Procedure Computation List
Get a list of ProcedureComputation objects. ProcedureComputations have a 1:1 mapping with Observations.
### Available end points:
- `/ProcedureComputations/` - Will list all ProcedureComputations in the database
- `/ProcedureComputations.json` - Will return all ProcedureComputations in json format
- `/ProcedureComputations/<object_id>/` - Returns ProcedureComputations object with that id
### Available Methods:
- `GET`
- `HEAD`
### Available filters:
- `uuid`
- `title`
- `keywords`
- `abstract`
### How to use filters:
These filters can be used like django query filters using __ for related model relationships.
- `/computations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/computations/?title__startswith!=DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE`
- `/computations/?abstract__contains=HadCM3 model`
GET /api/v2/computations/?format=api&offset=300
{ "count": 3949, "next": "https://api.catalogue.ceda.ac.uk/api/v2/computations/?format=api&limit=100&offset=400", "previous": "https://api.catalogue.ceda.ac.uk/api/v2/computations/?format=api&limit=100&offset=200", "results": [ { "ob_id": 11737, "uuid": "1d4e7fd6e30b39ee7b996db69560884d", "title": "ipsl-cm4 deployed on unknown computer", "abstract": "This computation involved: ipsl-cm4. \n\nEmpty content", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7718/?format=api" ] }, { "ob_id": 11738, "uuid": "0c0bc25791002879bf3a08e976e243df", "title": "hadcrut4 data processing deployed on unknown computer", "abstract": "This computation involved: hadcrut4 data processing. The gridded data are a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record given current understanding of non-climatic factors affecting near-surface temperature observations. This ensemble approach allows characterisation of spatially and temporally correlated uncertainty structure in the gridded data, for example arising from uncertainties in methods used to account for changes in SST measurement practices, homogenisation of land station records and the potential impacts of urbanisation.\n\nThe HadCRUT4 data are neither interpolated nor variance adjusted\n\nEmpty content", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7719/?format=api" ] }, { "ob_id": 11739, "uuid": "5e85fd62a49c1a728593d8f4a6036de8", "title": "ncare-ccsm30 deployed on unknown computer", "abstract": "This computation involved: ncare-ccsm30. \n\nEmpty content", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7720/?format=api" ] }, { "ob_id": 11740, "uuid": "69a7d10dc79ef966bb3695645a8d11b8", "title": "hadcrut3 data processing deployed on unknown computer", "abstract": "This computation involved: hadcrut3 data processing.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7721/?format=api" ] }, { "ob_id": 11741, "uuid": "d163a65490620b392c36d974243360cf", "title": "Forecast trajectories deployed on unknown computer", "abstract": "This computation involved: Forecast trajectories.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7722/?format=api" ] }, { "ob_id": 11742, "uuid": "51bc98d05b15423e16c9391e90cca73d", "title": "GFDL deployed on unknown computer", "abstract": "This computation involved: GFDL.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7723/?format=api" ] }, { "ob_id": 11743, "uuid": "3eeea3634d12f3ccba37aa849149867b", "title": "MOM deployed on unknown computer", "abstract": "This computation involved: MOM.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7724/?format=api" ] }, { "ob_id": 11744, "uuid": "9164e82c265d56f62f4e8279929168d9", "title": "Trajectories deployed on unknown computer", "abstract": "This computation involved: Trajectories.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7725/?format=api" ] }, { "ob_id": 11757, "uuid": "601c6d224b86d83b26abd4d63e68b177", "title": "Back Trajectories deployed on unknown computer", "abstract": "This computation involved: Back Trajectories.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7740/?format=api" ] }, { "ob_id": 11851, "uuid": "6ac043426bdc38fe71fb1feccf8a7843", "title": "Master Chemical Mechanism Short lived species model deployed on unknown computer", "abstract": "This computation involved: Master Chemical Mechanism Short lived species model.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7915/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7916/?format=api" ] }, { "ob_id": 11852, "uuid": "1e9788d8e8d8a151ac79100dedbdc9b0", "title": "Master Chemical Mechanism Long lived species Model deployed on unknown computer", "abstract": "This computation involved: Master Chemical Mechanism Long lived species Model.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7917/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7918/?format=api" ] }, { "ob_id": 11864, "uuid": "87309b898ea35dc50fcf5ff251d0d566", "title": "HadCEM deployed on unknown computer", "abstract": "This computation involved: HadCEM.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7934/?format=api" ] }, { "ob_id": 11865, "uuid": "3fffd5357c29ee313189e2314c1d289d", "title": "C-Goldstein deployed on unknown computer", "abstract": "This computation involved: C-Goldstein.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7935/?format=api" ] }, { "ob_id": 11867, "uuid": "4c917996ebfdaf4a1b628d4b12a35952", "title": "CIRA-86 Model deployed on unknown computer", "abstract": "This computation involved: CIRA-86 Model. A global climatology of atmospheric temperature, zonal velocity and geopotential height derived from a combination of satellite, radiosonde and ground-based measurements. The reference atmosphere extends from pole to pole and 0-120 km. The majority of the data are on a 5 degree latitude grid and approximately 2 km vertical resolution.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7938/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7939/?format=api" ] }, { "ob_id": 11874, "uuid": "fdc64527455647f7b280c879635fcfa3", "title": "Cambridge: Trajectory Model deployed on unknown computer", "abstract": "This computation involved: Cambridge: Trajectory Model.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7949/?format=api" ] }, { "ob_id": 11876, "uuid": "4dcabe9b70db4ed8b9e3460767d7068b", "title": "Hadley Centre Global Environmental Model version 1a (HadGEM1a) deployed on unknown computer", "abstract": "This computation involved: Hadley Centre Global Environmental Model version 1a (HadGEM1a). The HadGEM1a model builds on the IPCC AR4 version of HadGEM1 and includes various small improvements to the science and fixing of known problems.\n\nThe main advances from HadGEM1 are 1) Improved tropical biases and ENSO 2) Reduced continental warm dry bias 3) Improved aerosols", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7954/?format=api" ] }, { "ob_id": 11877, "uuid": "27e04bb8bbc2438591a99bfdc7b586c6", "title": "HOPE-G Hamburg Ocean Primitive Equation Model (Global Version) deployed on unknown computer", "abstract": "This computation involved: HOPE-G Hamburg Ocean Primitive Equation Model (Global Version).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7955/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7956/?format=api" ] }, { "ob_id": 11878, "uuid": "693339bec032443c9bab373200ac5145", "title": "FRUGAL deployed on unknown computer", "abstract": "This computation involved: FRUGAL.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7957/?format=api" ] }, { "ob_id": 11879, "uuid": "56fe8560851c4632839a157de9b15022", "title": "GENIE deployed on unknown computer", "abstract": "This computation involved: GENIE.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7958/?format=api" ] }, { "ob_id": 11891, "uuid": "8a4290168f744e95ab71309e911f3763", "title": "3-component model of Phytoplankton size class deployed on unknown computer", "abstract": "This computation involved: 3-component model of Phytoplankton size class. \n\nEmpty content", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7980/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7981/?format=api" ] }, { "ob_id": 11900, "uuid": "0d396f07d506465baaea81d7d0f992b7", "title": "DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on ERS-2", "abstract": "This computation involved: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on ERS-2. \n\nMetadata document", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11905, "uuid": "af975fa44f9f4354b83278e480dbf35f", "title": "DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on MSG", "abstract": "This computation involved: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on MSG. \n\nMetadata document", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11917, "uuid": "7d280ef1e09844ff9e78424507d3c303", "title": "Computation Process for: DUMMY OB TITLE - FOR: OBS_fd06b0ba-1c54-11e2-aaef-00163e251233", "abstract": "This computation involved: deployed on National Energy Research Scientific Computing Center's Cray XE6 'Hopper' system. The National Energy Research Scientific Computing Center (NERSC) is the primary scientific computing facility for the Office of Science in the U.S. Department of Energy. One of the main parallel systems that they make available for research use is the Centre's Cray XE6 'Hopper' system, with a peak theoretical performance of 1.29 Petaflop/s.\n\n<div property=\"cedacat:introduction\">\n<div class=\"introduction\">Introduction</div>\n<p>The National Energy Research Scientific Computing Center's (NERSC) 'Hopper' Cray XE6 system has a peak performance of 1.28 Petaflops/sec, 153,216 compute cores for running scientific applications, 217 Terabytes of memory and 2 Petabytes of online disk storage.</p>\n</div>", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8013/?format=api" ] }, { "ob_id": 11923, "uuid": "a553acf6dfd148c4ab29fdf6bb71c7b6", "title": "DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on MLS", "abstract": "This computation involved: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on MLS.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11929, "uuid": "0694d430e9c14dd0adfca50a3cbc79b8", "title": "DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on SAM II", "abstract": "This computation involved: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on SAM II.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11941, "uuid": "2691a50252fd45cc969c40693f3494d6", "title": "Computation Process for: DUMMY OB TITLE - FOR: obs_11665284833911895", "abstract": "This computation involved: deployed on CEH Beowulf Cluster.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8028/?format=api" ] }, { "ob_id": 11952, "uuid": "96183d068eae4db7ba11da56fefb007d", "title": "DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on Landsat3", "abstract": "This computation involved: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on Landsat3. Landsat3 is a polar orbiting platform onboard which the Multispectral Scanner (MSS) Instrument.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11958, "uuid": "1619ef54da6842edb146dbce083265d7", "title": "DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on Landsat2", "abstract": "This computation involved: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on Landsat2. Landsat2 was a polar orbiting platform onboard which is mounted the Multispectral Scanner (MSS) Instrument.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11964, "uuid": "38681a00945747c58258d05ce37afc28", "title": "DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on Landsat1", "abstract": "This computation involved: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on Landsat1.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12150, "uuid": "57fc8de25a424b21a311bca687d9c720", "title": "Met Office Cyclone Data Base Methodology", "abstract": "Please refer to the linked documentation by Tim Hewson regarding the cyclone database and algorithms used to construct this dataset. The document refers to work expanding on and improving that covered by Hewson, T.D., 1998. ‘A Frontal Wave Database’. JCMM Internal Report No. 85. pp 20. Department of meteorology,\r\nReading university.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12153, "uuid": "677a341f41494279ad0abf8f53a43b04", "title": "KNMI Penman-Monteith parameterization deployed on KNMI computer system based on the CRU TS data sets", "abstract": "For details about the computation of scPDSI, please refer to van der Schrier et al. (2013) - see link below.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12207, "uuid": "48028ae006e0444fbdfb5bbf8d04ec33", "title": "UEA Climatic Research Unit (CRU) CRUTEM gridding software deployed on UEA Climatic Research Unit (CRU) computer system", "abstract": "For details about the construction of the CRUTEM dataset, please refer to:\r\n\r\nOsborn, T.J. and Jones, P.D., 2014: The CRUTEM4 land-surface air temperature data set: construction, previous versions and dissemination via Google Earth. Earth System Science Data 6, 61-68, doi:10.5194/essd-6-61-2014", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12262, "uuid": "179889034c1142118bc57cf357640015", "title": "HadGEM3-ES", "abstract": "Hadley Centre Global Environment Model version 3 Earth System simulations deployed on Met Office Hadley Centre computers", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12263, "uuid": "274cba2cd5654e569e85c477e7693f48", "title": "SOCOL3", "abstract": "The third generation of the coupled chemistry-climate model SOCOL (modeling tools for studies of SOlar Climate Ozone Links)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12270, "uuid": "c7808e7c0a0644359ae90e543686bcee", "title": "Procedure used to derive vegetation height frequency distributions from the ICESAT Geoscience Laser Altitmeter System (GLAS) dataset", "abstract": "Vegetation height is derived from the ICESAT Geoscience Laser Altitmeter System (GLAS) waveform data from the GLA14 product release 31. This product contains the decomposition of waveforms in up to 6 Gaussians. Height is estimated from the difference between the first return, indicative of the top of the vegetation canopy or object, and the ground return. Ground return is estimated from the lowest of the two gaussians. The Gaussian with maximum amplitude of the last two Gaussians is thought to represent the ground return (Rosette et al. 2008). \r\n\r\nSpurious data were eliminated by applying a set of filters. Filters test for slope, difference in elevation between the wave form and the ground (indicative of clouds) and signal strength. An adjustment is applied for the shape of the last Gaussian. Further details can be found in Los et al 2012.\r\n", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12282, "uuid": "ef3f92c0b2ce467ab4f0567a207cb34d", "title": "GEOSCCM", "abstract": "The Goddard chemistry climate model, GEOSCCM, is based on the NASA/GMAO general circulation model integrated with various chemical packages.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12296, "uuid": "29e400ee2dbe4a57bd546f0bd2f9df72", "title": "Production of MSLP charts from the Met Office's SWIFT system", "abstract": "Mean Sea-level pressure (MSLP) charts are produced routinely from the Met Office's forecasting system via the Met Office's SWIFT system using VisualWeather.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12320, "uuid": "a83b5cfca79a48599c002dfbb3de858e", "title": "Level 1 processing algorithm applied to Sentinel 1 raw data, Instrument Processing Facility (IPF) v3", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Synthetic Aperture Radar (SAR) data. This consists of Level 1 preprocessing, special handling for TOPSAR mode, Doppler centroid estimation, Level 1 Single Look Complex (SLC) processing algorithms and Level 1 post-processing to generate the output Single Look Complex (SLC) and Ground Range Detected (GRD) products as well as quicklook images. \r\n\r\nLevel-1 Single Look Complex (SLC) products consist of focused SAR data, geo-referenced using orbit and attitude data from the satellite, and provided in slant-range geometry. Slant range is the natural radar range observation coordinate, defined as the line-of-sight from the radar to each reflecting object. The products are in zero-Doppler orientation where each row of pixels represents points along a line perpendicular to the sub-satellite track.\r\n\r\nThe products include a single look in each dimension using the full available signal bandwidth and complex samples (real and imaginary) preserving the phase information. The products have been geo-referenced using the orbit and attitude data from the satellite and have been corrected for azimuth bi-static delay, elevation antenna pattern and range spreading loss.\r\n\r\nFor more information on the changes for this processing version please see the Sentinel 1 document libary under the docs tab.", "keywords": "Synthetic Aperture Radar, Sentinel 1, Level 1, algorithm, SAR", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12431, "uuid": "b954472159724d5598aeae89d9d32f68", "title": "Deployed on Landsat 8.", "abstract": "Deployed on Landsat 8.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 12897, "uuid": "364a37c33f254bffbc51f3af640f4662", "title": "Preprocessing of raw data", "abstract": "Preprocessing of raw data from the Chilbolton 40 GHz ALPHASAT beacon receiver", "keywords": "ESA, ALPHASAT", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13153, "uuid": "b276e7826a0f4e77bebc6d2d4ca09619", "title": "ECMWF reanalysis output for the ISLSCP-I project", "abstract": "The ECMWF, and ECMWF, NASA/LaRC data on the ISLSCP Initiative I CD-ROM are comprised of the ECMWF/TOGA Advanced Operational Analysis Data the ECMWF/TOGA Supplementary Fields data and a hybrid dataset using the radiation fields within the ECMWF/TOGA Supplementary Fields and the NASA/LaRC Surface Shortwave and Longwave Radiation Fluxes data set.\r\n\r\nECMWF/TOGA Advanced Operational Analysis Data Sets:\r\n\r\nThis dataset contains uninitialized analysis values at the resolution of the data assimilation system in operational use at ECMWF. The Advanced Operational Analysis Data Set, on the ISLSCP Initiative 1 CD-ROM, are comprised only of the Surface and Diagnostic Fields.\r\n\r\nThe original ECMWF Surface and Diagnostic Fields data set was represented on a 320 x 160 grid, with a regular spacing of 1.125 degrees (lat/long) between points along each row for the period January 1, 1987 - December 31, 1988. Grid point values were stored in latitude rows starting at the north and working southwards; within each row values ran from west to east, starting at the 0 degree longitude. All of the ECMWF Surface and Diagnostic Fields Data sets, on the ISLSCP CD-ROM, have been converted, by the Goddard DAAC, to a 1 X 1 degree equal angle lat/long grid, starting at 90 degrees latitude North and 180 degrees longitude West (see section 9.3.1).\r\n\r\nThe Parameters from the Surface and Diagnostic Fields data set, on the ISLSCP Initiative I CD-ROM set, are:\r\n\r\nSurface Fields - surface pressure, surface temperature, soil moisture, snow depth, mean sea level pressure, u- and v-components of wind at 10m, temperature at 2m, dew point temperature at 2m, deep-soil wetness, deep-soil temperature.\r\n\r\nDiagnostic Fields - surface roughness, albedo, climate deep-soil wetness, climate deep-soil temperature.\r\n\r\nECMWF/TOGA Supplementary Fields Data Set:\r\n\r\nThe Supplementary Fields Data Set contains surface heat fluxes, net radiation and u- v-stress derived from 6-hour forecasts used as \"first-guess\" for analyses within ECMWF's data assimilation system. The Supplementary Fields Data Set acquired from ECMWF were represented in the same format, as the Surface and Diagnostic Fields Data set, described above. All ECMWF Supplementary Fields Data Sets, on the ISLSCP CD-ROM, have been converted, by the Goddard DAAC, to a 1 X 1 degree equal angle lat/long grid, starting at 90 degrees latitude North and 180 degrees longitude West (see section 9.3.1).\r\n\r\nThe Parameters from the Supplementary Fields data set, on the ISLSCP Initiative I CD-ROM set, are: surface flux of sensible heat, surface flux of latent heat, surface shortwave radiation, surface longwave radiation, top of the atmosphere shortwave radiation, top of the atmosphere longwave radiation, and the zonal and meridional components of the surface wind stress.\r\n\r\nMost of the near-surface meteorological data are taken directly from forecast products generated by the ECMWF operational numerical weather prediction model.\r\n\r\nECMWF requested that the following information be provided to users of the ECMWF data:\r\n\r\nThe ECMWF data sets are adapted to a specific model orography; the data sets have biases which are only partially documented (reference list).\r\n\r\nNo surface observations of T, q, precipitation, nor surface wind observations over land were used in the analysis.\r\n\r\nModel spin up can seriously affect the flux data. All flux fields, including total cloud cover, are first-guess fields (i.e. 6 hour forecasts).\r\n\r\nAll the time-evolving fields on this CD-ROM, such as soil moisture, snow depth and deep soil parameters include no direct observations, but evolve during the data assimilation cycle.\r\n\r\nThe Technical Attachment to the Description of the ECMWF/WCRP Archive should be cited by users in publications (see reference section).\r\n\r\nIn addition to the routine products extracted from the ECMWF archive for this data set, NASA/GSFC generated synthetic 'hybrid' 6-hourly incident surface shortwave and longwave radiation fluxes, and NOAA/NMC generated 'hybrid' 6-hourly total and convective precipitation rates. As presented on the CD-ROMs the data sets include:\r\n\r\nI. Prescribed/Diagnostic Fields (see table in section 1.3),\r\nII. Monthly (6-hourly) Forcing Fields (see table in section 1.3),\r\nIII. Diurnally-resolved (6-hourly) Forcing Fields (see table in section 1.3). (These include the hybrid products).\r\n\r\nThe data in I are intended for reference rather than direct use by modelers. The data sets in II are suitable for forcing long time-step models. The data sets in III have been put together for the express purpose of forcing energy-water-carbon land models.", "keywords": "ECMWF, ISLSCP, reanalysis", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13154, "uuid": "5141aa5b44584877ba3a7bd187ff005d", "title": "NCM GPCP precipitation reanalysis precipitation model output for the ISLSCP project", "abstract": "The objective of this dataset is to provide a global continental precipitation time series of relatively high temporal frequency. Its purpose is to fulfill the precipitation forcing needs of the various land-surface/hydrology initiatives of the Global Energy and Water Cycle Experiment (GEWEX), including ISLSCP, GCIP, GNEP, and PILPS. \r\n\r\nOne chief application is in the initiative of the GEWEX Global Soil Wetness Workshop (4-6 Oct 1994, Longmont, Colorado), which enlisted a number of international land-surface modeling groups to utilize the same global, continental atmospheric forcing data as input to various land-surface process models to generate a set of global soil wetness estimates for use in global climate models and other applications. A good discussion of the need for and approach to a global soil wetness initiative is given by Dirmeyer (1995) in his summary of a related forerunner meeting on soil wetness (COLA, 19 Aug 94, Calverton, MD).", "keywords": "NCM GPCP, ISLSCP, precipitation", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13192, "uuid": "74e36a898d694a70bc8b0412720741e3", "title": "Level 1C processing algorithm applied to Sentinel 2 raw data", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Multispectral Instrument (MSI) data. Level-1C processing includes radiometric and geometric corrections including ortho-rectification and spatial registration on a global reference system with sub-pixel accuracy. This processing produces the level 1C data as well as quicklook images for the user.", "keywords": "Multispectral Instrument, Sentinel 2, level 1C, algorithm, MSI", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13203, "uuid": "5f2c6f3844d548de8e78a14c2421ad46", "title": "ISLSCP -International Satellite Land Surface Climatology regular geo-temporal", "abstract": "The collection covers four areas : land cover, hydro-meteorology, radiation, and soils, spanning the 24 month period 1987-1988. The irregular data were taken and mapped to a common spatial resolution and grid (1 degree x 1 degree) except for one. Temporal resolution for most datasets is monthly; however, a few are at a finer resolution (e.g., 6-hourly). The data within the four areas are organized into five groups within this collection: vegetation, Hydrology and Soils, Snow, Ice and Oceans, Radiation and Clouds, and Near-Surface Meteorology.", "keywords": "ISLSCP, NASA", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13232, "uuid": "8ca38a99a1f44789b5dd09681f97dcdf", "title": "ISLSCP II: International Satellite Land Surface Climatology Project, Initiative II regular geo-temporal", "abstract": "The International Satellite Land Surface Climatology Project, Initiative II (ISLSCP II) is a follow on project from The International Satellite Land Surface Climatology Project (ISLSCP). ISLSCP II had the lead role in addressing land-atmosphere interactions - process modelling, data retrieval algorithms, field experiment design and execution, and the development of global data sets. The ISLSCP II dataset contains comprehensive data over the 10 year period from 1986 to 1995, from the International Satellite Land Surface Climatology Project (ISLSCP). The data are mapped to consistent grids (0.5 x 0.5 degrees for topography, 1 x 1 degrees for meteorological parameters). Some data have a grid size of 0.25 x 0.25 degrees. The temporal resolution for most data sets is monthly (however a few are at finer resolution - 3 hourly). This dataset is public.", "keywords": "ISLSCP II, NASA", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13239, "uuid": "7cc3121cfcd848fea28c7fbee0cd538e", "title": "Earth Observing System (EOS) Digital Elevation Model (DEM) at 30 arcsecond (~1km)", "abstract": "The files in this directory were produced by the ISLSCP2 staff based on the 30 \r\narcsecond (~1km) Earth Observing System (EOS) Digital Elevation Model (DEM) \r\nprovided by Dr. Thomas Logan from NASA/Jet Propulsion Laboratory (JPL). These \r\nare global, coarse resolution (1/4, 1/2 and 1 degree spatial resolutions) binary \r\n( 1 and 0) overlays of land/water and land/sea boundaries.\r\n\r\nThe ISLSCP2 masks are based on the best available 30 arcsecond (~1km) land/water \r\nmasks produced at JPL in support of the EOS AM-1 satellite platform. The JPL \r\nmasks are based in turn on vector data from the World Vector Shoreline (WVS) \r\ndatabase (Solluri and Woodson 1990) for coastlines, and the Digital Chart of the \r\nWorld (DCW) (Danko 1992) for inland water bodies. The WVS is based on older \r\n1:250,000 scale Defense Mapping Agency JOG (Joint Operational Graphics) charts \r\nproduced from a variety of sources. DCW is based on a photogrammetric consistent \r\nmapping at a scale of 1:1,000,000. The ISLSCP2 staff have aggregated the 1km \r\ndata to spatial resolutions of 1/4, 1/2 and 1 degree, in the process generating \r\nlayers with the percentage of land/water or land/sea cells within the coarse \r\nresolution cells. An arbitrary threshold of greater than or equal to 50% water \r\nwas used to designate water dominated cells and to produce binary land/water or \r\nland/sea masks for the data collection.", "keywords": "DEM, EOS", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13240, "uuid": "335bb953b02a4da98196580504feac0b", "title": "ECMWF reanalysis output for the ISLSCP-II project", "abstract": "The ECMWF (European Centre for Medium-range Weather Forecasts) near-surface data\r\nset for the ISLSCP Initiative II data collection has been derived from the ECMWF 40-year reanalysis,\r\nor ERA40 (Simmons and Gibson, 2000), covering the years 1957 to 2001. The purpose\r\nof ERA40 is to produce an objective analysis of the atmosphere making optimal use of a wide\r\nrange of observing systems. A recent version of the ECMWF Numerical Weather Prediction\r\nsystem (cycle 23r4) is used for the entire analysis period. The advantage of re-analysis over\r\noperational analysis is that no system changes occur that might affect the analysis products,\r\nalthough there are significant changes in the observations", "keywords": "ECMWF, ISLSCP II, reanalysis", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13241, "uuid": "01e87f78a3b34a1babef40f3271fe8ca", "title": "NCEP reanalysis output for the ISLSCP-II project", "abstract": "The analysis increment for the NCEP/DOE AMIP-II reanalysis is six hours, and output\r\ndata are routinely reported every hour or six hours. In order to satisfy the ISLSCP-II requirement\r\nfor 3-hourly data, twice daily 36 hour forecasts were made and hourly output were obtained from\r\nthe 24-36 hour forecasts. The 24-36 hour forecasts were chosen to minimize \"spin-up/spindown\"\r\nproblems. The one-hour data were later combined to produce 3-hourly data. Time\r\naveraging was performed on the native reanalysis grid. For the 3-hourly and the monthly-3-\r\nhourly data, the hour in the file name refers to the end of the 3-hour period. For example, 03Z\r\nrefers to the value at 03Z (for instantaneous data) or the average over the preceding period 00Z-\r\n03Z (for the flux fields and snow cover fraction).", "keywords": "NCEP, ISLSCP II, reanalysis", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13243, "uuid": "1e492191d0934264b76c19c41e618c28", "title": "ISLSCP II: Surface Radiation Budget and Clouds using the NASA/GEWEX SRB dataset", "abstract": "ISLSCP II: Surface Radiation Budget and Clouds using the NASA/GEWEX SRB dataset", "keywords": "NASA/GEWEX SRB dataset", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13251, "uuid": "20f1d00932ec4e3ead089be843818333", "title": "Weybourne Name Footprint atmospheric data", "abstract": "The Weybourne Atmospheric Observatory (WAO) is part of the School of Environmental Sciences at the University of East Anglia (UEA). It is situated on the north Norfolk coast and is a world class facility for fundemental research, background atmospheric monitoring and teaching purposes. WAO operates a range of instruments in its measurement programme - the data from which is archived at the BADC. The dataset contains NAME dispersion model footprints- Please notify Zoe Fleming if any of these plots will be used in presentations and publications", "keywords": "Weybourne Atmospheric Observatory, NAME Footprint", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13252, "uuid": "f7599214fcb541328306b1e45503a84e", "title": "Airborne Arctic Stratospheric Expedition II (AASE II) Project Model Output", "abstract": "MODEL data containing 12 Z hemispheric analyses of potential vorticity, temperature, horizontal winds, and radiative heating rates; and one file named MA911006.H00 which contains gas-phase chemistry model reconstructions of several radicals as a function of latitude, altitude, and local time.", "keywords": "AASE II", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13380, "uuid": "b51c6734ee934dd5aa6b45475b52bb7a", "title": "NCAR Parallel Climate Model (PCM) deployed on National Centre for Atmospheric Research (USA) computing facility", "abstract": "NCAR Parallel Climate Model (PCM) deployed on National Centre for Atmospheric Research (USA) computing facility", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13386, "uuid": "078cbdfb97254a5f82b3bd8ac8bc0ad4", "title": "INGV-SXG at Instituto Nazionale di Geofisica e Vulcanologia (INGV)", "abstract": " INGV-SXG at Instituto Nazionale di Geofisica e Vulcanologia (INGV)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13391, "uuid": "49e6741a6645410080dad9c859cc85f5", "title": "CSIRO-Mk3.5 Global Circulation Model deployed on Commonwealth Scientific and Industrial Research Organisation computing facility", "abstract": "This computation involved: CSIRO-Mk3.5 Global Circulation Model deployed on Commonwealth Scientific and Industrial Research Organisation computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13473, "uuid": "56664e66063c4fe696e377186aadde59", "title": "Envisat satellite composite (third reprocessing)", "abstract": "For the third reprocessing, the IPF Processor 6.05 (the IPF Processor 6.01 for the second version) is used. Several static and dynamic auxiliary data files are updated or introduced. This update aims for: \r\n- Improvement of SST retrievals by updating SST coefficients (SST ADF)\r\n- Implementation of improved and consistent calibration for the reflectance channels (555 nm, 660 nm, 865 nm and 1600 nm), which would correct the long term drift.\r\n- Improvement of cloud identification through updated cloud test auxiliary file (CL1 ADF).\r\n- Implementation of the new L1B characterisation file (CH1 ADF) which would improve the colocation displacement between the nadir and forward views, and the absolute geolocation accuracy.", "keywords": "third reprocessing, AATSR, Envisat", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13526, "uuid": "02d903686bc9471a866e6b0d7c19f727", "title": "HadISDH.land: gridded global land surface humidity dataset produced by the Met Office Hadley Centre", "abstract": "HadISDH.land utilises simultaneous subdaily temperature and dew point temperature data from over 3000 quality controlled HadISD stations that have sufficiently long records. All humidity variables are calculated at hourly resolution and monthly means are created. \r\n\r\nMonthly means are homogenised to detect and adjust for features within the data that do not appear to be of climate origin. While unlikely to be perfect, this process does help remove large errors from the data an improve robustness of long-term climate monitoring. The NCEI's Pairwise Homogenisation Algorithm has been used directly on DPD and T. An indirect PHA method (ID PHA) is used whereby changepoints detected in DPD and T are used to make adjustments to q, e, Tw and RH. Changepoints from DPD are also applied to T. Td is derived from homogenised T and DPD. See Docs 'HadISDH.land process diagram'.\r\n\r\nStation measurement, climatological and homogeneity adjustment uncertainties are estimated for each month. Climatological averages are calculated (the climatological period is dependent on product version) and monthly mean climate anomalies obtained. These anomalies (in addition to climatological mean and standard deviation, actual values and uncertainty components) are then averaged over 5° by 5° gridboxes centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N. Given the uneven distribution of stations over time and space, sampling uncertainty is estimated for each gridbox month.\r\n\r\nFor greater detail please see:\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nand\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.\r\n\r\nDocs contains links to both these publications", "keywords": "HadISDH, humidity, surface, land, gridded, station, specific humidity, relative humidity, temperature, dewpoint temperature, wetbulb temperature, dewpoint depression, vapour pressure, in situ, homogenisation, quality control", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13527, "uuid": "2649a2ef6070473c9acd47dfb27b3fe8", "title": "HadCRUT4: gridded dataset of global historical surface temperature anomalies produced by the Met Office Hadley Centre", "abstract": "The gridded data are near surface temperature anomalies from 1850 (relative to 1961-1990) produced as a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record given current understanding of non-climatic factors affecting near-surface temperature observations. \r\n\r\nThis ensemble approach allows characterisation of spatially and temporally correlated uncertainty structure in the gridded data, for example arising from uncertainties in methods used to account for changes in SST measurement practices, homogenisation of land station records and the potential impacts of urbanisation.\r\n\r\nThe HadCRUT4 data are neither interpolated nor variance adjusted.", "keywords": "HadCRUT4", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13549, "uuid": "d13bc917b2de43c4a018535ffa25ae5a", "title": "HadISST Sea Surface Temperature data processing deployed on Met Office Hadley Centre Computers", "abstract": "This computation involved: HadISST Sea Surface Temperature data processing deployed on Met Office Hadley Centre Computers. Processing used by the Met Office Hadley Centre to produce the HadISST dataset.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8596/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8597/?format=api" ] }, { "ob_id": 13555, "uuid": "9ece9037125640339c478a1170634bf8", "title": "Network for the Detection of Atmospheric Composition Change: Numerical Model Output from stations", "abstract": "Network for the Detection of Atmospheric Composition Change: Numerical Model Output from stations using the NMC satellite ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13610, "uuid": "92a305551fdc4ca798b75d75fdb43b2b", "title": "Computation process: African Monsoon Multidisciplinary Analysis (AMMA) Project: Centre for Ecology & Hydrology (CEH) Model", "abstract": "African Monsoon Multidisciplinary Analysis (AMMA) Project: Centre for Ecology & Hydrology (CEH) Model JULES v2.0", "keywords": "AMMA, CEH, Model", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13611, "uuid": "f5620ca7d998422996baea3765c3a796", "title": "African Monsoon Multidisciplinary Analysis (AMMA) Project: York Isoprene and monoterpenes samples", "abstract": "Isoprene and monoterpenes, samples collected on adsorption tubes and analysed by GC-TOF-MS", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13655, "uuid": "e6224de868b54aa78d56b3630133e86c", "title": "Computation process: African Monsoon Multidisciplinary Analysis (AMMA) Project: Africa Limited Area Model Output", "abstract": "Africa Limited Area Model Output", "keywords": "AMMA, Model", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13669, "uuid": "3e7f7fdc90b34fedb83bdfc1f17430d2", "title": "Level 1 processing applied to Envisat data", "abstract": "Reprocessed Level 0 data, with all supplemental information to be used in subsequent processing appended, for optional radiometric and geometric correction applied to produce parameters in physical units. Data are generally presented at full time/space resolution. ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13670, "uuid": "1a2e2023d0284494b4518bbb51d8f2c4", "title": "Level 2 processing applied to Envisat data", "abstract": "Retrieved environmental variables (e.g. ocean wave height, soil moisture, ice concentration, ozone, sea surface temperature, chlorophyll, etc.) at the same resolution and location as the Level 1 source data.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13675, "uuid": "6dfaa6f7df744b8899f74ead1caa6aff", "title": "Computation process: Bodeker Scientific vertical ozone profile", "abstract": "Monthly means are calculated from individual ozone measurements extracted from the The Binary Data Base of Profiles (BDBP), several different satellite-instruments and ozonesondes were used. These are referred to as Tier 0 data. A regression model is fitted to the Tier 0 data at each of 70 pressure/altitude levels. The regression model is of the form:\r\n\r\nOzone(t,lat) = A(t,lat) + Offset and seasonal cycle\r\n B(t,lat) x t + Linear trend\r\n C(t,lat) x EESC(t,AoA) + Age-of-air dependent equivalent effective stratospheric chlorine\r\n D(t,lat) x QBO(t) + Quasi-biennial Oscillation \r\n E(t,lat) x QBOorthog(t) + Orthogonalized QBO\r\n F(t,lat) x ENSO(t) + El-Niño Southern Oscillation \r\n G(t,lat) x Solar(t) + Solar cycle\r\n H(t,lat) x Pinatubo(t) + Mt. Pinatubo volcanic eruption\r\n R(t) Residual\r\n\r\nRegression model fit coefficients are expanded in Fourier series to account for seasonality and in Legendre polynomials in latitude to account for meridional structure in the fit coefficients. Regression model output is then used to produce 4 gap free Tier 1 data sets, viz.:\r\nTier 1.1 (Anthropogenic): This comprises the mean annual cycle plus contributions from the EESC and linear trend basis functions.\r\nTier 1.2 (Natural): This comprises the mean annual cycle plus contributions from the QBO, solar cycle and El Niño basis functions.\r\nTier 1.3 (Natural & volcanoes): Tier 1.2 but now also including contributions from volcano basis functions.\r\nTier 1.4 (All): Constructed by summing the contributions from all basis functions.", "keywords": "Ozone, regression", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13691, "uuid": "7cdbefb9a4c246c98d60cd775297bf86", "title": "Jakobshavn Glacier Velocity Maps", "abstract": "Intensity tracking, based on patch intensity cross-correlation optimization, and coherence tracking, based on patch coherence optimization, are used to estimate the movement of glacier surfaces between two SAR images in both slant-range and azimuth direction. The accuracy and application range of the two methods are examined in the case of the surge of Monacobreen in Northern Svalbard between 1992 and 1996. Offset-tracking procedures of SAR images are an alternative to differential SAR interferometry for the estimation of glacier motion when differential SAR interferometry is limited\r\nby loss of coherence, i.e., in the case of rapid and incoherent flow and of large acquisition time intervals between the two SAR images. In addition, an offset-tracking procedure in the azimuth\r\ndirection may be combined with differential SAR interferometry in the slant-range direction in order to retrieve a two-dimensional displacement map when SAR data of only one orbit configuration are available.\r\n\r\nThe velocity fields were transformed to map coordinates using the GLAS/ICESat 1 km Laser Altimetry Digital Elevation Model of Greenland.", "keywords": "Digital Elevation Model", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13694, "uuid": "edd20cdb331947628e61807fd20fb3c6", "title": "Global Phytoplankton Size Class (PSC) Monthly (Composites) Climatology from Plymouth Marine Laboratory using SeaWiFS satellite", "abstract": "A three-component model was developed which calculates the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) to the overall chlorophyll-a concentration in the Atlantic Ocean. The model is an extension of the Sathyendranath et al. (2001) approach, based on the assumption that small cells dominate at low chlorophyll-a concentrations and large cells at high chlorophyll-a concentrations. Diagnostic pigments were used to infer cell size using an established technique adapted to account for small picoeukaroytes in ultra-oligotrophic environments. Atlantic Meridional Transect (AMT) pigment data taken between 1997 and 2004 were split into two datasets; 1935 measurements were used to parameterise the model, and a further 241 surface measurements, spatially and temporally matched to chlorophyll-a derived from SeaWiFS satellite data, were set aside to validate the model. Comparison with an independent global pigment dataset (256 measurements) also supports the broader-scale application of the model. The effect of optical depth on the model parameters was also investigated and explicitly incorporated into the model. It is envisaged that future applications would include validating multi-plankton biogeochemical models and improving primary-production estimates by accounting for community composition.", "keywords": "Phytoplankton, Pigment, Size, Ocean colour, Remote sensing, Chlorophyll-a, SeaWiFS", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13695, "uuid": "01b7312738c54ddfa0a9cac3f528f658", "title": "Theme 5 (Cryosphere and Polar Oceans) Sea Ice Elevation and Thickness and Ice Sheet Elevation Change", "abstract": "To generate winter averages for each season, the data were seasonally adjusted to the 1st January using an average winter growth curve derived from the data. The seasonally adjusted data were averaged onto 100 × 100 km grid cells on a polar stereographic projection. We estimated the errors in ice thickness for each grid cell as follows: The error in the ice freeboard was calculated using equation (1) from Giles and Hvidegaard [2006], with an additional term to account for the error in the velocity of the radar signal through the snow pack. The error in the estimate of ice thickness in each grid cell was then calculated from equation (3) of Giles et al. [2007], with errors in the ice and water densities taken to be 5 kg m−3 and 0.5 kg m−3 respectively [Wadhams et al., 1992], the snow density error taken to be 3 kg m−3 [Warren et al., 1999], and snow depth error taken to be the interannual variability (IAV) in snow depth of 0.03 m from Radionov et al. [1996]. For each winter season we then calculated ice thickness anomalies for each grid cell, which contained data for all years, by removing the six-year mean thickness for that cell. The error in the anomaly for each grid cell was also computed. Our grids of ice thickness anomalies were then averaged over the Arctic for each winter season, inversely weighted by the error on each grid cell, to generate regional or circumpolar averages.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13697, "uuid": "6cf4819c630d400b93dac29869327d51", "title": "Cryosphere and Polar Oceans - Ice Sheet Dynamics: Jakobshavn Glacier Calving front - SAR backscatter images", "abstract": " Calving front locations were digitized from SAR backscatter images data, and sea ice extent was mapped using daily sea ice concentration data from the National Snow and Ice Data Centre.\r\n\r\nThe TSX data allowed for calculation of the calving flux components, i.e. (i) the ice flux through a fixed fluxgate near the calving front, and (ii) the mass change of the terminus downglacier of that fluxgate, accounting for front position changes.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13709, "uuid": "54a19411c4d64e1896259e84b18202ba", "title": "UTRAJ trajectory model deployed on Reading University computer", "abstract": "This computation involved: UTRAJ trajectory model deployed on Reading University computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13877, "uuid": "8766588d093841a29a8c13aabe4fcd9f", "title": "Airborne Southern Hemisphere Ozone Experiment (ASHOE) / Measurements for Assessing the Effects of Stratospheric Aircraft (MAESA): Model data", "abstract": "The model contains 00 Z and 12 Z analyses of meteorological parameters on isentropic and isobaric surfaces. From the GSFC Assimilation Model with each file containing analyses for one time period. The GSFC Assimilation was rubn on a GG2%5x2 grid data on theta surfaces", "keywords": "ASHOE, MAESA, Model", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13884, "uuid": "a1111c212f3c4a2eb61e65ad376f2901", "title": "Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE) Project: Model measurements", "abstract": "GSFC Assimilation GG2%5X2 grid data on theta surfaces. The model data contains 12 Z hemispheric analyses of potential vorticity, temperature, horizontal winds, and geopotential. ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13930, "uuid": "3423ef8dc8974e88847fe542fa1bdb0b", "title": "EXPORT Meteorology conditions for the campaign days from ECMWF", "abstract": "Meteorology conditions for the campaign days from ECMWF", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13964, "uuid": "06a52692542d4688bfaf52c642403685", "title": "Cape Verde: NAME dispersion model footprints", "abstract": "Cape Verde: NAME dispersion model footprints", "keywords": "Cape Verde, NAME dispersion model footprints", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 13967, "uuid": "1d1f9f9f54e24cc89a4a840cfb4f1086", "title": "Cape Verde: SOLAS NAME back trajectory images", "abstract": "Cape Verde: SOLAS NAME back trajectory images", "keywords": "Cape Verde, NAME dispersion model footprints", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14174, "uuid": "4af4efc4a9d049678c68f13f8ef6507d", "title": "OP3 Trajectory", "abstract": "OP3 Trajectory", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14197, "uuid": "91ca338e3ce04e16ae735e82e483e693", "title": "UTLS-Ozone ACTO campaign: Model output images", "abstract": "UTLS-Ozone ACTO campaign: Unknown Model output images with flight track", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14233, "uuid": "4b8d095cf2374ebaab5d9c5bbb23f8df", "title": "Flood Risk for Extreme Events (FREE): 3D-Var assimilation of insect-derived radial winds (July 2008 - June 2009)", "abstract": "Radial winds from insects detected by four operational weather radars were assimilated using three-dimensional variational data assimilation (3D-Var) into a 1.5-km resolution version of the Met Office Unified Model.\r\n\r\nThe Met Office’s Unified Model (nonhydrostatic) version 7.3 was used with no convective parameterization. The domain covered the southern part of England and Wales (Fig. 1). The model had a fixed horizontal resolution of 2883360 cell grid with 0.0368 spacing (approximately 1.5 km). The vertical coordinates consisted of 70 terrain-following levels that were closely spaced near the ground. The upper boundary was 40 km MSL. The initial conditions (ICs) used to initialize the runs were derived from archived output of runs from a 4-km resolution, whole U.K. version of the Unified Model.Thereafter the 1.5-km model was run with hourly assimilation cycling to produce updated analyses. The boundary conditions (BCs) used during the forecasts were supplied from the same U.K. 4-km runs. ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14309, "uuid": "b87ff15e75a04958be1b951893fbdeeb", "title": "Quantifying the Amazon Isoprene Budget: GEOS-Chem Chemistry Transport Model", "abstract": "GEOS-Chem Chemistry Transport Model. The nest-grid has a horizontal resolution of 0.667° × 0.5° (longitude × latitude), and 47 vertical levels extending from the surface to 0.01 hPa. The model is driven using GEOS-5 meteorology, which is updated every 3–6 hours. Tracer mixing ratios from an off-line global 4° × 5° simulation provide 3-hourly boundary conditions to the grid-edges. Based on a previous model evaluation [Barkley et al., 2011], we use an updated chemical mechanism to simulate O3-NOx-VOC-aerosol photochemistry.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14343, "uuid": "0e901801a8684e118e9c956cf1f309c9", "title": "Polluted Troposphere TORCH 1: Imperial College model measurements at Writtle College", "abstract": "Results calculated with MCM v3.1 and an optimised gas-aerosol partitioning code in a Photochemical trajectory Model (PTM) for 9 case study events within the TORCH-1 campaign.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14349, "uuid": "514318416f0c40bdb76b6f93855212e2", "title": "HadRT2.0 Computation", "abstract": "Anomalies are calculated with respect to 1971-1990 climatology and are calculated for each of about 200 sonde stations worldwide and grid values derived from these.", "keywords": "Met Office, HADRT, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8794/?format=api" ] }, { "ob_id": 14359, "uuid": "5cfd997f668d42cdb86d9756ffd422f4", "title": "HadRT2.1 Computation", "abstract": "HadRT2.1 is as HadRT2.0 but with bias corrections. That is, anomalies are calculated with respect to 1971-1990 climatology and are calculated for each of about 200 sonde stations worldwide and grid values derived from these and then bias corrections are made to many station time series world-wide. The adjustments were calculated by reference to MSU data products, but only for known changes in instrumental or operational procedures for the period post 1979.", "keywords": "Met Office, HADRT, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8795/?format=api" ] }, { "ob_id": 14360, "uuid": "f0015e95a155419b83e69cfd0c664668", "title": "HadRT2.2 Computation", "abstract": "HADRT2.2 is an eigenvector reconstructed grid data set from 1958 - 2000, on a 10 degree latitude by 20 degree longitude grid, created from HadRT2.1. The eigenvector reconstruction was used to infill missing seasons or years in boxes with 70% of seasonal or annual data available.\r\n\r\nHadRT2.1 is in turn based on HadRT2.0 but with bias corrections. That is, anomalies are calculated with respect to 1971-1990 climatology and are calculated for each of about 200 sonde stations worldwide and grid values derived from these and then bias corrections are made to many station time series world-wide. The adjustments were calculated by reference to MSU data products, but only for known changes in instrumental or operational procedures for the period post 1979.", "keywords": "Met Office, HADRT, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8796/?format=api" ] }, { "ob_id": 14362, "uuid": "135cc60ba6104af49295972a78d49df9", "title": "HadRT2.3 Computation", "abstract": "HADRT2.3 is a globally complete dataset based on HadRT2.1 1958-2000, but with gaps filled in by reference to the second derivative of the corresponding NCEP reanalysis temperature fields, using the Laplacian technique. See Reynolds (1988) paper in docs section.\r\n\r\nHadRT2.1 is in turn based on HadRT2.0 but with bias corrections. That is, anomalies are calculated with respect to 1971-1990 climatology and are calculated for each of about 200 sonde stations worldwide and grid values derived from these and then bias corrections are made to many station time series world-wide. The adjustments were calculated by reference to MSU data products, but only for known changes in instrumental or operational procedures for the period post 1979.", "keywords": "Met Office, HADRT, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8799/?format=api" ] }, { "ob_id": 14394, "uuid": "2da95c3773134f90bc6a2db514d65387", "title": "HadAT1 Computation", "abstract": "The HadAT1 data are produced by performing quality control and a nearest neighbour analysis on the near raw radiosonde network data of HadAT0. See the documentation for full details.", "keywords": "Met Office, HADAT, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8805/?format=api" ] }, { "ob_id": 14396, "uuid": "e5a65e41af384fe0b989ebfc66c69ca3", "title": "HadAT2 Computation", "abstract": "The HadAT2 data are based on the HadAT1 data (produced by performing quality control and a nearest neighbour analysis on the near raw radiosonde network data of HadAT0) but include an expanded radiosonde network. . See the documentation for full details.", "keywords": "Met Office, HADAT, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8807/?format=api" ] }, { "ob_id": 14458, "uuid": "ccea77ea7f8e4cebbc0ee4f711666fe5", "title": "HadAT Uncertainty Estimates compuatation process", "abstract": "See accompanying documentation for full details of of the uncertainty estimate computation process.", "keywords": "Met Office, HADAT, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8809/?format=api" ] }, { "ob_id": 14461, "uuid": "9e6e6341bf544571851db90748c5d259", "title": "Computation for MSU equivalent measures from HadAT2", "abstract": "The MSU equivalent measures from HadAT2 are a composite of remotely sensed data that is then processed to be equivalent to HadAT2. Although justifiable, many of the decisions they have made are subjective and alternative choices could be made that would appear, at least initially, to be equally plausible. Final MSU equivalent measures for the monthly HadAT2 timeseries are available as well as a number of intermediate products required to produce these from the Temperature on Pressure Levels data.", "keywords": "Met Office, HADAT, MSU, radiosonde, temperature anomalies, Hadley", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/8811/?format=api" ] }, { "ob_id": 14468, "uuid": "a12e65652edb42b9bc85f27aa55eb143", "title": "STFC RAL IASI methane processor", "abstract": "Retrieval of methane using the STFC RAL IASI methane processor. Full retrieval diagnostic information including averaging kernels, estimated error and retrieved cloud parameters is produced.", "keywords": "methane, optimal estimation, retrieval", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14478, "uuid": "e45b09df708a4312a3714386e71fd24c", "title": "Computation for: EUCLEIA", "abstract": "This computation involved: Met Office unified model (UM) deployed on Met Office supercomputer (Exeter).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14492, "uuid": "e02574868d5a4bcca4c9b019e91eca9f", "title": "Computation for: GlobSnow L3A STD of daily Snow Water Equivalent (SWE) Estimates", "abstract": "Statistical error is determined through an adaptive dynamic error propagation approach. For more details see accompanying documents on basic methodology see Pulliainen, 2006 (link under docs tab).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14494, "uuid": "8b1d73a40fe44b3589d2da8b027ea697", "title": "Computation for: GlobSnow L3B mean STD of 7 day running mean Snow Water Equivalent (SWE) Estimates", "abstract": "Statistical error is determined through an adaptive dynamic error propagation approach. For more details see accompanying documents on basic methodology in Pulliainen 2006 (link under docs tab).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14495, "uuid": "d2ffb1353af94534a101f5af0f688382", "title": "Computation for: GlobSnow Snow Water Equivalent (SWE) v2.0 L3A Daily data", "abstract": "GlobSnow Snow Water Equivalent dataset combines space borne radiometer brightness temperature information with snow depth information from terrestrial weather station network to give an estimate about amount of water contained within a snow pack. The computational retrieval algorithm is complex, for more detailed information, please see accompanying documentation.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14496, "uuid": "b103bd50efb54c92b520eff9df5193f7", "title": "Computation for: GlobSnow Snow Water Equivalent (SWE) v2.0 L3B Monthly Aggregated Maximum value data", "abstract": "GlobSnow Snow Water Equivalent dataset combines space borne radiometer brightness temperature information with snow depth information from terrestrial weather station network to give an estimate about amount of water contained within a snow pack. These files contain a maximum value from GlobSnow SWE Weekly product calculated for each given month. The computational retrieval algorithm is complex, for more detailed information, please see accompanying documentation.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14497, "uuid": "9eb3c85266344d9ea437a95772ed8df3", "title": "Computation for: GlobSnow Snow Water Equivalent (SWE) v2.0 L3B Monthly data", "abstract": "GlobSnow Snow Water Equivalent dataset combines space borne radiometer brightness temperature information with snow depth information from terrestrial weather station network to give an estimate about amount of water contained within a snow pack. These files contain a monthly aggregate value that has been calculated as simple mean from GlobSnow SWE Weekly product for given month. The computational retrieval algorithm is complex, for more detailed information, please see accompanying documentation.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14498, "uuid": "4c096aa211ac48e59a73339013a1618b", "title": "Computation for: GlobSnow Snow Water Equivalent (SWE) v2.0 L3B Weekly aggregated data", "abstract": "Computation for GlobSnow Snow Water Equivalent (SWE) v2.0 L3B Weekly aggregated data. GlobSnow Snow Water Equivalent dataset combines space borne radiometer brightness temperature information with snow depth information from terrestrial weather station network to give an estimate about amount of water contained within a snow pack. These files have been computed from GlobSnow SWE daily product as a 7-day sliding window average to reduce effects from missing weather station data and other artefacts. The computational retrieval algorithm is complex, for more detailed information, please see accompanying documentation.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14521, "uuid": "70aa606ca0584f4594588fc6d7842595", "title": "NAME dispersion model footprints", "abstract": "Atmospheric dispersion model footprints computed at the University of Leicester for various projects using the the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14562, "uuid": "293b605e334a49f4892f0f83d189b3a1", "title": "Met Office Hadley Centre Regional Climate Model (HadRM3-PPE)", "abstract": "These model runs were generated by running the Met Office Hadley Centre Regional Model 3 Simulation Data (HadRM3) using a Perturbed Physics Ensemble.", "keywords": "Met Office, UM, PPE", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14615, "uuid": "1c75f914814545e68231638b42dd60f0", "title": "Volcanic Ash Product Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Volcanic Ash Product derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14616, "uuid": "53e81259174b4cd981826a14a8bd923e", "title": "Snow Detection Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Snow Detection Products derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ] }