Articles | Volume 21, issue 3
https://doi.org/10.5194/bg-21-747-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-747-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Feb 2024
Research article |
| 12 Feb 2024
| 12 Feb 2024
Underestimation of multi-decadal global O2 loss due to an optimal interpolation method
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
Hernan E. Garcia
NOAA, National Centers for Environmental Information, Silver Springs, Maryland, USA
Zhankun Wang
NOAA, National Centers for Environmental Information, Silver Springs, Maryland, USA
Shoshiro Minobe
Department of Natural History Sciences, Graduate School of Science, Hokkaido University, Sapporo, Japan
Department of Earth and Planetary Sciences, Faculty of Science, Hokkaido University, Sapporo, Japan
Matthew C. Long
Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, Colorado, USA
Just Cebrian
NOAA, National Centers for Environmental Information, Silver Springs, Maryland, USA
Northern Gulf Institute, Mississippi State University, Stennis Space Center, Mississippi, USA
Vesta, PBC, San Francisco, California, USA
James Reagan
NOAA, National Centers for Environmental Information, Silver Springs, Maryland, USA
Tim Boyer
NOAA, National Centers for Environmental Information, Silver Springs, Maryland, USA
Christopher Paver
NOAA, National Centers for Environmental Information, Silver Springs, Maryland, USA
Courtney Bouchard
NOAA, National Centers for Environmental Information, Silver Springs, Maryland, USA
Yohei Takano
Los Alamos National Laboratory, Los Alamos, New Mexico, USA
Seth Bushinsky
School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, Honolulu, Hawaii, USA
Ahron Cervania
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
Curtis A. Deutsch
Department of Geosciences, Princeton University, Princeton, New Jersey, USA
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Short summary
This study aims to estimate how much oceanic oxygen has been lost and its uncertainties. One major source of uncertainty comes from the statistical gap-filling methods. Outputs from Earth system models are used to generate synthetic observations where oxygen data are extracted from the model output at the location and time of historical oceanographic cruises. Reconstructed oxygen trend is approximately two-thirds of the true trend.
This study aims to estimate how much oceanic oxygen has been lost and its uncertainties. One...
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