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2024-03-08T13:21:39Z
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Global surface-ocean partial pressure of carbon dioxide (pCO2) estimates from a machine learning ensemble: CSIR-ML6 v2019a (NCEI Accession 0206205)
2019-11-05
publication
International DOI Foundation (IDF)
10.25921/z682-mn47
NOAA National Centers for Environmental Information
gov.noaa.nodc:0206205
NCEI Archive Management System
0206205
NOAA National Centers for Environmental Information
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publisher
Luke Gregor
Institute of Biogeochemistry and Pollutant Dynamics (IBP)
luke.gregor@usys.ethz.ch
http://www.ibp.ethz.ch/
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Institute of Biogeochemistry and Pollutant Dynamics website
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Council for Scientific and Industrial Research (CSIR)
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Luke Gregor
Institute of Biogeochemistry and Pollutant Dynamics (IBP)
luke.gregor@usys.ethz.ch
http://www.ibp.ethz.ch/
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principalInvestigator
Alice D. Lebehot
Council for Scientific and Industrial Research (CSIR)
principalInvestigator
Schalk Kok
Department of Mechanical and Aeronautical Engineering, University of Pretoria, Pretoria, 0028, South Africa
principalInvestigator
Pedro M. S. Monteiro
Council for Scientific and Industrial Research (CSIR)
principalInvestigator
Gregor, Luke
Institute of Biogeochemistry and Pollutant Dynamics (IBP)
luke.gregor@usys.ethz.ch
http://www.ibp.ethz.ch/
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Institute of Biogeochemistry and Pollutant Dynamics website
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author
Lebehot, Alice D.
Council for Scientific and Industrial Research (CSIR)
author
Kok, Schalk
Department of Mechanical and Aeronautical Engineering, University of Pretoria, Pretoria, 0028, South Africa
author
Monteiro, Pedro M. S.
Council for Scientific and Industrial Research (CSIR)
author
Institute of Biogeochemistry and Pollutant Dynamics (IBP)
http://www.ibp.ethz.ch/
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Council for Scientific and Industrial Research (CSIR)
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This dataset contains surface-ocean partial pressure of carbon dioxide (pCO2) that the ensemble mean of six two-step clustering-regression machine learning methods. The ensemble is a combination of two clustering approaches and three regression methods. For the clustering approaches, we use K-means clustering (21 clusters) and open ocean CO2 biomes as defined by Fay and McKinley (2014). Three machine learning regression methods are applied to each of these two clustering methods. These machine learning methods are feed-forward neural-network (FFN), support vector regression (SVR) and gradient boosted machine using decision trees (GBM). The final estimate of surface ocean pCO2 is the average of the six machine learning estimates resulting in a monthly by 1° ⨉ 1° resolution product that extends from the start of 1982 to the end of 2016. Sea-air fluxes (FCO2) calculated from pCO2 are also presented in the data. The discrete boundaries of the clustering approach result in semi-discrete discontinuities in pCO2 and fCO2 estimates. These are smoothed by applying a 3 ⨉ 3 ⨉ 3 convolution (moving average) to the dataset in time, latitude and longitude.
This dataset is available to the public for a wide variety of uses including scientific research and analysis.
Funding Information: SOCCO, Council for Scientific and Industrial Research
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0206205
NCEI ACCESSION NUMBER
2019-10-18
publication
AIR-SEA FLUX - PARTIAL PRESSURE (OR FUGACITY) OF CARBON DIOXIDE
partial pressure of carbon dioxide - water
pCO2 - AIR
theme
NODC DATA TYPES THESAURUS
showerhead equilibrator
instrument
NODC INSTRUMENT TYPES THESAURUS
chemical
meteorological
surface measurements
theme
NODC OBSERVATION TYPES THESAURUS
VARIOUS CHARTERED VESSELS
platform
NODC PLATFORM NAMES THESAURUS
Council for Scientific and Industrial Research
Institute of Biogeochemistry and Pollutant Dynamics
dataCentre
NODC COLLECTING INSTITUTION NAMES THESAURUS
Council for Scientific and Industrial Research
dataCentre
NODC SUBMITTING INSTITUTION NAMES THESAURUS
Surface Ocean CO2 Atlas (SOCAT)
project
NODC PROJECT NAMES THESAURUS
Arctic Ocean
Indian Ocean
North Atlantic Ocean
North Pacific Ocean
South Atlantic Ocean
South Pacific Ocean
Southern Ocean
place
NODC SEA AREA NAMES THESAURUS
oceanography
theme
WMO_CategoryCode
2012-09-15
publication
Various
project
Cruise ID
Various
project
EXPOCODE
Ocean Carbon and Acidification Data System (OCADS) Project
project
Ocean Acidification Search Keywords
Various
project
Reference Section ID
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC CHEMISTRY > CARBON AND HYDROCARBON COMPOUNDS > ATMOSPHERIC CARBON DIOXIDE > PARTIAL PRESSURE OF CARBON DIOXIDE
EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > CARBON DIOXIDE
theme
Global Change Master Directory (GCMD) Science Keywords
2023
revision
17
Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA)
Greenbelt
MD
https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords
HTTPS
GCMD Keyword Forum Page
Global Change Master Directory (GCMD). 2023. GCMD Keywords, Version 17. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords
information
custodian
Data synthesis product
Discrete measurement
Profile
theme
OCADS Study Type
FCO2_raw (time, lat, lon)
FCO2_smooth (time, lat, lon)
Time
lat (180)
lon (360)
pCO2air (time, lat, lon)
pCO2sea_raw (time, lat, lon)
pCO2sea_smooth (time, lat, lon)
seamask (lat, lon)
theme
Provider Variable Abbreviations
EQUILIBRATORS
instrument
Global Change Master Directory (GCMD) Instrument Keywords
2023
revision
17
Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA)
Greenbelt
MD
https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords
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GCMD Keyword Forum Page
Global Change Master Directory (GCMD). 2023. GCMD Keywords, Version 17. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords
information
custodian
OCEAN > ARCTIC 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
place
Global Change Master Directory (GCMD) Location Keywords
2023
revision
17
Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA)
Greenbelt
MD
https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords
HTTPS
GCMD Keyword Forum Page
Global Change Master Directory (GCMD). 2023. GCMD Keywords, Version 17. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords
information
custodian
Arctic Ocean
Atlantic Ocean
Indian Ocean
Pacific Ocean
Southern Ocean
place
Provider Geographic Names
accessLevel: Public
otherRestrictions
Cite as: Gregor, Luke; Lebehot, Alice D.; Kok, Schalk; Monteiro, Pedro M. S. (2019). Global surface-ocean partial pressure of carbon dioxide (pCO2) estimates from a machine learning ensemble: CSIR-ML6 v2019a (NCEI Accession 0206205). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/z682-mn47. Accessed [date].
Distribution liability: NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives.
otherRestrictions
Use liability: NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose.
Gregor, L., Lebehot, A. D., Kok, S., and Scheel Monteiro, P. M., 2019: A comparative assessment of the uncertainties of global surface ocean CO2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) - have we hit the wall?, Geosci. Model Dev. Discuss., 12, 5113-5136, https://doi.org/10.5194/gmd-2019-46.
2019-04-05
publication
International DOI Foundation (IDF)
https://doi.org/10.5194/gmd-2019-46
https://doi.org/10.5194/gmd-2019-46
HTTPS
https://doi.org/10.5194/gmd-2019-46
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information
Gregor, Luke
ETH Zürich
http://www.ethz.ch
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ETH Zürich website
Institution web page
information
author
Lebehot, Alice D.
author
Kok, Schalk
author
Scheel Monteiro, Pedro M.
author
Copernicus GmbH
publisher
documentDigital
ARRAY(0x592b4f8)
crossReference
project
Global surface-ocean pCO2 estimates from a machine learning ensemble: CSIR-ML6 v2019a
2022
publication
https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/ndp_101/ndp101.html
HTTPS
https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/ndp_101/ndp101.html
related resource
information
US DOC; NOAA; NESDIS; National Centers for Environmental Information (NCEI)
publisher
documentDigital
crossReference
project
NOAA National Centers for Environmental Information (2022). Ocean Carbon and Acidification Data System (OCADS). NOAA National Centers for Environmental Information. https://www.ncei.noaa.gov/products/ocean-carbon-acidification-data-system
2022-04
publication
https://www.ncei.noaa.gov/products/ocean-carbon-acidification-data-system
HTTPS
https://www.ncei.noaa.gov/products/ocean-carbon-acidification-data-system
OCADS website
information
NOAA National Centers for Environmental Information
author
US DOC; NOAA; NESDIS; National Centers for Environmental Information (NCEI)
publisher
documentDigital
[accessed 2024-02-08]
crossReference
program
eng; USA
utf8
environment
oceans
climatologyMeteorologyAtmosphere
-180
180
-89.5
89.5
1982-01-01
2016-12-31
NOAA National Centers for Environmental Information
+1-301-713-3277
NCEI.Info@noaa.gov
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In most cases, electronic downloads of the data are free. However, fees may apply for custom orders, data certifications, copies of analog materials, and data distribution on physical media.
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Originator data format
551.804
https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0206205.html
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information
https://doi.org/10.25921/z682-mn47
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https://www.ncei.noaa.gov/archive/accession/oas/206205
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https://www.ncei.noaa.gov/archive/accession/download/206205
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ftp://ftp-oceans.ncei.noaa.gov/nodc/archive/arc0148/0206205/
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dataset
NCEI Accession 0206205 v1.1 was published.
2019-11-05T19:14:30Z
NCEI Accession 0206205 v1.1
publication
https://www.ncei.noaa.gov/archive/accession/0206205/1.1
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NCEI Accession 0206205 v1.1
published 2019-11-05T19:14:30Z
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dataset
Parameter or Variable: Time;
Abbreviation: Time;
Unit: seconds since 2000-01-01;
Detailed sampling and analyzing information: min = 1982-01-15; max = 2016-12-15; step = month.
Parameter or Variable: Latitude;
Abbreviation: lat (180);
Unit: degrees_north;
Detailed sampling and analyzing information: min = -89.5; max = 89.5; step = 1.0.
Parameter or Variable: Latitude;
Abbreviation: lon (360);
Unit: degrees_east;
Detailed sampling and analyzing information: min = -180; max = 180; step = 1.0.
Parameter or Variable: partial pressure of surface ocean CO2 raw;
Abbreviation: pCO2sea_raw (time, lat, lon);
Unit: µatm;
Detailed sampling and analyzing information: The ensemble mean of six machine learning methods that first cluster data and then apply regression to the clusters.
Parameter or Variable: smoothed partial pressure of surface ocean CO2;
Abbreviation: pCO2sea_smooth (time, lat, lon);
Unit: µatm;
Detailed sampling and analyzing information: The discrete boundaries of the clustering approach result in semi-discrete discontinuities in pCO2 and FCO2 estimates. These are smoothed by applying a 3 ⨉ 3 ⨉ 3 convolution (moving average) to the dataset in time, latitude and longitude..
Parameter or Variable: sea-air CO2 flux;
Abbreviation: FCO2_raw (time, lat, lon);
Unit: molC/m2/yr;
Detailed sampling and analyzing information: sea-air CO2 flux calculated after Landschutzer et al (2016) as the product of the following: (pCO_2^sea-pCO_2^air) where positive values are outgassing from sea to air; the Wanninkhof (1992) parameterisation of k_w scaled globally to 16 cm/hr with wind from ERA-interim (Dee et al, 2011); K_0 from Weiss (1974) using the OISSTv2 sea surface temperature product (Reynolds et al. 2007) and EN4 sea salinity (Good et al. 2013); (1 - ice_frac) as described in Butterworth and Miller (2016)..
Parameter or Variable: smoothed sea-air CO2 flux;
Abbreviation: FCO2_smooth (time, lat, lon);
Unit: mol/m2/a;
Detailed sampling and analyzing information: The discrete boundaries of the clustering approach result in semi-discrete discontinuities in pCO2 and FCO2 estimates. These are smoothed by applying a 3 ⨉ 3 ⨉ 3 convolution (moving average) to the dataset in time, latitude and longitude..
Parameter or Variable: partial pressure of atmospheric CO2;
Abbreviation: pCO2air (time, lat, lon);
Unit: µatm;
Detailed sampling and analyzing information: Atmospheric pCO2 from CarboScope v1.7 (Rodenbeck et al 2014) source = http://www.bgc-jena.mpg.de/CarboScope/.
Parameter or Variable: boolean mask where True is ocean and False is land or NULL;
Abbreviation: seamask (lat, lon);
Detailed sampling and analyzing information: source - https://www.ncei.noaa.gov/access/ocean-carbon-data-system/oceans/SPCO2_1982_present_ETH_SOM_FFN.html .
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Metadata are developed, maintained and distributed by NCEI. Updates are performed as needed to maintain currentness.
NOAA National Centers for Environmental Information
custodian
showerhead equilibrator
showerhead equilibrator
extracts dissolved CO2 from water
A carbon dioxide equilibrator is usually in the shape of a vertical tube, with a showerhead on the top, some headspace, a lot of beads to increase the surface exchange area between water and air, a water seal device at the bottom to allow water to overflow, but prevents air exchange between inside and outside.
Carbon dioxide (CO2) equilibrator works together with carbon dioxide (CO2) gas analyzer (insttypes_id 183) to measure carbon dioxide in the water.
To measure water carbon dioxide, water needs to be continuously supplied to a showerhead inside an equilibrator. As the water flows through the equilibrator chamber, dissolved carbon dioxide exchanges quickly with air in the headspace. This air is then sampled by the carbon dioxide analyzer to determine the mole fraction of CO2 in water.
VARIOUS CHARTERED VESSELS
VARIOUS CHARTERED VESSELS