer on Sentinel 3A (SLSTRA); and data from the Moderate Imaging Spectroradiometer on Earth Observation System - Terra (MODIS Terra) to fill the gap between AATSR and SLSTR. So, the instruments contributing to the time series are: ATSR-2 from August 1995 to July 2002; AATSR from August 2002 to March 2012; MODIS Terra from April 2012 to July 2016; and SLSTRA from August 2016 to December 2020. Inter-instrument biases are accounted for by cross-calibration with the Infrared Atmospheric Sounding Interferometer (IASI) instruments on Meteorological Operational (METOP) satellites. For consistency, a common algorithm is used for LST retrieval for all instruments. Furthermore, an adjustment is made to the LSTs to account for the half-hour difference between satellite equator crossing times. For consistency through the time series, coverage is restricted to the narrowest instrument swath width.\r\n\r\nThe dataset coverage is near global over the land surface. During the period covered by ATSR-2, small regions were not covered due to downlinking constraints (most noticeably a track extending southwards across central Asia through India – further details can be found on the ATSR project webpages at http://www.atsr.rl.ac.uk/dataproducts/availability/coverage/atsr-2/index.shtml).\r\n\r\nLSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. Full Earth coverage is achieved in 3 days so the daily files have gaps where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 1st August 1995 and ends on 31st December 2020. There are two gaps of several months in the dataset: no data were acquired from ATSR-2 between 23 December 1995 and 30 June 1996 due to a scan mirror anomaly; and the ERS-2 gyro failed in January 2001, data quality was less good between 17th Jan 2001 and 5th July 2001 and are not used in this dataset. Also, there is a twelve day gap in the dataset due to Envisat mission extension orbital manoeuvres from 21st October 2010 to 1st November 2010. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies. \r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
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                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Multisensor Infra-Red (IR) Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) land surface temperature (LST) level 3 supercollated (L3S) global product (2009-2020), version 1.00",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from multiple Infra-Red (IR) instruments on satellites in Geostationary Earth Orbit (GEO) and Low Earth Orbiting (LEO) sun-synchronous (a.k.a. polar orbiting) satellites. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nLST fields are provided at 3 hourly intervals each day (00:00 UTC, 03:00 UTC, 06:00 UTC, 09:00 UTC, 12:00 UTC, 15:00 UTC, 18:00 UTC and 21:00 UTC). Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and the solar geometry angles.\r\n\r\nThe product is based on merging of available GEO data and infilling with available LEO data outside of the GEO discs. Inter-instrument biases are accounted for by cross-calibration with the IASI instruments on METOP and LSTs are retrieved using a Generalised Split Window algorithm from all instruments. As data towards the edge of the GEO disc is known to have greater uncertainty, any datum with a satellite zenith angle of more than 60 degrees is discarded. All LSTs included have an observation time that lies within +/- 30 minutes of the file nominal Universal Time.\r\n\r\nData from the following instruments is included in the dataset: geostationary, Imagers on Geostationary Operational Environmental Satellite (GOES) 12 and GOES 13, Advanced Baseline Imager (ABI) on GOES 16, Spinning Enhanced Visible Infra-Red Imager (SEVIRI) on Meteosat Second Generation (MSG) 1, MSG 2, MSG 3, and MSG 4, Japanese Advanced Meteorological Imager (JAMI) on Multifunctional Transport Satellite MTSAT) 1, and MTSAT 2; and polar, Advanced Along-Track Scanning Radiometer (AATSR) on Environmental Satellite (Envisat), Moderate-resolution Imaging Spectroradiometer (MODIS) on Earth Observation System (EOS) - Aqua and EOS - Terra, Sea and Land Surface Temperature Radiometer SLSTR on Sentinel-3A and Sentinel-3B. However, it should be noted that which instruments contribute to a particular product file depends on depends on mission start and end dates and instrument downtimes.\r\n\r\nDataset coverage starts on 1st January 2009 and ends on 31st December 2020. \r\n\r\nLSTs are provided on a global equal angle grid at a resolution of 0.05° longitude and 0.05° latitude. The dataset coverage is nominally global over the land surface but varies depending on satellite and instrument availability and coverage. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and data were processed in the UoL processing chain. The Geostationary data were produced by the Instituto Português do Mar e da Atmosfera (IPMA) before being merged into the final dataset.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards."
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                "abstract": "In-situ airborne observations collected during flight 319 on 23 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Falkland Islands area."
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                "abstract": "In-situ airborne observations collected during flight 276 on 02 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "abstract": "In-situ airborne observations collected during flight 277 on 03 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "abstract": "In-situ airborne observations collected during flight 278 on 06 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "abstract": "In-situ airborne observations collected during flight 279 on 06 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "abstract": "In-situ airborne observations collected during flight 289 on 16 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "abstract": "In-situ airborne observations collected during flight 280 on 07 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "abstract": "In-situ airborne observations collected during flight 281 on 08 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "abstract": "In-situ airborne observations collected during flight 287 on 15 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Antarctic Peninsula."
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                "short_code": "ob",
                "title": "BAS-MASIN flight 288: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 288 on 15 December 2017 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\nData were collected over the Antarctic Peninsula."
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        {
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                "ob_id": 34838,
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                "title": "BAS-MASIN flight 312: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 312 on 07 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the  Falkland Islands area."
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                "short_code": "ob",
                "title": "BAS-MASIN flight 313: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 313 on 08 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Falkland Islands area."
            },
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                "uuid": "a5328df497c84df1a392039f56dd211b",
                "short_code": "ob",
                "title": "BAS-MASIN flight 314: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 314 on 13 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Falkland Islands area."
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        {
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                "ob_id": 34850,
                "uuid": "94aa1faf95c8407fa5efb34ac650a8d8",
                "short_code": "ob",
                "title": "BAS-MASIN flight 315: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 315 on 15 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Falkland Islands area."
            },
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        {
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                "ob_id": 34854,
                "uuid": "b01b46a2e18c44d1b563a6fc36bb26b5",
                "short_code": "ob",
                "title": "BAS-MASIN flight 316: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 316 on 17 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Falkland Islands area."
            },
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            "observation": {
                "ob_id": 34858,
                "uuid": "837f68e650d24a109a7ec85715a909d4",
                "short_code": "ob",
                "title": "BAS-MASIN flight 317: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 317 on 18 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Falkland Islands area."
            },
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        {
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/orchestra/data/twinotter/flight320_20190223",
            "numberOfFiles": 4,
            "volume": 128095710,
            "fileFormat": "MASIN data are in NetCDF format",
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            "observation": {
                "ob_id": 34862,
                "uuid": "1ed327b7ab7e47048b116ff5f42d1e5a",
                "short_code": "ob",
                "title": "BAS-MASIN flight 320: airborne meteorological observations from the ORCHESTRA project",
                "abstract": "In-situ airborne observations collected during flight 320 on 23 February 2019 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports project. This dataset contains the core meteorological data from the MASIN instrument suite. \r\n\r\nData were collected over the Falkland Islands area."
            },
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        {
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            "numberOfFiles": 18913,
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                "ob_id": 33362,
                "uuid": "058d3ad17a084f0bb8dc9b5dc5efdb7f",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): All-weather MicroWave Land Surface Temperature (MW-LST) global data record (1996-2020)",
                "abstract": "MW-LST is a data record of land surface temperature (LST) derived from the microwave instruments Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager / Sounder (SSMIS). Observations available at frequencies close to 18, 22, 26, and 85 GHz are used as an input to a retrieval algorithm that produces LST over all continental surfaces, twice per day (6 am/pm), at a spatial resolution of ~25 km, and over 25 years (1996-2020). \r\n\r\nThe data record has been produced by the company Estellus working within the ESA Land Surface Temperature Climate Change Initiative (LST_cci).   Compared with the remaining infrared LST data records of the LST_cci, the spatial resolution of the MW-LST is coarser, and the associated retrieval errors are larger. However, it offers LST estimates for clear-sky and cloudy conditions, therefore complementing the IR LST data records, which can only provide LST for clear skies. The data record is temporally and spatially complete, although in rare occasions some data can be missing due to missing observations, e.g., due to satellite maintenance operations or anomalous behavior. The data record is provided on a regular grid of 0.25x0.25 degrees, saved as daily, monthly, and yearly netcdf files. The reader is referred to the LST_cci website for more information about how the data record was derived, and how to use the data and associated quality flags and estimated uncertainty."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34867,
            "uuid": "aa701155b2f3493195eac8218f189c24",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/tls/data/raw/australia/AEP-02/",
            "numberOfFiles": 1554,
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            "fileFormat": "Scan folders contain a number of file formats CSV, ASCII, text, PNG , RXP and PAT",
            "storageStatus": "online",
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            "oldDataPath": [],
            "observation": null,
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        {
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            "curationCategory": "",
            "dataPath": "/neodc/esacci/water_vapour/data/TCWV-land/L3/v3.2/0.05deg/daily/",
            "numberOfFiles": 5664,
            "volume": 403492397164,
            "fileFormat": "Data are in NetCDF format",
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            "observation": {
                "ob_id": 34606,
                "uuid": "fc3310aaa2fe4a26a29a63642e1164f2",
                "short_code": "ob",
                "title": "ESA Water Vapour Climate Change Initiative (Water_Vapour_cci): Total Column Water Vapour daily gridded data over land at 0.05 degree resolution, version 3.2",
                "abstract": "This dataset consists of daily total column water vapour (TCWV) over land, at a 0.05 degree resolution, observed by various satellite instruments.   It has been produced by the European Space Agency Water Vapour Climate Change Initiative (Water_Vapour_cci), and forms part of their TCVW over land Climate Data Record -1  (TCWV-land (CDR-1).\r\n\r\nThis version of the data is v3.2.  This is an updated dataset, which fixes an issue with the filtering of the v3.1 data."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34870,
            "uuid": "15a05208e39445b6a05887088119edc1",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/water_vapour/data/TCWV-land/L3/v3.2/0.5deg/daily/",
            "numberOfFiles": 5664,
            "volume": 8466232731,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 34605,
                "uuid": "5bd687c7ea624e3aa68c51e242ae828a",
                "short_code": "ob",
                "title": "ESA Water Vapour Climate Change Initiative (Water_Vapour_cci): Total Column Water Vapour daily gridded data over land at 0.5 degree resolution, version 3.2",
                "abstract": "This dataset consists of daily total column water vapour (TCWV) over land, at a 0.5 degree resolution, observed by various satellite instruments.   It has been produced by the European Space Agency Water Vapour Climate Change Initiative (Water_Vapour_cci), and forms part of their TCVW over land Climate Data Record -1  (TCWV-land (CDR-1).\r\n\r\nThis version of the data is v3.2. This is an updated dataset, which fixes an issue with the filtering of the v3.1 data."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 34873,
            "uuid": "4b2f399da7c94fac8e3f31cbb16e7271",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/Lagrangian_H2Ostrat_projection/",
            "numberOfFiles": 0,
            "volume": 0,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": null,
            "onlineresource_set": []
        },
        {
            "ob_id": 34876,
            "uuid": "0b3fce413cf749dabf1194565d08f084",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/Lagrangian_H2Ostrat_projection/",
            "numberOfFiles": 0,
            "volume": 0,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
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            "oldDataPath": [],
            "observation": null,
            "onlineresource_set": []
        },
        {
            "ob_id": 34898,
            "uuid": "513879533f9c4af78a47498847b5e354",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2022/Lagrangian_H2Ostrat_projection/",
            "numberOfFiles": 21,
            "volume": 507485970,
            "fileFormat": "Data are NetCDF formatted.",
            "storageStatus": "online",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 34897,
                "uuid": "e4eac61c06e348389f16bb863334dbf6",
                "short_code": "ob",
                "title": "Water budget and Lagrangian analysis of tropical tropopause in simulations with Hadley Centre Global Environmental Model version 3 (HadGEM3)",
                "abstract": "This dataset contains water budget and Lagrangian analysis of the tropical tropopause from climate model simulations and Lagrangian trajectory calculations.  This study was conducted to understand better the role of convection as water vapour enters the tropical stratosphere (above about 17.4km), in particular in future scenarios.\r\n\r\nThe atmosphere component of HadGEM3, Global Atmosphere (GA) 7.0, was run for three different scenarios. Based on the SPARC Quasi-Biennial Oscillation initiative (QBOi) experiments 2,3,4, these force the atmosphere model with year 2002 conditions (e.g. of solar radiation and sea surface temperatures) every year for 21 years, so that each year experiences identical boundary conditions. The first scenario has no modifications (as a control), the second has doubled CO2 concentrations and sea surface temperatures (SSTs) are increased by 2K, andthe third has quadrupled CO2 concentrations and SSTs are increased by 4K. Simulations were allowed 10 years to stabilise to their modified forcing conditions and the final 11 years were analysed further. These simulations were chosen because they give a simplified indication of how the atmosphere might change in the 21st century.\r\n\r\nA second component to this dataset is estimates of water vapour entering the stratosphere with the available output. For this, climate model output was used for Lagrangian calculations which were conducted with the OFFLINE trajectory model.\r\n\r\nRecords includes:\r\n-increments of all model processes that affect water vapour and ice (to get a full water budget) at grid points around the tropical tropopause (altitude of 17.4km and 18.0km, 40degS - 40degN and 180W - 180E) as monthly means of 6 hourly instantaneous values across the first two years after stabilisation. \r\n- locations and timing of model grid points above the minimum saturation mixing ratio in the vertical profile (the dry point) that exhibit convective ice injection (fast transport of ice by strong cloud processes)\r\n- monthly mean values of estimates of water vapour concentration above the tropical tropopause. These values include the HadGEM3 calculation, and proxies based on the dry point or on Lagrangian (trajectory-following) calculations of water vapour passing through the tropical tropopause.\r\n\r\nThese records are analysed in:\r\nSmith, J. W., Bushell, A. C., Butchart.,N. , Haynes, P. H., Maycock, A. C., The effect of convective injection of ice on stratospheric water vapor in a changing climate, Geophysical Research Letters, submitted 12/21.\r\n\r\nLinks for further information:\r\n\r\nHadGEM3:\r\nhttps://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/hadgem3\r\n\r\nQBOi experiment:\r\nButchart, N., Anstey, J. A., Hamilton, K., Osprey, S., McLandress, C., Bushell, A. C., … Yukimoto, S. (2018). Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi). Geoscientific Model Development, 11(3), 1009–1032. https://doi.org/10.5194/gmd-11-1009-2018\r\n\r\nOFFLINE trajectory model:\r\nhttp://www.met.reading.ac.uk/~swrmethn/offline/"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35033,
            "uuid": "0dc78875f9bd44aebc1152d351ff2c83",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/snow/data/swe/MERGED/v2.0/",
            "numberOfFiles": 7936,
            "volume": 11151780565,
            "fileFormat": "This data product follows CCI Data Standards v2.3, 2021 and are distributed as NetCDF files conforming to Climate and Forecast (CF) convention version 1.9.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 31200,
                "uuid": "4647cc9ad3c044439d6c643208d3c494",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Snow Water Equivalent (SWE) level 3C daily global climate research data package (CRDP)  (1979 – 2020), version 2.0",
                "abstract": "This dataset contains v2.0 of the Daily Snow Water Equivalent (SWE) product from the ESA Climate Change Initiative (CCI) Snow project, at 0.1 degree resolution.\r\n\r\nSnow water equivalent (SWE) indicates the amount of accumulated snow on land surfaces, in other words the amount of water contained within the snowpack. The SWE product time series covers the period from 1979/01 to 2020/05. Northern Hemisphere SWE products are available at daily temporal resolution with alpine areas masked. \r\n\r\nThe product is based on data from the Scanning Multichannel Microwave Radiometer (SMMR) operated on National Aeronautics and Space Administration’s (NASA) Nimbus-7 satellite, the  Special Sensor Microwave / Imager (SSM/I) and the Special Sensor Microwave Imager / Sounder (SSMI/S) carried onboard the Defense Meteorological Satellite Program (DMSP) 5D- and F-series satellites. The satellite bands provide spatial resolutions between 15 and 69 km.  The retrieval methodology combines satellite passive microwave radiometer (PMR) measurements with ground-based synoptic weather station observations by Bayesian non-linear iterative assimilation. A background snow-depth field from re-gridded surface snow-depth observations and a passive microwave emission model are required components of the retrieval scheme.\r\n\r\nThe dataset is aimed to serve the needs of users working on climate research and monitoring activities, including the detection of variability and trends, climate modelling, and aspects of hydrology and meteorology.\r\n\r\nThe Finnish Meteorological Institute is responsible for the SWE product development and generation. \r\n\r\nFor the period from 1979 to May 1987, the products are available every second day. From October 1987 till May 2020, the products are available daily. Products are only generated for the Northern Hemisphere winter seasons, usually from beginning of October till the middle of May. A limited number of SWE products are available for days in June and September; products are not available for the months July and August as there is usually no snow information reported on synoptic weather stations, which is required as input for the SWE retrieval. Because of known limitations in alpine terrain, a complex-terrain mask is applied based on the sub-grid variability in elevation determined from a high-resolution digital elevation model. All land ice and large lakes are also masked; retrievals are not produced for coastal regions of Greenland.\r\n\r\nThis version 2 dataset has some notable differences compared to the v1 data. In v2, passive microwave radiometer data are obtained from the recalibrated enhanced resolution CETB ESDR dataset  (MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR)  https://nsidc.org/pmesdr/data-sets/) the grid spacing is reduced from 25 km to 12.5 km, and spatially and temporally varying snow density fields are used to adjust SWE retrievals in post processing. The output grid spacing is reduced from 0.25-degree to 0.10-degree WGS84 latitude / longitude to be compatible with other Snow_cci products. The time series has been extended by two years with data from 2018 to 2020 added.\r\n\r\nThe ESA CCI phased product development framework allowed for a systematic analysis of these changes to the input data and snow density parameterization that occurred between v1 and v2 using a series of step-wise developmental datasets. In comparison with in-situ snow courses, the correlation and RMSE of v2 improved 18% (0.1) and 12% (5mm), respectively, relative to v1. The timing of peak snow mass is shifted two weeks later and a temporal discontinuity in the monthly northern hemisphere snow mass time series associated with the shift from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) in 2009 is removed in v2."
            },
            "onlineresource_set": []
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        {
            "ob_id": 35037,
            "uuid": "40bb1b3748574018808c8b751d8cdbec",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/snow/data/scfg/AVHRR_MERGED/v2.0/",
            "numberOfFiles": 13405,
            "volume": 26517990507,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 33062,
                "uuid": "3f034f4a08854eb59d58e1fa92d207b6",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from AVHRR (1982 - 2018), version 2.0",
                "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFG time series provides daily products for the period 1982-2018. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\n\r\nThe retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map; ii) Forest canopy transmissivity map; this layer is based on the tree cover classes of the ESA CCI Land Cover 2000 data set and the tree cover density map from Landsat data for the year 2000 (Hansen et al., Science, 2013, DOI: 10.1126/science.1244693). This layer is used to apply a forest canopy correction and estimate in forested areas the fractional snow cover on ground.\r\n\r\nThe SCFG product is aimed to serve the needs of users working in cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFG product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation.\r\n\r\nThe SCFG AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 37 years."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35038,
            "uuid": "4cceb72282734b6e9071128c3d85c690",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/snow/data/scfv/MODIS/v2.0/",
            "numberOfFiles": 7559,
            "volume": 206015589926,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 33059,
                "uuid": "ebe625b6f77945a68bda0ab7c78dd76b",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2020), version 2.0",
                "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from the MODIS satellite instruments, produced by the Snow project of the ESA Climate Change Initiative programme.  \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. \r\n\r\nThe SCFV time series provides daily products for the period 2000 – 2020. \r\n\r\nThe SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the Snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 µm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the Snow_cci SCFV retrieval method is applied. \r\n\r\nThe main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the adaptation of the retrieval method using of a spatially variable ground reflectance instead of global constant values for snow free land, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data to assure in forested areas consistency of the SCFV and the SCFG CRDP v2.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/ebe625b6f77945a68bda0ab7c78dd76b) using the same retrieval approach.\r\n\r\nImprovements of the Snow_cci SCFV version 2.0 compared to the Snow_cci version 1.0 include (i) the utilisation of an updated ground reflectance map derived from statistical analyses of an extended MODIS time series, (ii) an update of the forest mask used for the transmissivity estimation, and (iii) an update of the constant reflectance value for wet snow based on the analysis of time series of the MODIS reflectance at 0.55 µm.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFV product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nENVEO is responsible for the SCFV product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFV products are available but have data gaps."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35040,
            "uuid": "42278ffcd52a4560b9e59c0b9955ceef",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/bodc/USO220011/CHIMNEY_OBS_active",
            "numberOfFiles": 924,
            "volume": 868369944141,
            "fileFormat": "Data are SEGY formatted data files",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35039,
                "uuid": "5b0d2588954e404ab03e8f439d48a8d3",
                "short_code": "ob",
                "title": "Multi-frequency, three-dimensional, four-component ocean bottom seismometer dataset acquired from an active fluid flow structure: Scanner Pockmark, North Sea.",
                "abstract": "A three-dimensional wide-angle active source seismic dataset was acquired during RRS James Cook cruise JC152 (August - September 2017), around the Scanner Pockmark Complex in the North Sea. Data were recorded on 25 four-component ocean bottom seismometers, recording at a sampling rate of 4 kHz. Four different seismic sources were used: \r\n\r\n1) a 700 ci (100, 200 and 400 ci) Bolt airgun array towed at 10-12 m below sea surface and fired at 10 s intervals; \r\n2) a 420 ci (2 x 105/105 ci) GI airgun array, towed at 2 m depth below sea surface and fired at 8 s intervals; \r\n3) a Squid sparker (1750 or 2000 J), towed at the sea surface and triggered at 2 s intervals; and, \r\n4) a Duraspark sparker (2000 J), towed at the sea surface and triggered at 2 s intervals. \r\n\r\nThis dataset complements Bayrakci et al. (2021; https://doi.org/10.1594/PANGAEA.932200) and updates instrument and shot corrections to fit a single, unique set of instrument positions, generated using a grid search algorithm. \r\n\r\nData are provided in standard SEG-Y format. The shot line geometry corrections were performed following the method described in the accompanying document CHIMNEY_OBS_corrections_summary.pdf. All location information is also present in the positioning directory. The data were acquired as part of the 'Characterization of major overburden leakage pathways above sub-seafloor CO2 storage reservoirs in the North Sea' (CHIMNEY) project, funded by the Natural Environment Research Council (NERC) under grant reference NE/N016130/1."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35143,
            "uuid": "4f859a56844f40ae8021026577383e71",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/austria/altmunster/zamg-vaisala-cl51_A",
            "numberOfFiles": 819,
            "volume": 2783063973,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35144,
                "uuid": "91fe5a23aefa4ad59dc7288b0e3a46cd",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from ZAMG's Vaisala CL51 instrument deployed at Altmunster, Austria",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Zentralanstalt für Meteorologie und Geodynamik (ZAMG)'s Vaisala CL51 deployed at Altmunster, Austria.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-11254.\n Details for this WIGOS station are presently unavailable in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities.\n"
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35146,
            "uuid": "258787e484d04a49a2a613f28c8f05d9",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/belgium/arlon/rmi-vaisala-cl51_A",
            "numberOfFiles": 1230,
            "volume": 3212752949,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35147,
                "uuid": "622c657e3a3a49e0961153f9a03c8d43",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from RMI's Vaisala CL51 instrument deployed at Arlon, Belgium",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Royal Meteorological Institute (RMI)'s Vaisala CL51 deployed at Arlon, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-56-101-70003.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35149,
            "uuid": "5f0e7fb72427499d90e176400dba31e3",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/canada/western/uwo-lufft-chm15k_A",
            "numberOfFiles": 1691,
            "volume": 4359764985,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35150,
                "uuid": "44ebc02da2cf4d0a8b4de454643c0b34",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from UWO's Lufft CHM15k \"Nimbus\" instrument deployed at Western, Canada",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from University of Western Ontario (UWO)'s Lufft CHM15k \"Nimbus\" deployed at Western, Canada.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-73009.\n Details for this WIGOS station are presently unavailable in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35152,
            "uuid": "36f31ff4a3c847079b61c1b20eb592a5",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/croatia/gmp-zagreb-maksimir/dhmz-lufft-chm15k_A",
            "numberOfFiles": 1449,
            "volume": 3705279453,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35153,
                "uuid": "614bb206c02b4d59b5ff2ecf589c7f48",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from DMHZ's Lufft CHM15k \"Nimbus\" instrument deployed at Gmp Zagreb Maksimir, Croatia",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Croatian Meteorological and Hydrological Service (DMHZ)'s Lufft CHM15k \"Nimbus\" deployed at Gmp Zagreb Maksimir, Croatia.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-14240.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35155,
            "uuid": "1f30985bafd64df0bd513fededc80ea8",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/cyprus/akrotiri/metoffice-vaisala-cl31_A",
            "numberOfFiles": 1653,
            "volume": 2224018229,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35156,
                "uuid": "b3b8bb92e88a4ee89c033211ea6970b5",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Met Office's Vaisala CL31 instrument deployed at Akrotiri, Cyprus",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Met Office's Vaisala CL31 deployed at Akrotiri, Cyprus.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-17601.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35158,
            "uuid": "5746c4c9e250453abb4636fda05256b6",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/czech-republic/cervena/chmi-vaisala-cl31_A",
            "numberOfFiles": 1704,
            "volume": 3737364652,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35159,
                "uuid": "46006fa888334683a8694dfb78e0c413",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from CHMI's Vaisala CL31 instrument deployed at Cervena, Czech Republic",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Czech Hydrometeorological Institute (CHMI)'s Vaisala CL31 deployed at Cervena, Czech Republic.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-11766.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35161,
            "uuid": "78e6901464f3470aaf75f3be744724e2",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/finland/alajarvi-moksy/fmi-vaisala-cl31_A",
            "numberOfFiles": 1049,
            "volume": 1409211322,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35162,
                "uuid": "7c9fd415b8c64d8eb2270eedca9bbe1b",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from FMI's Vaisala CL31 instrument deployed at Alajarvi Moksy, Finland",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Finnish Meteorological Institution (FMI)'s Vaisala CL31 deployed at Alajarvi Moksy, Finland.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-246-0-101533.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35164,
            "uuid": "94866dde4b9e4de0891a1f20b65d1c7b",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/france/agen/meteofrance-vaisala-cl31_A",
            "numberOfFiles": 1868,
            "volume": 3516865603,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35165,
                "uuid": "eee4461fad6141598c1b27ae76363b01",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Météo-France's Vaisala CL31 instrument deployed at Agen, France",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Météo-France's Vaisala CL31 deployed at Agen, France.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-07524.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35167,
            "uuid": "a53d7010206942168e8bf19a1fd4c367",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/germany/aachen/dwd-lufft-chm15k_0",
            "numberOfFiles": 1818,
            "volume": 4725345276,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35168,
                "uuid": "456ce527d99c401ab562684b66a7bdb8",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from DWD's Lufft CHM15k \"Nimbus\" instrument deployed at Aachen, Germany",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Deutscher Wetterdienst (DWD)'s Lufft CHM15k \"Nimbus\" deployed at Aachen, Germany.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-10505.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 35170,
            "uuid": "2d82b34ff87c412c9552d8f39b4b5e00",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/eprofile/data/daily_files/greece/athens-observatory/asnoa-vaisala-cl31_A",
            "numberOfFiles": 1520,
            "volume": 2070930720,
            "fileFormat": "Data are netCDF formatted.",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 35171,
                "uuid": "6773f88c193d4a72ae53a968d5e160d8",
                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from ASNOA's Vaisala CL31 instrument deployed at Athens Observatory, Greece",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Actinometric Station of National Observatory of Athens (ASNOA)'s Vaisala CL31 deployed at Athens Observatory, Greece.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-16714.\n Details for this WIGOS station are presently unavailable in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
            },
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                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from IMO's Vaisala CL51 instrument deployed at Bolungarvik, Iceland",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Icelandic Meteorological Office (IMO)'s Vaisala CL51 deployed at Bolungarvik, Iceland.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-04005.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
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                "short_code": "ob",
                "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Met Éireann's Vaisala CL31 instrument deployed at Casement, Ireland",
                "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Met Éireann's Vaisala CL31 deployed at Casement, Ireland.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-03967.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n    \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities."
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