contact:
- organization: {email: ncei.info@noaa.gov, name: NOAA National Centers for Environmental
      Information}
  roles: [custodian]
- organization: {email: null, name: NOAA National Centers for Environmental Information}
  roles: [custodian]
distribution:
- name: {en: Project Metadata, fr: Project Metadata (FR)}
  url: https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0222469.html
- name: {en: NCEI Dataset Landing Page, fr: NCEI Dataset Landing Page (FR)}
  url: https://doi.org/10.25921/ndgj-jp24
- name: {en: Descriptive Information, fr: Descriptive Information (FR)}
  url: https://www.ncei.noaa.gov/archive/accession/oas/222469
- name: {en: HTTPS, fr: HTTPS (FR)}
  url: https://www.ncei.noaa.gov/archive/accession/download/222469
- name: {en: FTP, fr: FTP (FR)}
  url: ftp://ftp-oceans.ncei.noaa.gov/nodc/archive/arc0164/0222469/
- name: {en: CIOOS HTTP, fr: SIOOC HTTP}
  url: https://data.cioospacific.ca/ocads/gov.noaa.nodc_0222469/
identification:
  abstract:
    en: 'This dataset contains global monthly climatology of oceanic total dissolved
      inorganic carbon (DIC). (DIC) monthly climatology was created from a neural
      network approach (Broullón et al., 2020). The neural network was trained with
      GLODAPv2.2019 (Olsen et al., 2019) and LDEOv2016 (Takahashi et al., 2017) data,
      using as predictor variables position (latitude, longitude and depth), year,
      temperature, salinity, phosphate, nitrate, silicate and dissolved oxygen. pCO2
      from LDEOv2016 and AT from Broullón et al. (2019) were used to compute DIC surface
      values to increase the surface coverage in the training data. The relations
      extracted between the predictor variables and DIC were used to obtain the climatology
      passing through the network global monthly climatologies of the predictor variables:
      temperature and salinity fields of the World Ocean Atlas version 2013 (WOA13),
      filtered WOA13 oxygen (fifth-order one-dimensional median filter through the
      depth dimension; see Broullón et al., 2019 for details) and nutrients computed
      using CANYON-B (Bittig et al., 2018) over the three previous fields. The obtained
      climatology has a 1ºx1º spatial resolution and 102 depth levels between 0 and
      5500 m, with a monthly resolution from 0 to 1500 m and an annual resolution
      from 1550 to 5500m.'
    fr: 'This dataset contains global monthly climatology of oceanic total dissolved
      inorganic carbon (DIC). (DIC) monthly climatology was created from a neural
      network approach (Broullón et al., 2020). The neural network was trained with
      GLODAPv2.2019 (Olsen et al., 2019) and LDEOv2016 (Takahashi et al., 2017) data,
      using as predictor variables position (latitude, longitude and depth), year,
      temperature, salinity, phosphate, nitrate, silicate and dissolved oxygen. pCO2
      from LDEOv2016 and AT from Broullón et al. (2019) were used to compute DIC surface
      values to increase the surface coverage in the training data. The relations
      extracted between the predictor variables and DIC were used to obtain the climatology
      passing through the network global monthly climatologies of the predictor variables:
      temperature and salinity fields of the World Ocean Atlas version 2013 (WOA13),
      filtered WOA13 oxygen (fifth-order one-dimensional median filter through the
      depth dimension; see Broullón et al., 2019 for details) and nutrients computed
      using CANYON-B (Bittig et al., 2018) over the three previous fields. The obtained
      climatology has a 1ºx1º spatial resolution and 102 depth levels between 0 and
      5500 m, with a monthly resolution from 0 to 1500 m and an annual resolution
      from 1550 to 5500m. (FR)'
    translations:
      fr: {message: Auto-translated using AWS, validated: false}
  acknowledgement: acknowledgement
  associated_resources: []
  keywords:
    default:
      en: [0222469, Arctic Ocean, Atlantic Ocean, CO2 ANALYZERS > CO2 ANALYZERS, DEPTH
          - OBSERVATION, DISSOLVED INORGANIC CARBON (DIC), Data synthesis product,
        EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > INORGANIC CARBON, GLOBAL OCEAN
          DATA ANALYSIS PROJECT (GLODAP), GLODAP > Global Ocean Data Analysis Project,
        Indian Ocean, Institute of Marine Research Vigo, LATITUDE, LONGITUDE, North
          Atlantic Ocean, North Pacific Ocean, OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC
          OCEAN, OCEAN > ATLANTIC OCEAN > SOUTH ATLANTIC OCEAN, OCEAN > INDIAN OCEAN,
        OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN, OCEAN > PACIFIC OCEAN > SOUTH
          PACIFIC OCEAN, OCEAN > SOUTHERN OCEAN, Ocean Carbon and Acidification Data
          System (OCADS) Project, Pacific Ocean, South Atlantic Ocean, South Pacific
          Ocean, Southern Ocean, TCO2_NNGv2LDEO, VARIOUS CHARTERED VESSELS, Various,
        chemical, depth, discrete sample, latitude, longitude, profile]
      fr: [0222469 (FR), Arctic Ocean (FR), Atlantic Ocean (FR), CO2 ANALYZERS > CO2
          ANALYZERS (FR), DEPTH - OBSERVATION (FR), DISSOLVED INORGANIC CARBON (DIC)
          (FR), Data synthesis product (FR), EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY
          > INORGANIC CARBON (FR), GLOBAL OCEAN DATA ANALYSIS PROJECT (GLODAP) (FR),
        GLODAP > Global Ocean Data Analysis Project (FR), Indian Ocean (FR), Institute
          of Marine Research Vigo (FR), LATITUDE (FR), LONGITUDE (FR), North Atlantic
          Ocean (FR), North Pacific Ocean (FR), OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC
          OCEAN (FR), OCEAN > ATLANTIC OCEAN > SOUTH ATLANTIC OCEAN (FR), OCEAN >
          INDIAN OCEAN (FR), OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN (FR), OCEAN
          > PACIFIC OCEAN > SOUTH PACIFIC OCEAN (FR), OCEAN > SOUTHERN OCEAN (FR),
        Ocean Carbon and Acidification Data System (OCADS) Project (FR), Pacific Ocean
          (FR), South Atlantic Ocean (FR), South Pacific Ocean (FR), Southern Ocean
          (FR), TCO2_NNGv2LDEO (FR), VARIOUS CHARTERED VESSELS (FR), Various (FR),
        chemical (FR), depth (FR), discrete sample (FR), latitude (FR), longitude
          (FR), profile (FR)]
    eov:
      en: [carbon dioxide (CO2) gas analyzer, oceanography, physical]
      fr: [carbon dioxide (CO2) gas analyzer (FR), oceanography (FR), physical (FR)]
  project:
    en: [project_a, project_b]
    fr: [project_a in french, project_b in french]
  status: onGoing
  temporal_begin: '1950-07-31'
  temporal_duration: P1D
  temporal_end: '2025-04-16'
  time_coverage_resolution: P1D
  title:
    en: 'A global monthly climatology of oceanic total dissolved inorganic carbon
      (DIC): a neural network approach (NCEI Accession 0222469)'
    fr: 'A global monthly climatology of oceanic total dissolved inorganic carbon
      (DIC): a neural network approach (NCEI Accession 0222469) (FR)'
    translations:
      fr: {message: Auto-translated using AWS, validated: false}
instruments:
- description: {en: null, fr: null}
  id: null
  manufacturer: null
  type: {en: null, fr: null}
  version: null
metadata:
  comment: auto-generated comment
  dates: {creation: '2024-01-01'}
  history:
  - scope: model
    statement:
      en: null
      fr: None (FR)
      translations:
        fr: {message: text translated using the Amazon translate service / texte traduit
            à l'aide du service de traduction Amazon, verified: false}
  - scope: model
    statement:
      en: null
      fr: None (FR)
      translations:
        fr: {message: text translated using the Amazon translate service / texte traduit
            à l'aide du service de traduction Amazon, verified: false}
  identifier: gov.noaa.nodc:0222469
  language: en
  maintenance_note: auto-generated
  naming_authority: ca.cioos
  scope: model
  use_constraints:
    licence: {code: CC-BY-4.0, title: Creative Commons Attribution 4.0, url: 'https://creativecommons.org/licenses/by/4.0/'}
    limitations:
      en: limitations in english
      fr: limitations in french
      translations:
        fr: {message: Auto-translated using AWS, validated: false}
spatial:
  bbox: [-179.5, -77.5, 179.5, 89.5]
  description: description of the spatial extent or study area of the dataset
  descriptionIdentifier: A2345-FS323-DG434-345DG
  vertical: [0, 10]
  vertical_positive: down
