Dataset: Optimally Interpolated O2 anomalies based on World Ocean Database 2018

Name: Optimally Interpolated O2 anomalies based on World Ocean Database 2018
Published: 2023-01-11
Keywords: deoxygenation, oxygen, climate change, oceans

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.886218.1Version 1 (2023-01-11)Dataset Type:model resultsDataset Type:Cruise Results

Principal Investigator: Takamitsu Ito (Georgia Institute of Technology)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: Mapping Dissolved Oxygen using Observations and Machine Learning (DO Machine Learning)

Abstract

OIO2 is a gridded data product of dissolved oxygen interpolated from shipboard observations archived in the World Ocean Database 2018 (WOD18). The quality-controlled WOD18 data are averaged for each bin at 1°x1° and monthly resolution where mean, variance, and sample size are recorded from 1965 to 2014 for the bottle data, and from 1987 to 2014 for the CTD-O2 data.

Cite Dataset

Spatial Extent: N:90.00 E:180.00 S:-90.00 W:-180.00
Temporal Extent: 1965 - 2012

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This is a gridded data product generated from many observational profiles from the World Ocean Database 2018. There are two types of measurement methods included in the data source: bottle O2 data measured by the Winkler titration method and data from the CTD-O2 sensor. The data product is available as a NetCDF file (OIO2_g1x1v47_1967_2012.nc).

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References

Dataset: https://www.ncei.noaa.gov/sites/default/files/2020-04/wod_intro_0.pdf

Boyer, T.P., O.K. Baranova, C. Coleman, H.E. Garcia, A. Grodsky, R.A. Locarnini, A.V. Mishonov, C.R. Paver, J.R. Reagan, D. Seidov, I.V. Smolyar, K. Weathers, M.M. Zweng,(2018): World Ocean Database 2018. A.V. Mishonov, Technical Ed., NOAA Atlas NESDIS 87. https://www.ncei.noaa.gov/sites/default/files/2020-04/wod_intro_0.pdf

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Dataset: Optimally Interpolated O2 anomalies based on World Ocean Database 2018

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.886218.1Version 1 (2023-01-11)Dataset Type:model resultsDataset Type:Cruise Results

Principal Investigator: Takamitsu Ito (Georgia Institute of Technology)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: Mapping Dissolved Oxygen using Observations and Machine Learning (DO Machine Learning)

Abstract

Cite Dataset

Spatial Extent: N:90.00 E:180.00 S:-90.00 W:-180.00
Temporal Extent: 1965 - 2012

65

Views

330

Downloads

These numbers come from web analytics and reflect real user activity on the site. They reliably show dataset usage and are mostly free of bot traffic.

Related Datasets

References

Dataset: https://www.ncei.noaa.gov/sites/default/files/2020-04/wod_intro_0.pdf

Related Publications

No Related Publications

Dataset: Optimally Interpolated O2 anomalies based on World Ocean Database 2018

Principal Investigator: Takamitsu Ito (Georgia Institute of Technology)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: Mapping Dissolved Oxygen using Observations and Machine Learning (DO Machine Learning)

Abstract

65

330

Files

Related Datasets

Related Publications

Dataset: Optimally Interpolated O2 anomalies based on World Ocean Database 2018

Principal Investigator: Takamitsu Ito (Georgia Institute of Technology)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: Mapping Dissolved Oxygen using Observations and Machine Learning (DO Machine Learning)

Abstract

65

330

Files

Related Datasets

Related Publications

Dataset: Optimally Interpolated O2 anomalies based on World Ocean Database 2018

Principal Investigator: Takamitsu Ito (Georgia Institute of Technology)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: Mapping Dissolved Oxygen using Observations and Machine Learning (DO Machine Learning)

Abstract

Metadata

65

330

Files

Related Datasets

Related Publications

Dataset: Optimally Interpolated O2 anomalies based on World Ocean Database 2018

Principal Investigator: Takamitsu Ito (Georgia Institute of Technology)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: Mapping Dissolved Oxygen using Observations and Machine Learning (DO Machine Learning)

Abstract

Metadata

65

330

Files

Related Datasets

Related Publications