Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Project Information
• Funding

A results paper for this dataset is in preparation for the Geoscience Data Journal as Ito T. (2021) Optimal interpolation of global dissolved oxygen: 1965-2015.

This dataset provides a gridded map of dissolved oxygen for the global oceans using optimal interpolation method solely based on the Winker O2 measurements from the World Ocean Database 2018.  The resulting gridded product includes full-depth map of dissolved oxygen from 1965 to 2015 with uncertainty estimates. The uncertainty can come from unresolved small-scale and high frequency variability and mapping errors. The multi-decadal trend of global dissolved oxygen is in the range of -281 to -373 Tmol/decade (95% confidence interval) with the median of -328 Tmol/decade. This estimate is more conservative than previous works. In optimal interpolation, the grid points far from the observations are essentially assigned to the climatology. The results from this study likely provide a lower bound estimate of the global oxygen loss.

Further methodology details are included in the publication in preparation for the Geoscience Data Journal as Ito T. (2021) Optimal interpolation of global dissolved oxygen: 1965-2015.

This data is open for all. While it is not necessary, you can email taka.ito (at) eas.gatech.edu if you are using this data and are interested in future updates or bug fixes.

BCO-DMO Data Manager Processing Notes:
* Version 2 replaces version 1 on 2021-04-20. Version 1 of this dataset is still available as an archived copy at https://doi.org/10.26008/1912/bco-dmo.816978.1.
* Replaced version 1 data file  o2_aan_mcl1950-2016_0147_QC3.nc with new version 2 file o2_aan_mcl1965-2015_rev1.nc.

Major updates in this version (2) compared to Version 1:
** The new dataset includes error estimates for each grid cell due to mapping error, unresolved small-scale and high-frequency variability
** The new data set includes full water column data. (The previous version was from the surface to 1,000m depth. )
** Time range has changed from 1965 to 2015. 

NSF Abstract:

This project will use a combination of ocean observations and modeling to understand why the dissolved oxygen concentration in the ocean changes on timescales of years to decades. As oceans absorb heat, its oxygen content is expected to decline which will affect marine ecosystems and oxygen-sensitive biochemical reactions. In turn, biochemical processes can affect the oxygen level. Understanding why oceanic oxygen changes remains limited due to sparse data and the fact that it naturally fluctuates. Furthermore, state-of-the-art Earth System Models, used to develop future projections, struggle to skillfully simulate present-day oxygen distributions. Given model biases, there is a clear need to re-calibrate model-based projections based on informed interpretations of available observations. The intellectual merit of this study is to perform a series of computational simulations to quantify linkages between the patterns of climate variability, ocean heating, and oxygen content for different regions. In conjunction with a novel synthesis of available observational data, this modeling study will develop a more comprehensive model for evaluating oxygen variability and change, thereby reducing uncertainty in future projections under climate forcing scenarios. Broader impacts of this study includes education and outreach about decreasing ocean concentrations in the ocean and its disruptive impacts on ocean biogeochemical cycles and marine ecosystems. Two Ph.D. students and a postdoctoral scientist will be trained under the supervision of the PIs.

Ocean deoxygenation is a direct consequence of ocean heat uptake; as ocean waters warm, dissolved oxygen (O2) concentrations decline, with profound influences on marine ecosystem and redox-sensitive biogeochemical cycling. Existing observations are characterized by significant interannual to decadal fluctuations. Natural variability challenges detection and attribution of human-driven trends; however, it can also be interrogated to provide mechanistic insight. State-of-the-art Earth System Models still struggle to skillfully simulate present-day O2 distributions but these models are useful because they invoke mechanistic representations of key processes. The objective of this project is to improve our understanding of the mechanisms behind interannual and decadal variability of O2 globally and regionally. Low- and high-latitude regions exhibit distinct patterns in dissolved oxygen and ocean heat content. In order to isolate the impact of physical and biological controls on O2 variability, a suite of numerical simulations will be conducted, including some with a global eddy-resolving configuration. Combining observational and model-based analyses will enable quantitative assessments about the relation between ocean heat uptake and deoxygenation, and linkages to climate variability and trends.