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

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.

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).


Related Datasets

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

Related Publications

No Related Publications