Result List

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            "curationCategory": "A",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/SENTINEL3B_SLSTR/L3C/0.01/v4.00/daily/",
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                "ob_id": 44674,
                "uuid": "49b4836314db4fec8d05d14b85a8614d",
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                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Daily land Surface Temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3B, level 3 collated (L3C) global product (2018-2023), version 4.00",
                "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 2023. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nIn Version 4.00 the temporal coverage is extended to 31st December 2023. The emissivities used in the retrieval come from the Combined ASTER and MODIS Emissivity over Land (CAMEL) Version 2 database; in Version 4.00 a climatology is used since there are temporal instabilities in the CAMEL time series.\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.\r\n\r\nAn extended version of this dataset is also provided through the EOCIS project."
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/snow/data/scfg/MODIS/v4.0/",
            "numberOfFiles": 8644,
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                "ob_id": 43388,
                "uuid": "375ffdb8f0a445e380b4b9548655f5f9",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2023), version 4.0",
                "abstract": "This dataset provides daily Snow Cover Fraction on Ground (SCFG) derived from Terra MODIS observations, produced within the ESA Climate Change Initiative Snow project.\r\n\r\nSCFG expresses the proportion of land area within each about 1 km x 1 km pixel that is covered by snow. In forested areas, the masking effect of the forest canopy is corrected to estimate the SCFG. The SCFG is given in percentage (%) per pixel.\r\n\r\nThe SCFG product is available at about 1 km pixel size for global land areas except the Antarctica and Greenland ice sheets and permanent snow and ice areas. The coastal zones of Greenland are included. The SCFG time series spans 24 February 2000 to 31 December 2023.\r\n\r\nThe SCFG product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. 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 (SCDA) (Metsämäki et al., 2015).  For all remaining pixels, the snow_cci SCFG retrieval method is applied, 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 that first identifies pixels which are assessed as snow free, followed by SCFG retrieval for remaining pixels. \r\nPermanent snow/ice and water bodies are masked using the Land Cover CCI 2000 dataset, supplemented by a manually mapped salt-lake mask.  Per-pixel uncertainty is provided in the ancillary variable as an unbiased Root Mean Square Error (RMSE) for all observed land pixels.\r\n\r\nCompared with SCFG CRDP v3.0 (https://catalogue.ceda.ac.uk/uuid/80567d38de3f4b038ee6e6e53ed1af8a/) the SCFG CRDP v4.0 includes the following improvements: \r\n•\tmore permissive pre-classification allowing more pixels to enter the SCFG retrieval; \r\n•\tcorrection function applied to spectral reflectance for improved SCFG retrieval at low solar illumination conditions;\r\n•\tupdated spectral reflectance layers for snow free ground and snow free forest to improve SCFG retrieval;\r\n•\tupdated uncertainty estimation to account for the changes in the SCFG retrieval;\r\n•\timproved merging method for generating daily global SCFG products;\r\n•\tupdated salt lake mask;\r\n•\textended time series, to December 2023.\r\n\r\nThere are several days with no MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2022. In addition, on multiple days between 2000 and 2006 and in 2023, as well as on single days in 2012, 2015 and 2016, 2018, and 2020, the available MODIS data exhibit either limited spatial coverage, or corruption during data download. SCFG products are provided for all of these days, but they contain data gaps.\r\n\r\nThe SCFG product is aimed to support cryosphere and climate research applications, including variability and trend analyses, climate modelling and studies in hydrology, meteorology, and ecology.\r\nENVEO leads the SCFG product development and product generation from MODIS data, with contributions on the product development from Syke."
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/snow/data/scfv/MODIS/v4.0/",
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                "ob_id": 43387,
                "uuid": "bc13bb02a958449aac139853c4638f32",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2023), version 4.0",
                "abstract": "This dataset provides daily Snow Cover Fraction Viewable from above (SCFV) derived from Terra MODIS observations, produced within the ESA Climate Change Initiative Snow project.\r\n\r\nSCFV expresses the proportion of land area within each about 1 km x 1 km pixel that is covered by snow. SCFV represents snow viewable from above, whether on the forest canopy or on the ground in clear-cut or non-forested areas. The SCFV is given in percentage (%) per pixel.\r\n\r\nThis SCFV product is available at about 1 km pixel size for global land areas except the Antarctica and Greenland ice sheets and permanent snow and ice areas. The coastal zones of Greenland are included. The SCFV time series spans 24 February 2000 to 31 December 2023.\r\n\r\nThis SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. 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 (SCDA) (Metsämäki et al., 2015).   For all remaining pixels, the snow_cci SCFV retrieval method is applied, 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 that first identifies pixels which are assessed as snow free, followed by SCFV retrieval for remaining pixels. \r\nPermanent snow/ice and water bodies are masked using the Land Cover CCI 2000 dataset, supplemented by a manually mapped salt-lake mask.    Per-pixel uncertainty is provided in the ancillary variable as an unbiased Root Mean Square Error (RMSE) for all observed land pixels.\r\n\r\nCompared with SCFV CRDP v3.0 (https://catalogue.ceda.ac.uk/uuid/e955813b0e1a4eb7af971f923010b4a3/) the SCFV CRDP v4.0 includes the following improvements: \r\n•\tmore permissive pre-classification allowing more pixels to enter the SCFV retrieval; \r\n•\tcorrection function applied to spectral reflectance for improved SCFV retrieval at low solar illumination conditions;\r\n•\tupdated spectral reflectance layers for snow free ground and snow free forest to improve SCFV retrieval;\r\n•\tupdated uncertainty estimation to account for the changes in the SCFV retrieval;\r\n•\timproved merging method for generating daily global SCFV products;\r\n•\tupdated salt lake mask;\r\n•\textended time series, to December 2023.\r\n\r\nThere are several days with no MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2022. In addition, on multiple days between 2000 and 2006 and in 2023, as well as on single days in 2012, 2015 and 2016, 2018, and 2020, the available MODIS data exhibit either limited spatial coverage, or corruption during data download. SCFV products are provided for all of these days, but they contain data gaps.\r\n\r\nThe SCFV product is aimed to support cryosphere and climate research applications, including variability and trend analyses, climate modelling and studies in hydrology, meteorology, and ecology.\r\nENVEO leads the SCFV product development and product generation from MODIS data, with contributions on the product development from Syke."
            },
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        {
            "ob_id": 45115,
            "uuid": "ca802ebb56b14fe3a5d64d44fea0e790",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/badc/ar6_wg1/data/ch_09/ch9_fig13/v20251121",
            "numberOfFiles": 16,
            "volume": 12431664,
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            "observation": {
                "ob_id": 45114,
                "uuid": "f5f541ce05c44062a39d9a0e9e9463bc",
                "short_code": "ob",
                "title": "Chapter 9 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 9.13 (v20251121)",
                "abstract": "Data for Figure 9.13 from Chapter 9 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 9.13 shows Arctic sea ice historical records and CMIP6 projections. \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\nFox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. 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. 1211–1362, doi:10.1017/9781009157896.011.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 2 subpanels, with data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n- (Left panel) Absolute anomaly of monthly-mean Arctic sea ice area during the period 1979 to 2019 relative to the average monthly-mean Arctic sea ice area during the period 1979 to 2008. \r\n- (Right panel) Sea ice concentration in the Arctic for March and September, which usually are the months of maximum and minimum sea ice area, respectively. \r\n\r\nFirst column: Satellite-retrieved mean sea ice concentration during the decade 1979–1988. Second column: Satellite-retrieved mean sea ice concentration during the decade 2010-2019. \r\nThird column: Absolute change in sea ice concentration between these two decades, with grid lines indicating non-significant differences. \r\nFourth column: Number of available CMIP6 models that simulate a mean sea ice concentration above 15 % for the decade 2045–2054. \r\n\r\nThe average observational record of sea ice area is derived from the UHH sea ice area product (Doerr et al., 2021), based on the average sea ice concentration of OSISAF/CCI (OSI-450 for 1979–2015, OSI-430b for 2016–2019) (Lavergne et al., 2019), NASA Team (version 1, 1979–2019) (Cavalieri et al., 1996) and Bootstrap (version 3, 1979–2019) (Comiso, 2017) that is also used for the figure panels showing observed sea ice concentration. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 9.SM.9)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 9.13\r\n \r\n - Data file: NSIDC_polehole_big.nc\r\n - Data file: NSIDC_polehole_small.nc\r\n - Data file: SeaIceArea__NorthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: SeaIceArea__SouthernHemisphere__monthly__UHH__v2019_fv0.01.nc\r\n - Data file: cryo_div.txt\r\n - Data file: cryo_seq.txt\r\n\r\nExtracted from  'mapplot_data.npz':\r\n - Data file: nmodels_ssp245_nh_nhsummer.nc\r\n - Data file: nmodels_ssp245_nh_nhwinter.nc\r\n - Data file: nmodels_ssp245_sh_nhsummer.nc\r\n - Data file: nmodels_ssp245_sh_nhwinter.nc\r\n - Data file: sic_obs_nh_nhsummer.nc\r\n - Data file: sic_obs_nh_nhwinter.nc\r\n - Data file: sic_obs_sh_nhsummer.nc\r\n - Data file: sic_obs_sh_nhwinter.nc\r\n\r\nData from the datafile  'mapplot_data.npz' included in the 'Plotted Data' folder of the dedicated GitHub repository has been extracted in NetCDF format for archival by the authors. The original .npz file is not archived here but on Zenodo at the link provided in the Related Documents section of this catalogue record.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nNSIDC is the National Snow and Ice Data Center.\r\nUHH is the University of Hamburg (Universtität Hamburg).\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nBoth panels were plotted using standard matplotlib software - code is available via the link in the documentation.\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 - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 9)\r\n - Link to the Supplementary Material for Chapter 9, which contains details on the input data used in Table 9.SM.9\r\n- Link to the data and code used to produce this figure and others in Chapter 9, archived on Zenodo.\r\n- Link to the output data and scripts for this figure, contained in a dedicated GitHub repository."
            },
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        {
            "ob_id": 45122,
            "uuid": "7b52778254544eeababf996a4220b864",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/snow/data/scfg/SLSTR/v1.0",
            "numberOfFiles": 853,
            "volume": 86888387272,
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            "observation": {
                "ob_id": 40360,
                "uuid": "38a71d034b5c4097821de29ee3bc2498",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from SLSTR (2020 - 2022), version 1.0",
                "abstract": "This dataset provides daily Snow Cover Fraction on Ground (SCFG) derived from Sentinel-3A&B SLSTR observations, produced within the ESA Climate Change Initiative Snow project.\r\n\r\nSCFG expresses the proportion of land area within each about 1 km x 1 km pixel that is covered by snow. In forested areas, the masking effect of the forest canopy is corrected to estimate the SCFG. The SCFG is given in percentage (%) per pixel. The SCFG product is available at about 1 km pixel size for global land areas except the Antarctica and Greenland ice sheets and permanent snow and ice areas. The coastal zones of Greenland are included. The SCFG time series spans 01 September 2020 to 31 December 2022. The time series is extended within the Copernicus Climate Change Service (C3S) for Cryosphere from 1 January 2023 onwards. \r\n\r\nThe SCFG product is based on Sea and Land Surface Temperature Radiometer (SLSTR) data on-board the Sentinel-3A and Sentinel-3B satellites. For the SCFG product generation from SLSTR, 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 (SCDA) (Metsämäki et al., 2015). For all remaining pixels, the snow_cci SCFG retrieval method is applied, 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 that first identifies pixels which are assessed as snow free, followed by SCFG retrieval for remaining pixels. Permanent snow/ice and water bodies are masked using the Land Cover CCI 2000 dataset, supplemented by a manually mapped salt-lake mask. Per-pixel uncertainty is provided in the ancillary variable as an unbiased Root Mean Square Error (RMSE) for all observed land pixels.\r\n\r\nThe retrieval approach used for the SLSTR based SCFG CRDP (Climate Research Data Package) v1.0 is the same as the one used for the SCFG CRDP v4.0 from Moderate resolution Imaging Spectroradiometer (MODIS) on board of the Terra satellite, covering the period 2000 – 2023 (https://catalogue.ceda.ac.uk/uuid/ 375ffdb8f0a445e380b4b9548655f5f9).\r\nThe SCFG product is aimed to support cryosphere and climate research applications, including variability and trend analyses, climate modelling and studies in hydrology, meteorology, and ecology.\r\n\r\nENVEO leads the SCFG product development and product generation from SLSTR data, with contributions on the product development from Syke."
            },
            "onlineresource_set": []
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        {
            "ob_id": 45123,
            "uuid": "634c99a0fcc849a2b911cd1be835db8f",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/snow/data/scfv/SLSTR/v1.0",
            "numberOfFiles": 853,
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            "observation": {
                "ob_id": 40359,
                "uuid": "f5dce1f7bec2447093cf460a4d3ba2c2",
                "short_code": "ob",
                "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from SLSTR (2020 - 2022), version 1.0",
                "abstract": "This dataset provides daily Snow Cover Fraction Viewable from above (SCFV) derived from Sentinel-3A&B SLSTR observations, produced within the ESA Climate Change Initiative Snow project.\r\n\r\nSCFV expresses the proportion of land area within each about 1 km x 1 km pixel that is covered by snow. SCFV represents snow viewable from above, whether on the forest canopy or on the ground in clear-cut or non-forested areas. The SCFV is given in percentage (%) per pixel. The SCFV product is available at about 1 km pixel size for global land areas except the Antarctica and Greenland ice sheets and permanent snow and ice areas. The coastal zones of Greenland are included. The SCFV time series spans 01 September 2020 to 31 December 2022. The time series is extended within the Copernicus Climate Change Service (C3S) for Cryosphere from 1 January 2023 onwards.\r\n\r\nThe SCFV product is based on Sea and Land Surface Temperature Radiometer (SLSTR) data on-board the Sentinel-3A and Sentinel-3B satellites. For the SCFV product generation from SLSTR, 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 (SCDA) (Metsämäki et al., 2015). For all remaining pixels, the snow_cci SCFV retrieval method is applied, 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 that first identifies pixels which are assessed as snow free, followed by SCFV retrieval for remaining pixels. Permanent snow/ice and water bodies are masked using the Land Cover CCI 2000 dataset, supplemented by a manually mapped salt-lake mask. Per-pixel uncertainty is provided in the ancillary variable as an unbiased Root Mean Square Error (RMSE) for all observed land pixels.\r\n\r\nThe retrieval approach used for the SLSTR based SCFV CRDP (Climate Research Data Package) v1.0 is the same as the one used for the SCFV CRDP v4.0 from Moderate resolution Imaging Spectroradiometer (MODIS) on board of the Terra satellite, covering the period 2000 – 2023 (https://catalogue.ceda.ac.uk/uuid/bc13bb02a958449aac139853c4638f32/).\r\nThe SCFV product is aimed to support cryosphere and climate research applications, including variability and trend analyses, climate modelling and studies in hydrology, meteorology, and ecology. \r\n\r\nENVEO leads the SCFV product development and product generation from SLSTR data, with contributions on the product development from Syke."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 45140,
            "uuid": "94167aff10c240f0becf02fa0be00ded",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v09.2",
            "numberOfFiles": 12124,
            "volume": 7860905106,
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            "observation": {
                "ob_id": 45085,
                "uuid": "2600f842cfeb481bb21f032a5741c353",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 09.2",
                "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The ACTIVE product has been created by fusing scatterometer soil moisture products, derived from the active remote sensing instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v09.2 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees and is an extension in time of the v09.1 ACTIVE product. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2024-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896."
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            "observation": {
                "ob_id": 45086,
                "uuid": "d4e66299f5054129b8076fb7502949e1",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 09.2",
                "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The COMBINED product has been created by directly merging Level 2 scatterometer ('active' remote sensing) and radiometer ('passive' remote sensing) soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v09.2 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees and is an extension in time of the v09.1 COMBINED product. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2024-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896."
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                "ob_id": 45087,
                "uuid": "c93c99588d5848b1ac7833e3bc6d5c2d",
                "short_code": "ob",
                "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 09.2",
                "abstract": "The Soil Moisture CCI PASSIVE dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The PASSIVE product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP passive remote sensing satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v09.2 PASSIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees and is an extension in time of the v09.1 PASSIVE product. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2024-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896."
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                "title": "ESA River Discharge Climate Change Initiative (RD_cci):  Nadir radar altimeters Water Level product, v2.0",
                "abstract": "This dataset contains water level (WL) data from the ESA Climate Change Initiative River Discharge project (RD_cci).   Water level in this context corresponds to the distance between river surface water and a reference surface (the WGS84 ellipsoid). This physical variable might also be referred to as Water Surface Elevation (WSE) in other dataset or publications.\r\n\r\nThis version of the dataset is v2.0\r\n\r\nThese river water level time series have been computed in at 54 locations (within 18 river basins). The data has been derived from nadir viewing satellite radar altimeter missions (ERS-2, Envisat, Saral, Topex-Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-3A/B and Sentinel 6A). At each location, time series are provided for each available single nadir radar altimetry mission. Based on these single mission time series, merged multi-missions WL time series (with two different methodologies for some basins) have also been produced."
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                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Daily land surface temperature from ATSR-2 (Along-Track Scanning Radiometer 2),  level 3 collated (L3C) global product (1995-2003), version 4.00",
                "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 https://artefacts.ceda.ac.uk/frozen_sites/www.atsr.rl.ac.uk/documentation/docs/userguide/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 June 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\nVersion 4.00 uses data from the 4th reprocessing of the ATSR L1B archive. The emissivities used in the retrieval come from the Combined ASTER and MODIS Emissivity over Land (CAMEL) Version 2 database; in Version 4.00 a climatology is used since there are temporal instabilities in the CAMEL time series.\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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                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Daily land surface temperature from AATSR (Advanced Along-Track Scanning Radiometer), level 3 collated (L3C) global product (2002-2012), version 4.00",
                "abstract": "This dataset contains daily-averaged land surface temperatures (LSTs) and their uncertainty estimates from the Advanced Along-Track Scanning Radiometer (AATSR) on the 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 20th May 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\nVersion 4.00 uses data from the 4th reprocessing of the ATSR L1B archive. The emissivities used in the retrieval come from the Combined ASTER and MODIS Emissivity over Land (CAMEL) Version 2 database; in Version 4.00 a climatology is used since there are temporal instabilities in the CAMEL time series.\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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            "dataPath": "/neodc/esacci/land_surface_temperature/data/METOPA_AVHRR/L3C/0.01/v2.00/daily/",
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            "observation": {
                "ob_id": 44647,
                "uuid": "c836ded4f8154c3ba86ee58ec0a7a7b1",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Daily land surface temperature from the Metop-A AVHRR (Advanced Very High Resolution Radiometer) instrument, level 3 collated (L3C) global product, version 2.00",
                "abstract": "This dataset contains daily land surface temperatures (LSTs) and their uncertainty estimates from the Advanced Very High Resolution Radiometer 3 (AVHRR-3) on the Metop-A satellite. 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 METOP-A equator crossing times which are 9.30 and 21:30 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. 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 March 2007 and ends on 31st December 2020. There are minor interruptions during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nThe emissivities used in the retrieval come from the Combined ASTER and MODIS Emissivity over Land (CAMEL) Version 2 database; in Version 4.00 a climatology is used since there are temporal instabilities in the CAMEL time series.\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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            "short_code": "result",
            "curationCategory": "B",
            "dataPath": "/neodc/esacci/sea_level/data/XTRACK_ALES_SLA/Trends_SelectedSites/v3.0/",
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                "uuid": "4be5091f70f04e50b1c1da79d2d89a97",
                "short_code": "ob",
                "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): New network of virtual altimetry stations for measuring sea level along the world coastlines from 2002 to 2021, v3.0",
                "abstract": "This dataset contains a 19.5-year-long (January 2002 to June 2021), high-resolution (20 Hz), along-track sea level dataset in most of the world coastal zones, including tropical islands. It has been developed within the sea level project of the European Space Agency (ESA) Climate Change Initiative (SL_cci). \r\n\r\nThe main objective of this dataset is to analyze the sea level trends as well as the inter-annual variability at local scale at an average of less than 2.5km from the coastline. It provides essential information in areas devoid of other sources of measurements, and it also allows filling the gaps in existing timeseries of tide gauges located nearby the stations.\r\n\r\nThis dataset of coastal sea level anomalies is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series.\r\n\r\nThis large amount of coastal sea level estimates has been further analysed to produce the present dataset: a total of 1634 altimetry-based virtual coastal stations have been selected and sea level anomalies time series together with associated coastal sea level trends have been computed over the study time span.\r\n\r\nThe new updated version (v3.0; June 2025) of along-track coastal sea level time series and associated trends from January 2002 to June 2021 differs from the previous v2.4 product (released in November 2024) by a spatial extension. It also uses the new improved FES22 ocean tide model instead of FES14 model in the previous versions. The data editing (outlier removal) has slightly evolved, and a new variable has been added (sla_mean_10pts_filt). We strongly recommend the users to use this latest v3.0 product.\r\n\r\nFor the latest version of the documentation, see the 'Technical Coastal Sea Level' Key Documents section of the project's website (https://climate.esa.int/en/projects/sea-level/).\r\nThis dataset is v3.0 of the data and is a copy of the v3.0 data published on the SEANOE (SEA scieNtific Open data Edition) website (https://doi.org/10.17882/74354#122284).\r\n\r\nThe dataset should be cited as: Cazenave Anny, Gouzenes Yvan, Leclercq Lancelot, Birol Florence, Legér Fabien, Passaro Marcello, Calafat Francisco M, Shaw Andrew, Niño Fernando, Legeais Jean François, Oelsmann Julius, Benveniste Jérôme, Connors Sarah (2025). New network of virtual altimetry stations for measuring sea level along the world coastlines. SEANOE. https://doi.org/10.17882/74354\r\n\r\nIn addition, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :\r\n\r\n- Cazenave Anny, Gouzenes Yvan, Birol Florence, Leger Fabien, Passaro Marcello, Calafat Francisco M., Shaw Andrew, Nino Fernando, Legeais Jean François, Oelsmann Julius, Restano Marco, Benveniste Jérôme (2022). Sea level along the world’s coastlines can be measured by a network of virtual altimetry stations. Communications Earth & Environment, 3 (1). https://doi.org/10.1038/s43247-022-00448-z\r\n\r\n- Benveniste Jérôme, Birol Florence, Calafat Francisco, Cazenave Anny, Dieng Habib, Gouzenes Yvan, Legeais Jean François, Léger Fabien, Niño Fernando, Passaro Marcello, Schwatke Christian, Shaw Andrew (2020). Coastal sea level anomalies and associated trends from Jason satellite altimetry over 2002–2018. Scientific Data, 7 (1). https://doi.org/10.1038/s41597-020-00694-w"
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            "dataPath": "/neodc/esacci/precursors/data/MERGED_CO/v1.0",
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                "ob_id": 44637,
                "uuid": "6242532d87d442a3acf0171d35c02e56",
                "short_code": "ob",
                "title": "ESA Precursors for Aerosols and Ozone Climate Change Initiative (Precursors_cci): Merged CO product, version 1.0",
                "abstract": "The carbon monoxide (CO) Climate Data Record (CDR) merged product is a new monthly Level 3 CO product developed by merging satellite data from the IASI instrument (on METOP-A, B, and C) and the MOPITT instrument (on TERRA) as part of the ESA Climate Change Initiative (CCI) Precursors for Aerosols and Ozone project.\r\n\r\nAn intermediate IASI L3 product was created averaging cloud-free Level 2 CO from the three METOP platforms (A, B and C) using the Cloud Detection Product of Whitburn et al. (2022). These data were then combined with MOPITT V9T L3 data using a weighted averaging approach. Weights were determined based on the MOPITT CO total column to prior ratio. \r\n\r\nThe merged dataset includes CO total column monthly 1°x1° resolution grids as well as uncertainty grids, for both daytime and night-time from January 2008 to December 2024. Surface altitude grids as well as data source flags grids are also provided.\r\n\r\nThe European Space Agency (ESA) Precursors for Aerosol and Ozone Climate Change Initiative (Precursors CCI) project is part of ESA's Climate Change Initiative (CCI) to produce long term datasets of Essential Climate Variables derived from global satellite data.\r\n\r\nThe version number is 1.0. Data are available in NetCDF format."
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                "ob_id": 45190,
                "uuid": "d8d9bf82d2764f75b5177dadfdfbc258",
                "short_code": "ob",
                "title": "Ocean bottom node wide-angle seismic data at the Semenov-1 Hydrothermal Site region of the Mid-Atlantic Ridge during the RRS James Cook cruise JC254 (November 2023)",
                "abstract": "The dataset contains wide-angle seismic data from 6 ocean bottom nodes (OBX-90, GEOSPACE) collected during RRS James Cook cruise JC254 in November 2023. The data were acquired at the Semenov-1 Hydrothermal Field region of the Mid-Atlantic Ridge at 13°30'N, and were shot in two sequences (SEM1 and SEM1B). Two GI-guns were used as seismic sources, each with a total volume of 210 cubic inches (105 cu. inch generator, 105 cu. inch injector chamber). The data were recorded at a sampling rate of 2000 Hz (500 µs), with a shot interval of 8 s at a ship speed of 5 knots, resulting in shot interval of ~20.5 m. The data are provided in raw SEGY format, cut into four components (three geophone channels and one hydrophone channel). The SEGY file has a trace length of 10s and 20000 samples. This dataset was collected with an aim to derive a seismic velocity structure of the SEM-1 seafloor massive sulphide deposit region. The aim was to understand the interplay between tectonic faulting, magmatism, and hydrothermal circulation at the ultramafic-hosted hydrothermal systems along slow-spreading ridges. The data were collected as part of a NERC-funded strategic research project called 'Ultramafic-hosted mineral Resource Assessment (ULTRA)', grant reference NE/S004068/1. The data were processed and interpreted as part of a PhD studentship hosted by the University of Southampton, awarded to Szu-Ying Lai, and funded by Equinor A.S, Norway."
            },
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        {
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/crowd-grid/data/crowd-grid/v1.0",
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            "observation": {
                "ob_id": 45178,
                "uuid": "1ee84eb83cf8406e8ec86f914aaf172d",
                "short_code": "ob",
                "title": "Crowd-Grid Gridded Climate Observations on a 1km grid over the UK (2013-2024, v1.0, prototype)",
                "abstract": "The Crowd-Grid dataset comprises daily maximum/minimum temperature grids spanning the period 01/01/2013 to 31/12/2024 at 1km resolution for the UK. Crowd-Grid uses crowdsourced observations from WOW (the UK Met Office Weather Observation Website) and other sources to give a more detailed view of the temperatures people experience, including in built-up areas.\r\n\r\nThis dataset differs from and complements the \"standard\" gridded dataset, HadUK-Grid, the Met Office’s official climate record. HadUK-Grid uses the Met Office's network of calibrated instruments to give the UK's official record of temperature and is typically representative of grassy fields and parks. Crowd-Grid adds crowdsourced observations to give a more detailed view of the temperatures people experience, including in built-up areas.\r\n\r\nFor further details on the dataset and its interpretation, refer to the provided README (doi:10.5281/zenodo.17787357)."
            },
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        {
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            "observation": {
                "ob_id": 45183,
                "uuid": "9f45ae9217c44dea82be3ba4ef0fa30f",
                "short_code": "ob",
                "title": "Recent Heat Packs for local areas in the UK (v1.0, prototype)",
                "abstract": "This dataset contains Recent Heat Packs derived from the Crowd-Grid dataset. A Recent Heat Pack is a set of .csv files and a factsheet that provide information on temperatures and climate metrics from recent years (2013-2024). Created for each UK local authority, they are designed to equip users to fit extreme events into the context of recent climate. The Recent Heat Packs may be downloaded and used to understand how climate varies locally, to support decisions on climate adaptation\r\n\r\nCrowd-Grid is a new dataset of daily maximum/minimum temperatures grids spanning the period 01/01/2013 to 31/12/2024 at 1km resolution for the UK. Crowd-Grid uses crowdsourced observations from WOW and other sources to give a more detailed view of the temperatures people experience, including in built-up areas. It differs from and complements the standard dataset, HadUK-Grid - the Met Office’s official climate record.\r\n\r\nA set of Recent Heat Packs have been developed that provide for each of the 393 UK local authorities:\r\n–\ta 2-page Recent Heat Factsheet, which complements the 9-page Climate Report in the Met Office's Local Authority Climate Service (LACS)\r\n–\tthree .csv files that provide the underlying data for the local authority and its constituent census areas: MSOAs (Middle Layer Super Output Areas) in England and Wales, Intermediate Zones in Scotland, and District Electoral Areas in Northern Ireland\r\n\r\nFor further details on the dataset and its interpretation, refer to the README (doi:10.5281/zenodo.17787357)."
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        {
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                "ob_id": 45196,
                "uuid": "ae24a127728941bdbb10d04ecd8fbfff",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the zstar_Smag simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. In this simulation the fixed biharmonic viscosity is replaced with biharmonic Smagorinsky viscosity with a coefficient CMSmag=3; it is referred to as “zstar_Smag\". The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
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        {
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                "ob_id": 45198,
                "uuid": "4a5703b6cb4a4a6fb0e4c8b1671c9a68",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the ztilde_control simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. In this simulation the default z-star vertical coordinate is replaced by the z-tilde filtered quasi-adiabatic coordinate (Leclair and Madec, 2011; Megann et al., 2022) with filter timescale set to 20 days and the coordinate restoration timescale to 60 days, but otherwise uses the standard namelist settings for this configuration; it is referred to as \"ztilde_control\". The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
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        {
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            "observation": {
                "ob_id": 45200,
                "uuid": "b71dae97c57e45b3a5ba9ee8dadcbbb7",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the zstar_triads simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. In this simulation the default lateral tracer diffusion scheme of Redi and Cox is replaced with the Griffies triads scheme (Griffies et al., 1998); it is referred to a “zstar_triads”. The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 45201,
            "uuid": "8cd09229db9b4917864f454f1326b7fd",
            "short_code": "result",
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            "observation": {
                "ob_id": 45202,
                "uuid": "9ad1079501a5411f80e0aedfb2d66cad",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the zstar_visc_x1.8 simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. In this simulation the fixed viscosity is increased by a factor of 1.8 with respect to that in the control; it is referred to as “zstar_visc_x1.8\". The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
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        {
            "ob_id": 45203,
            "uuid": "b574898ebd4b47b6a1da1fab433d5a29",
            "short_code": "result",
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            "observation": {
                "ob_id": 45204,
                "uuid": "1f62d7372b0542608b5f882383b520ee",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the ztilde_Smag simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. In this simulation the default z-star vertical coordinate is replaced by the z-tilde filtered quasi-adiabatic coordinate (Leclair and Madec, 2011; Megann et al., 2022) with filter timescale set to 20 days and the coordinate restoration timescale to 60 days and replaces the fixed biharmonic viscosity with biharmonic Smagorinsky viscosity with a coefficient CMSmag=3; it is referred to as “ztilde_Smag”. The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 45205,
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            "short_code": "result",
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            "observation": {
                "ob_id": 45206,
                "uuid": "b552ba37b166402f85cc19280e48b062",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the zstar_FCT2V simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. In this simulation the vertical tracer advection is changed from the default of fourth order to second order; it is referred to as \"zstar_FCT2V\". The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
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        {
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            "short_code": "result",
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            "observation": {
                "ob_id": 45208,
                "uuid": "029c9c7dc7894290b4e27c0042028cdf",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the zstar_FCT2H simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. In this simulation the horizontal tracer advection is changed from the default of fourth order to second order; it is referred to as \"zstar_FCT2H\". The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
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        {
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            "short_code": "result",
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            "dataPath": "/bodc/soc251000",
            "numberOfFiles": 4740,
            "volume": 3449729445707,
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            "storageStatus": "online",
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            "observation": {
                "ob_id": 45210,
                "uuid": "ebe384bfab9e4c78b3d68e82f6dbe39e",
                "short_code": "ob",
                "title": "Model output containing ocean, atmospheric and sea ice variables from the zstar_control simulation of the HadGEM3-GC5-LM coupled climate model (1976-2035).",
                "abstract": "This dataset contains monthly means of ocean, atmospheric and sea ice variables from a 60-year (1976-2035) integration of the HadGEM3-GC5-LM coupled model, with fixed year 2000 control atmospheric composition. The archived model output includes monthly means from the NEMO v4.0.4 ocean component on T, U, V and W grids; monthly means from the SI3 sea ice model; and monthly means from the GAL9 atmosphere-land model. In addition, five-day means of the temperature and salinity (\"T grid\") and of the meridional velocity (\"V grid\") over a ten-year period are provided: these were used to estimate the total diapycnal mixing. This simulation uses the standard namelist settings for this configuration, constituting the control simulation for the eight-member ensemble, and is referred to as \"zstar_control\". The outputs were generated under the Marine LTSS: Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC) under reference NE/R015953/1."
            },
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        },
        {
            "ob_id": 45211,
            "uuid": "52b7c57b7e1d4e97b05affe9997e0551",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/glosat/data/GloSAT_historical1750",
            "numberOfFiles": 1982,
            "volume": 2589423723850,
            "fileFormat": "CMOR CMIP6 NetCDF",
            "storageStatus": "online",
            "storageLocation": "internal",
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            "observation": {
                "ob_id": 45105,
                "uuid": "9487085a6a3d4ca1aafa7c569e840d2a",
                "short_code": "ob",
                "title": "GloSAT historical1750 simulations : UKESM1-1-LL simulations covering the period 1750-2014",
                "abstract": "The Global Surface Air Temperature (GloSAT) model simulations were run on UK supercomputing platforms ARCHER2 and MONSooN using the UKESM1-1-LL UK Earth System Model described in Mulcahy, et al 2023 (https://doi.org/10.5194/gmd-16-1569-2023).\r\nThe simulations were run under the NERC funded project GloSAT. NE/S015647/2\r\n\r\nThe experiments and model set up are all described in:\r\nBallinger, A., Schurer, A., Hegerl, G., Dittus, A., Hawkins, E., Cornes, R., Kent, E., Marshall, L., Morice, C., Osborn, T., and Rayner, N.A. Rumbold, S.:(2025) Importance of beginning industrial-era climate simulations in the eighteenth century, Environmental Research Letters,650, accepted.\r\n\r\nThis dataset contains 100 monthly variables for 6 historical 1750 ensemble members in CMOR CMIP6 netcdf data format (Climate Model Output Rewriter Coupled Model Intercomparison Project 6)."
            },
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        {
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            "uuid": "9a4cab80b59d4e1192c5095badffb6e3",
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            "dataPath": "/badc/deposited2026/EAWAVES-CLIM/",
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                "ob_id": 45184,
                "uuid": "2f1d9204781e471cb76c2c4fdf3a0383",
                "short_code": "ob",
                "title": "European Atlantic Wave Data under Historical and Future Climate Scenarios (EAWAVES-CLIM)",
                "abstract": "This dataset provides 3-hourly ocean wave data for the European Atlantic domain spanning three 30-year periods: a historical simulation (1985–2014) and future projections (2030–2059) under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). It includes directional wave spectral data at 1,031 fixed offshore locations along the Atlantic coast of Europe, as well as gridded wave parameters covering the full North Atlantic simulation domain.\r\n\r\nThe wave data were generated using the Simulating WAves Nearshore (SWAN) model, forced with high-resolution winds obtained through dynamical downscaling of global climate models using the Weather Research and Forecasting (WRF) model, and open boundary conditions derived from WaveWatch III simulations.\r\n\r\nThe spectral component consists of NetCDF-4 files describing wave energy distribution across 25 frequency bands and 36 directions at offshore locations spaced approximately 10 km alongshore and 50 km from the coast."
            },
            "onlineresource_set": []
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        {
            "ob_id": 45215,
            "uuid": "d4290927fc02434c8ab273769a71b45a",
            "short_code": "result",
            "curationCategory": "",
            "dataPath": "https://catalogue.ceda.ac.uk",
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            "observation": {
                "ob_id": 11635,
                "uuid": "edbd3036e9424e8c9257c1aa3a93ebd0",
                "short_code": "ob",
                "title": "Data from LANDSAT4 MSS at Landsat 4 for the Landsat Campaign",
                "abstract": "The Landsat 4 was placed into lower orbits than the previous Landsat spacecraft and carried improved instrument suites. Landsat 4 carried a Thematic Mapper (TM) imaging sensors in addition to the Multi-Spectral Scanner (MSS) used on the first three Landsat satellites."
            },
            "onlineresource_set": []
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        {
            "ob_id": 45216,
            "uuid": "bd6b7c987aaf44fe82abf6fc262ef411",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/icecaps-melt/data/202408CampRavenSnowShearStreng",
            "numberOfFiles": 2,
            "volume": 2839,
            "fileFormat": "Data are BADC-CSV formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 44798,
                "uuid": "3ef571a45bcc4d95aaf8e48569a21ab5",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Manual shear strength from a 1-m snow profile in SW Greenland (August 2024)",
                "abstract": "Shear strength (kPa) was measured in a 1-m deep snow profile from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Summer 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. This profile was made 2-3 m away from the SLEIGH.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 45217,
            "uuid": "4703addd41054af2b004881ce3868624",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/icecaps-melt/data/202405CampRavenSnowShearStreng",
            "numberOfFiles": 3,
            "volume": 3890,
            "fileFormat": "Data are BADC-CSV formatted",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 44762,
                "uuid": "23bd97b1ac1e4e318234b2f2cab0892b",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Manual shear strength from two 1-m snow profiles in SW Greenland (May 2024)",
                "abstract": "Shear strength (kPa) was measured in two 1-m deep snow profiles from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Spring 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. Profile 1 was measured on 15 May 2024, 2-3 meters from the eventual SLEIGH installation. Profile 2 was measured on 18 May 2024, 20 m from the eventual SLEIGH installation.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 45218,
            "uuid": "ba1c8175aac84e0abe75b41ce0b11dff",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/icecaps-melt/data/202408CampRavenSnowDens1",
            "numberOfFiles": 2,
            "volume": 2539,
            "fileFormat": "Data are BADC-CSV formatted",
            "storageStatus": "online",
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            "oldDataPath": [],
            "observation": {
                "ob_id": 44791,
                "uuid": "42253e31a80947c1b63a5af456f04eeb",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Manual snow density from one 1-m snow profile in southwest Greenland (August 2024)",
                "abstract": "Manual snow density (km m-3) from a 1-m deep snow profile from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Summer 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. Manual snow density was measured using American Avalanche Association classifications and procedures (Snow, Weather, and Avalanche Guidelines, 4th Edition, 2022). This profile was made 2-3 m away from the SLEIGH.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
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                "short_code": "ob",
                "title": "ICECAPS-MELT: Manual snow density from two 1-m snow profiles in southwest Greenland (May 2024)",
                "abstract": "Manual snow density (km m-3) from two 1-m deep snow profile from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Spring 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. Manual snow density was measured using American Avalanche Association classifications and procedures (Snow, Weather, and Avalanche Guidelines, 4th Edition, 2022). Profile 1 was measured on 15 May 2024, 2-3 meters from the eventual SLEIGH installation. Profile 2 was measured on 18 May 2024, 20 m from the eventual SLEIGH installation.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
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        {
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            "observation": {
                "ob_id": 44796,
                "uuid": "efcba0f0ba4248c18ff3db743f7d0410",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Manual snow properties from one 1-m snow profile in SW Greenland (August 2024)",
                "abstract": "Snow properties were measured in a 1-m deep snow profile from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Spring 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. The properties measured were snow grain size, snow crystal habit/form, and hand hardness. A layer identification was performed prior to these measurements. This profile was made 2-3 m away from the SLEIGH.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
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                "uuid": "1ce3e71a2ca54807a1360a1ea4a1053a",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Manual snow properties from two 1-m snow profiles in SW Greenland (May 2024)",
                "abstract": "Snow properties were measured in two 1-m deep snow profiles from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Spring 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. A layer identification was performed and then snow properties were measured: snow grain size, snow crystal habit/form, and hand hardness. Profile 1 was measured on 15 May 2024, 2-3 meters from the eventual SLEIGH installation. Profile 2 was measured on 18 May 2024, 20 m from the eventual SLEIGH installation.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
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        {
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                "uuid": "0eaf19b647c54f489f5c5cbb8d0d83ab",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Permittivity-based snow density from a 1-m snow profile in SW Greenland (August 2024)",
                "abstract": "Snow density (kg m-3) was measured using two different permittivity-based devices (FPGA Company SnowPro-40 and SnowPro-17 sensors) from a 1-m deep snow profile from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Spring 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. This profile was made 2-3 m away from the SLEIGH.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
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        },
        {
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            "numberOfFiles": 5,
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                "ob_id": 44753,
                "uuid": "a49b455ac2c44d4e9a365c001c9f575f",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Permittivity-based snow density from two 1-m snow profiles in SW Greenland (May 2024)",
                "abstract": "Snow density (kg m-3) was measured using two different permittivity-based devices (FPGA Company SnowPro-40 and SnowPro-17 sensors) from two 1-m deep snow profiles from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Spring 2024. The snow profile measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. Profile 1 was measured on 15 May 2024, 2-3 meters from the eventual SLEIGH installation. Profile 2 was measured on 18 May 2024, 20 m from the eventual SLEIGH installation.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
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        },
        {
            "ob_id": 45224,
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            "dataPath": "/badc/icecaps-melt/data/202408CampRavenSnowSSA",
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                "ob_id": 44800,
                "uuid": "55467b8d0a314f408e73175d553fbdb1",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Snow specific surface area from a 1-m snow profile in SW Greenland (August 2024)",
                "abstract": "Snow specific surface area (SSA, m2/m3) was measured using an active near-infrared sensor (FPGA Company Infrasnow) from a 1-m deep snow profile from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Summer 2024. The snow SSA measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment. This profile was made 2-3 m away from the SLEIGH.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
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        },
        {
            "ob_id": 45225,
            "uuid": "5320a37ab45d48a2b3152fa9126cf7e0",
            "short_code": "result",
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            "dataPath": "/badc/icecaps-melt/data/202405CampRavenSnowSSA",
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            "observation": {
                "ob_id": 44765,
                "uuid": "71594a494413446bbfe4583be97fe41b",
                "short_code": "ob",
                "title": "ICECAPS-MELT: Snow specific surface area from two 1-m snow profiles in SW Greenland (May 2024)",
                "abstract": "Snow specific surface area (SSA, m2/m3) was measured using an active near-infrared sensor (FPGA Company Infrasnow) from two 1-m deep snow profiles from southwest Greenland (Camp Raven, 66.48 N, 46.30 W, 2331 m asl) during Spring 2024. The snow SSA measurements were made adjacent to an autonomous atmospheric and glaciological platform (the SLEIGH) as part of the ICECAPS-MELT (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation - MEasurements along Lagrangian Transects) experiment.\r\n\r\nThis work was US-led, US-UK collaboration co-funded by the US National Science Foundation and the UK National Environment Research Council."
            },
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        {
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            "dataPath": "/neodc/esacci/land_surface_temperature/data/MULTISENSOR_IRMGP/L3S/0.05/v3.00/daily/",
            "numberOfFiles": 58239,
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            "observation": {
                "ob_id": 44677,
                "uuid": "6ab837fc79e4487a9930a221b294df01",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): 3-Hourly Multisensor Infra-Red (IR) Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) land surface temperature (LST) level 3 supercollated (L3S) global product, version 3.00",
                "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, Japanese Advanced Meteorological Imager (JAMI) on Multifunctional Transport Satellite MTSAT) 1 and MTSAT 2, Advanced Himawari Imager (AHI) on Himawari 8 and Himawari 9 ; and polar, Moderate-resolution Imaging Spectroradiometer (MODIS) on Earth Observation System (EOS) - Aqua and EOS - Terra, Along-Track Scanning Radiometer 2 (ATSR-2) on European Remote-sensing Satellite 2 (ERS-2), Advanced Along-Track Scanning Radiometer (AATSR) on Environmental Satellite (Envisat), Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and Sentinel-3B, Advanced Very High Resolution Radiometer (AVHRR) on Metop-A, and Visible Infra-red Imaging Radiometer Suite(VIIRS) on Suomi National Polar-orbiting Partnership (Suomi NPP) . 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 24th January 2004 and ends on 31st December 2023.\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\nThis version of the dataset (Version 3.00) extends the temporal coverage to the end of 2023. An extension of the dataset to the end of 2024 is planned in the future.\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."
            },
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        {
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            "observation": {
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                "uuid": "cd037a9ea387438fabf4d674dbe53088",
                "short_code": "ob",
                "title": "Mars Analysis Correction Data Assimilation (MACDA): Atmospheric and surface fields produced from assimilated MGS/TES, ODY/THEMIS, and MRO/MCS observations, v2.0",
                "abstract": "This dataset contains 268 files of basic gridded atmospheric and surface data for the planet Mars, each covering a period of 30 sols (Martian mean solar days). The fields are produced by assimilating retrieved atmospheric quantities using the Analysis Correction (AC) scheme in the UK spectral version (Oxford University and The Open University) of the Mars Planetary Climate Model (Mars-PCM), which is maintained by the Laboratoire de Météorologie Dynamique at Sorbonne Université in Paris, France. \r\n\r\nObservations are taken from the Mars Global Surveyor/Thermal Emission Spectrometer (MGS/TES), the Mars Odyssey/Thermal Emission Imaging System (ODY/THEMIS), and the Mars Reconnaissance Orbiter/Mars Climate Sounder (MRO/MCS) instruments. Assimilated MGS/TES retrievals include nadir thermal profiles below approximately 40 km altitude and column dust optical depth values. Assimilated ODY/THEMIS retrievals include column dust optical depth values. Assimilated MRO/MCS retrievals include limb thermal profiles and dust extinction profiles below approximately 80 km altitude, as well as estimates of column dust optical depth values.\r\n\r\nThe dataset covers 12 Martian years (MY), from MY 24 through MY 35 (i.e. from July 1998 through February 2021). Each file contains 30 sols, and each sol contains variables at 12 times. TES, THEMIS, and MCS retrievals are assimilated separately, with no overlap. Several 30-sol periods at the beginning of MY 24 contain no available observations; in these cases the model is run with no assimilation (free run).\r\n\r\nThe file name and the \"assimilation_run_type\" global attribute indicate which observing system is assimilated in each file: MGS/TES, ODY/THEMIS, MRO/MCS, MRO/MCS_nodust (only thermal profiles, no dust extinction profiles nor column dust optical depth values), MRO/MCS_nodustprof (only thermal profiles and column dust optical depth values, no dust extinction profiles), or free-run (i.e. no assimilated observations because retrievals are not available)."
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        {
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            "short_code": "result",
            "curationCategory": "A",
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                "uuid": "3f19f0cea1588c25c948db5effc68893",
                "short_code": "ob",
                "title": "ARA Grob G520T Egrett aircraft flight summary for the CWVC EMERALD campaign",
                "abstract": "The EMERALD projects were airborne measurement campaigns designed to study dynamical, microphysical and infra-red radiative properties of cirrus clouds, using both in-situ and remote measurement techniques. The dataset contains static air temperature, static air pressure, relative humidity, water vapour mixing ratio, and ozone mixing ratio. These data are part of the NERC Clouds, Water Vapour and Climate (CWVC) programme."
            },
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        {
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            "observation": {
                "ob_id": 45247,
                "uuid": "90eafa3b5e4043ff823c130323757631",
                "short_code": "ob",
                "title": "High-Resolution Airborne Light Detection and Ranging (LiDAR) Scans of the Bristol Channel and Severn Estuary, UK (April - June 2023).",
                "abstract": "This dataset contains high-resolution water surface elevation (WSE) measurements from five airborne LiDAR surveys of an estuarine system conducted between April and June 2023. The surveys were strategically timed to coincide with Surface Water and Ocean Topography (SWOT) satellite overpasses and captured a comprehensive range of tidal conditions, spanning from - 5.1 m to + 5.4 m relative to the EGM2008 geoid during both flood and ebb tides. Two Leica LiDAR systems were deployed: the Hyperon system for three longitudinal flights (May 16, June 24, June 29) covering 55 km along the estuary axis, and the T500 system for two cross-estuary flights (April 7, 25) spanning 35 km perpendicular to the main channel. Each survey was flown at approximately 3 km altitude with a ~ 1 km swath width, achieving point densities of 4 - 10 points/m² and WSE accuracy of ~ 0.1 m resolution. Flight durations were up to 20 minutes per survey. These measurements provide critical validation and calibration data for satellite-based WSE observations in tidally influenced coastal environments, supporting improved understanding of estuarine hydrodynamics and remote sensing validation efforts. This dataset was collected under the Surface Water and Ocean Topography (SWOT) mission (https://noc.ac.uk/projects/swot-uk) and was funded by the UK Natural Environment Research Council and the UK Space Agency (NE/V009168/1)."
            },
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        {
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            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2026/black_and_bloom_greenland_particulates",
            "numberOfFiles": 23,
            "volume": 76071917,
            "fileFormat": "BADC-CSV",
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            "observation": {
                "ob_id": 44625,
                "uuid": "749bd99f286248a1a0a21f26cd30e2ee",
                "short_code": "ob",
                "title": "Atmospheric aerosols and meteorological observations for the Black and Bloom project.",
                "abstract": "In situ observations of atmospheric aerosols (optical particle counter) and basic meteorological parameters collected during two seasons on the Greenland Ice sheet for the Black and Bloom project.\r\nBlack and Bloom is a research project, funded by the UK Natural Environment Research Council (NERC), that aims to unravel how dark particles (black) and microbial processes (bloom) darken and accelerate the melting of the Greenland Ice Sheet.  The data has been collected during two distinct field seasons (July 12 – August 18, 2016 and June 1 – 28, 2017). During this time there were instrument outages and also the aerosol samplers were turned off during helicopter activity.\r\nThese particulate measurements were used to estimate deposition velocities.\r\nOffline DNA (OTU) analysis are included from air samples collected during the campaigns as well as Scanning Electron Microscope (SEM) particle size analysis.\r\nIn addition (in a seperate folder), ten-day  particle dispersion calculations made using the FLEXPART model initiated from the ground site (67.07° N, 49.38° W 1073 m Above Mean Sea Level)"
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        {
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            "uuid": "cda3438997994ff8bd772f682e277d4c",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/badc/deposited2026/Vietnam_Two_Cities/",
            "numberOfFiles": 2,
            "volume": 2035001,
            "fileFormat": "BADC-CSV",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 45251,
                "uuid": "c4e5b5939c3240fb823896cefadbfe75",
                "short_code": "ob",
                "title": "Nitrous oxide and carbon monoxide measurements from Ho Chi Minh City, Vietnam 2018-2019",
                "abstract": "Continuous in situ mole fractions measurements of nitrous oxide and carbon monoxide from instruments located on the roof of an 11-storey building (∼40m) at the Vietnam National University HCMC, University of Science campus in Ho Chi Minh City, Vietnam (10.7625°N, 106.6823°E).  These measurements were taken between October 2018 to March 2019 as part of the Two City study of Air Quality in Vietnam project NE/P014771/1."
            },
            "onlineresource_set": []
        },
        {
            "ob_id": 45260,
            "uuid": "e2305a16bcf04264bc41680e57099e6a",
            "short_code": "result",
            "curationCategory": "A",
            "dataPath": "/neodc/esacci/land_surface_temperature/data/NOAA15_AVHRR/L3C/0.05/v1.50/daily/",
            "numberOfFiles": 8085,
            "volume": 489582821250,
            "fileFormat": "Data are in NetCDF format",
            "storageStatus": "online",
            "storageLocation": "internal",
            "oldDataPath": [],
            "observation": {
                "ob_id": 44688,
                "uuid": "d1929f1241e24d3cade8e933ed1f1ff8",
                "short_code": "ob",
                "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Daily land surface temperature from AVHRR-3 (Advanced Very High Resolution Radiometer-3) on NOAA-15  (National Oceanic and Atmospheric Administration), level 3 collated (L3C) global product (1998-2010), version 1.50",
                "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Advanced Very High Resolution Radiometer-3 (AVHRR-3) on NOAA-15. 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\nSeparate files are provided for temperatures retrieved from descending and ascending orbits. Descending and ascending equator crossing times were originally 07:30 and 19:30 local solar time but have been allowed to drift.\r\nThis product includes a time correction which can be added to the observed LST to correct to a consistent overpass 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. 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 0.05° longitude and 0.05° latitude. AVHRR achieves full Earth coverage twice per day. 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 September 1998 and continues to 3rd July 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 a two channel Generalised Split Window retrieval algorithm and data were processed in the UoL processing chain."
            },
            "onlineresource_set": []
        },
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                "abstract": "This record contains data for the piClim-370-AFR126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using CanESM5-1. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-AFR126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over Africa and the Middle East are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. Africa and the Middle East is the region bounded by 20W, 60E, 35S, and 35N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nCanESM5-1: The Canadian Earth System Model version 5.1\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "abstract": "This record contains data for the piClim-370-AFR126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using MIROC6. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-AFR126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over Africa and the Middle East are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. Africa and the Middle East is the region bounded by 20W, 60E, 35S, and 35N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nMIROC6: The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community.\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "abstract": "This record contains data for the piClim-370-SAS126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using MIROC6. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-SAS126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over South Asia are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. South Asia is the region bounded by 65 and 95E and 5 and 35N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nMIROC6: The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community.\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "abstract": "This record contains data for the piClim-370-EAS126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using MIROC6. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-EAS126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over East Asia are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. East Asia is the region bounded by 95 and 133E and 20 and 53N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nMIROC6: The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community.\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "abstract": "This record contains data for the SSP370-ASIA126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using MIROC6. It contains NetCDF output from coupled transient simulations with global aerosol reductions. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe SSP370-ASIA126aer coupled transient experiment from January 2015 to at least February 2051. Aerosol and precursor emissions (sulphur dioxide, black carbon and organic carbon) over Asia are taken from SSP1-2.6, while all other anthropogenic emissions and land use follow SSP3-7.0. Asia is comprised of East Asia (the region bounded by 95 and 133E and 20 and 53N) and South Asia (the region bounded by 65 and 95E and 5 and 35N). \r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nMIROC6: The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community.\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers."
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                "title": "SSP370-SAF126ca data produced by the MIROC6 model for the Regional Aerosol Model Intercomparison Project (RAMIP)",
                "abstract": "This record contains data for the SSP370-SAF126ca experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using MIROC6. It contains NetCDF output from coupled transient simulations with global aerosol reductions. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe SSP370-SAF126ca coupled transient experiment from January 2015 to at least February 2051. Carbonaceous aerosol emissions (black carbon and organic carbon) over sub-Saharan Africa are taken from SSP1-2.6, while all other anthropogenic emissions and land use follow SSP3-7.0. Sub-Saharan Africa is the region bounded by 20W and 50E and 35S and 12N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nMIROC6: The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community.\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers."
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                "title": "piClim-370 data produced by the UKESM1-0-LL model for the Regional Aerosol Model Intercomparison Project (RAMIP)",
                "abstract": "This record contains data for the piClim-370 experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using UKESM1-0-LL. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370 experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Global anthropogenic forcing is taken from year 2050 of the ScenarioMIP SSP3-7.0 experiment. At least 30 years are requested.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nUKESM1: the United Kingdom Earth System Model UKESM1\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "title": "piClim-370-126aer data produced by the UKESM1-0-LL model for the Regional Aerosol Model Intercomparison Project (RAMIP)",
                "abstract": "This record contains data for the piClim-370-126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using UKESM1-0-LL. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Global aerosol and precursor emissions (sulphur dioxide, black carbon and organic carbon) are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nUKESM1: the United Kingdom Earth System Model UKESM1\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "short_code": "ob",
                "title": "piClim-370-NAE126aer data produced by the UKESM1-0-LL model for the Regional Aerosol Model Intercomparison Project (RAMIP)",
                "abstract": "This record contains data for the piClim-370-NAE126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using UKESM1-0-LL. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-NAE126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over North America and Europe are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. North America and Europe are the regions bounded by 20W, 45E, 35N, and 70N, and 150W, 45W, 25N and 70N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nUKESM1: the United Kingdom Earth System Model UKESM1\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "ob_id": 45360,
                "uuid": "e22ee9b0948d49f38001105e54964994",
                "short_code": "ob",
                "title": "piClim-370-EAS126aer data produced by the UKESM1-0-LL model for the Regional Aerosol Model Intercomparison Project (RAMIP)",
                "abstract": "This record contains data for the piClim-370-EAS126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using UKESM1-0-LL. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-EAS126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over East Asia are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. East Asia is the region bounded by 95 and 133E and 20 and 53N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nUKESM1: the United Kingdom Earth System Model UKESM1\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "short_code": "ob",
                "title": "piClim-370-SAS126aer data produced by the UKESM1-0-LL model for the Regional Aerosol Model Intercomparison Project (RAMIP)",
                "abstract": "This record contains data for the piClim-370-SAS126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using UKESM1-0-LL. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-SAS126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over South Asia are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. South Asia is the region bounded by 65 and 95E and 5 and 35N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nUKESM1: the United Kingdom Earth System Model UKESM1\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "ob_id": 45364,
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                "short_code": "ob",
                "title": "piClim-370-AFR126aer data produced by the UKESM1-0-LL model for the Regional Aerosol Model Intercomparison Project (RAMIP)",
                "abstract": "This record contains data for the piClim-370-AFR126aer experiment simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using UKESM1-0-LL. It contains NetCDF output for a set of experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe piClim-370-AFR126aer experiment is a fixed sea surface temperature (SST) experiment with 1850 SSTs and sea ice concentrations, following the RFMIP piClim experiment designs. Aerosol and precursor emissions (SO2, black carbon and organic carbon) over Africa and the Middle East are taken from year 2050 of SSP1-2.6, while all other anthropogenic emissions and land use are taken from SSP3-7.0 At least 30 years are requested. Africa and the Middle East is the region bounded by 20W, 60E, 35S, and 35N.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nUKESM1: the United Kingdom Earth System Model UKESM1\r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.\r\nRFMIP: The Radiative Forcing Model Intercomparison Project."
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                "abstract": "The Central England Temperature (HadCET) monthly series start in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe monthly temperature series are derived as the mean of the daily temperature series values.\r\n \r\nFor mean temperature, the monthly values from 1659 to 1771 are derived directly from Gordon Manley's monthly mean values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html).\r\n\r\nThe version controlled CET series is updated annually (February-March), with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.\r\n\r\nThe CET datasets employ the following version control protocol: \r\n\r\nVersion Vx.y.z.a:\r\n• x – major changes – e.g. change in scientific methodology\r\n• y – minor changes – e.g. small bug fixes or updates to diagnostics pages\r\n• z – incremental changes\r\n• a – reserved for use internally\r\n\r\nThe standard annual release cycle of CET will constitute an incremental release (z). However, if more substantial\r\nchanges have been made to the codebase, scientific methodology or source data values, then this may warrant a minor (y) or major (x) version release. (Note, these are applied to a cohort of datasets together - i.e. apply to the seasonal, monthly, daily and adjustment datasets as a coordinated version release).\r\n\r\nThis new version of the datasets supersedes the previous version."
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                "abstract": "The Central England Temperature (HadCET) daily mean series is anchored to Gordon Manley’s original temperature record prior to 1973. Between 1848 and 1878, adjustments are applied to account for periods when only a single station was in use.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nFrom 1973 onwards, multiple adjustments ensure continuity with Manley’s series, homogenise the current station selection with Manley’s original dataset, and correct for the effects of increasing urbanisation.\r\n \r\nThese static adjustments are calculated on a monthly basis and are applied uniformly to all daily values within each month from 1973 to the present. \r\n \r\nUrbanisation adjustments remain static from November 2004 onward, while adjustments between 1974 and October 2004 are graded to reflect a progressive increase in urbanisation effects over time.\r\n \r\nThis dataset contains the post-Manley extended adjustments, station homogenisation adjustments, and static urban corrections.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n\r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html).\r\n\r\nThe version controlled CET series is updated annually (February-March), with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.\r\n\r\nThe CET datasets employ the following version control protocol: \r\n\r\nVersion Vx.y.z.a:\r\n• x – major changes – e.g. change in scientific methodology\r\n• y – minor changes – e.g. small bug fixes or updates to diagnostics pages\r\n• z – incremental changes\r\n• a – reserved for use internally\r\n\r\nThe standard annual release cycle of CET will constitute an incremental release (z). However, if more substantial\r\nchanges have been made to the codebase, scientific methodology or source data values, then this may warrant a minor (y) or major (x) version release. (Note, these are applied to a cohort of datasets together - i.e. apply to the seasonal, monthly, daily and adjustment datasets as a coordinated version release).\r\n\r\nThis new version of the datasets supersedes the previous version."
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                "title": "Seasonal Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.1.1.0",
                "abstract": "The Central England Temperature (HadCET) seasonal series starts in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe seasonal temperature series are derived as the mean of the monthly temperature series values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html).\r\n\r\nThe version controlled CET series is updated annually (February-March), with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.\r\n\r\nThe CET datasets employ the following version control protocol: \r\n\r\nVersion Vx.y.z.a:\r\n• x – major changes – e.g. change in scientific methodology\r\n• y – minor changes – e.g. small bug fixes or updates to diagnostics pages\r\n• z – incremental changes\r\n• a – reserved for use internally\r\n\r\nThe standard annual release cycle of CET will constitute an incremental release (z). However, if more substantial\r\nchanges have been made to the codebase, scientific methodology or source data values, then this may warrant a minor (y) or major (x) version release. (Note, these are applied to a cohort of datasets together - i.e. apply to the seasonal, monthly, daily and adjustment datasets as a coordinated version release).\r\n\r\nThis new version of the datasets supersedes the previous version."
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                "short_code": "ob",
                "title": "FAAM C440 TEAMxUK flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for TEAMxUK project."
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            "short_code": "result",
            "curationCategory": "A",
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                "uuid": "f43b8a5a9c1f4665be59125c7229eb4d",
                "short_code": "ob",
                "title": "FAAM C441 TEAMxUK flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for TEAMxUK project."
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                "short_code": "ob",
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                "short_code": "ob",
                "title": "FAAM C398 Instrument Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
                "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument) project."
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                "short_code": "ob",
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                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for VERIFY FAAM Aircraft Project project."
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                "short_code": "ob",
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                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for VERIFY FAAM Aircraft Project project."
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            "storageStatus": "online",
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                "short_code": "ob",
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                "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for VERIFY FAAM Aircraft Project project."
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                "uuid": "07ca8e4bb6c840fa9aaab7f2606b68f4",
                "short_code": "ob",
                "title": "FAAM C402 VERIFY flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
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}