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/0298989.html
- name: {en: NCEI Dataset Landing Page, fr: NCEI Dataset Landing Page (FR)}
  url: https://doi.org/10.25921/0s8y-q287
- name: {en: Descriptive Information, fr: Descriptive Information (FR)}
  url: https://www.ncei.noaa.gov/archive/accession/oas/298989
- name: {en: HTTPS, fr: HTTPS (FR)}
  url: https://www.ncei.noaa.gov/archive/accession/download/298989
- name: {en: FTP, fr: FTP (FR)}
  url: ftp://ftp-oceans.ncei.noaa.gov/nodc/archive/arc0235/0298989/
- name: {en: CIOOS HTTP, fr: SIOOC HTTP}
  url: https://data.cioospacific.ca/ocads/gov.noaa.nodc_0298989/
identification:
  abstract:
    en: This dataset contains global surface water partial pressure of CO2 data, pCO2w
      data, and sea-air CO2 fluxes based on the extremely randomized trees or extra
      trees, ET machine learning approach. The products are labeled as AOML_ET. The
      outputs are monthly pCO2 and sea-air CO2 flux fields at 1°x1° resolution covering
      the global ocean from 1998 to 2023. The results of several different permutations
      of AOML-ET are provided. They all use the following predictor variables at monthly
      and at 1°x1° resolution. The variables are time, location, sea surface temperature,
      SST, sea surface salinity, SSS, mixed layer depth, MLD, and chlorophyll-a, chl-a.
      The training is performed on the v2020 and v2023 releases of the Surface Ocean
      CO2 Atlas (www.SOCATinfo). The sea-air CO2 fluxes are computed from the air-sea
      CO2 partial pressure difference, ∆pCO2, and a bulk gas transfer formulation
      with windspeed. This data holding includes files of the monthly 1°x1° predictor
      variables. Several AOML_ET products are provided in this accession. SOCATv2020
      and SOCATv2023 are used for training; pCO2w and ∆pCO2 are target variables;
      two different datasets for air CO2 are used for the calculation of sea-air CO2
      fluxes, and three different gas exchange parameterizations are applied to determine
      the sea-air CO2 fluxes. Details are found in the readme file.
    fr: This dataset contains global surface water partial pressure of CO2 data, pCO2w
      data, and sea-air CO2 fluxes based on the extremely randomized trees or extra
      trees, ET machine learning approach. The products are labeled as AOML_ET. The
      outputs are monthly pCO2 and sea-air CO2 flux fields at 1°x1° resolution covering
      the global ocean from 1998 to 2023. The results of several different permutations
      of AOML-ET are provided. They all use the following predictor variables at monthly
      and at 1°x1° resolution. The variables are time, location, sea surface temperature,
      SST, sea surface salinity, SSS, mixed layer depth, MLD, and chlorophyll-a, chl-a.
      The training is performed on the v2020 and v2023 releases of the Surface Ocean
      CO2 Atlas (www.SOCATinfo). The sea-air CO2 fluxes are computed from the air-sea
      CO2 partial pressure difference, ∆pCO2, and a bulk gas transfer formulation
      with windspeed. This data holding includes files of the monthly 1°x1° predictor
      variables. Several AOML_ET products are provided in this accession. SOCATv2020
      and SOCATv2023 are used for training; pCO2w and ∆pCO2 are target variables;
      two different datasets for air CO2 are used for the calculation of sea-air CO2
      fluxes, and three different gas exchange parameterizations are applied to determine
      the sea-air CO2 fluxes. Details are found in the readme file. (FR)
    translations:
      fr: {message: Auto-translated using AWS, validated: false}
  acknowledgement: acknowledgement
  associated_resources: []
  keywords:
    default:
      en: [0298989, CO2 ANALYZERS > CO2 ANALYZERS, 'COLUMBIA/LDEO > Lamont-Doherty
          Earth Observatory, Columbia University', Columbia University; Lamont-Doherty
          Earth Observatory, Data Product, NA, Ocean Carbon and Acidification Data
          System (OCADS), Ocean Carbon and Acidification Data System (OCADS) Project,
        'UCO/CIRES > Cooperative Institute for Research in Environmental Sciences,
          University of Colorado', 'University of Colorado Boulder, Cooperative Institute
          for Research In Environmental Sciences', World-Wide Distribution, chemical,
        in particular the Global Ocean Monitoring and Observations program (fund reference
          100007298), pCO2w]
      fr: [0298989 (FR), CO2 ANALYZERS > CO2 ANALYZERS (FR), 'COLUMBIA/LDEO > Lamont-Doherty
          Earth Observatory, Columbia University (FR)', Columbia University; Lamont-Doherty
          Earth Observatory (FR), Data Product (FR), NA (FR), Ocean Carbon and Acidification
          Data System (OCADS) (FR), Ocean Carbon and Acidification Data System (OCADS)
          Project (FR), 'UCO/CIRES > Cooperative Institute for Research in Environmental
          Sciences, University of Colorado (FR)', 'University of Colorado Boulder,
          Cooperative Institute for Research In Environmental Sciences (FR)', World-Wide
          Distribution (FR), chemical (FR), in particular the Global Ocean Monitoring
          and Observations program (fund reference 100007298) (FR), pCO2w (FR)]
    eov:
      en: ['DOC/NOAA/OAR/AOML > Atlantic Oceanographic and Meteorological Laboratory,
          OAR, NOAA, U.S. Department of Commerce', EARTH SCIENCE > OCEANS > OCEAN
          CHEMISTRY > CARBON DIOXIDE, GEOGRAPHIC REGION > GLOBAL OCEAN, The NOAA office
          of Oceanic and Atmospheric Research is acknowledged for financial support,
        US DOC; NOAA; OAR; Atlantic Oceanographic and Meteorological Laboratory, carbon
          dioxide (CO2) gas analyzer, oceanography, partial pressure of carbon dioxide
          - water]
      fr: ['DOC/NOAA/OAR/AOML > Atlantic Oceanographic and Meteorological Laboratory,
          OAR, NOAA, U.S. Department of Commerce (FR)', EARTH SCIENCE > OCEANS > OCEAN
          CHEMISTRY > CARBON DIOXIDE (FR), GEOGRAPHIC REGION > GLOBAL OCEAN (FR),
        The NOAA office of Oceanic and Atmospheric Research is acknowledged for financial
          support (FR), US DOC; NOAA; OAR; Atlantic Oceanographic and Meteorological
          Laboratory (FR), carbon dioxide (CO2) gas analyzer (FR), oceanography (FR),
        partial pressure of carbon dioxide - water (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: 'AOML_ET: Partial pressure of CO2 (pCO2) and sea-air CO2 fluxes for the global
      ocean, along with the predictor variables from 1998-01-01 to 2023-12-30, using
      an Extra Trees (extremely randomized trees) machine learning (NCEI Accession
      0298989)'
    fr: 'AOML_ET: Partial pressure of CO2 (pCO2) and sea-air CO2 fluxes for the global
      ocean, along with the predictor variables from 1998-01-01 to 2023-12-30, using
      an Extra Trees (extremely randomized trees) machine learning (NCEI Accession
      0298989) (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:0298989
  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: [-180.0, -70.0, 180.0, 78.0]
  description: description of the spatial extent or study area of the dataset
  descriptionIdentifier: A2345-FS323-DG434-345DG
  vertical: [0, 10]
  vertical_positive: down
