186 / 2024-09-10 22:44:35
An inter-comparison of the global ocean gridded dissolved oxygen data products
dissolved oxygen,gridded data,annual cycle
Session 15 - Ocean deoxygenation: drivers, trends, and biogeochemical-ecosystem impacts
Abstract Accepted
JUAN DU / Institute of Atmospheric Physics, Chinese Academy of Sciences
Lijing Cheng / Institute of Atmospheric Physics, Chinese Academy of Sciences
Takamitsu Ito / 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.
Johnson Sharp / University of Washington
Christopher Roach / Institute For Marine and Antarctic Studies, Hobart, Tasmania, Australia
Shoshiro Minobe / Hokkaido University
Siv K. Lauvset / University of Bergen and Bjerknes Centre for Climate Research
Seth Bushinsky / University of Hawai’i at Mānoa
Zachary Nachod / University of Hawaii at Manoa
Ocean dissolved oxygen (O2) changes at various spatiotemporal scales have been studied using various observationally-based gridded data products. The existing O2 data products used observations from different instruments and applied different data processing techniques such as vertical interpolation methods, quality control processes, bias correction approaches, land-ocean masks, mapping methods, etc. Because each of these factors contribute to the resulting data product, it is still unclear how robust ocean O2 changes can be represented. This study aims to compare available gridded ocean dissolved oxygen products in representing the climatology, seasonal cycle, inter-annual variability, and trends of the ocean oxygen changes from 0-2000 m. A common set of metrics is collaboratively developed to facilitate the comparative analyses, which will enable further planned intercomparison activities by the community including Dissolved Oxygen Maps Intercomparison Project Phase 1(DOMIP-1). The datasets adopted here for comparison include WOA18 (World Ocean Atlas 2018), WOA23 (World Ocean Atlas 2023), IAP (Institute of Atmospheric Physics), GOBAI (Gridded Ocean Biogeochemistry from Artificial Intelligence), GLODAP (Global Ocean Data Analysis Project) and RB (Roach and Bindoff). This comparison provides a baseline (reference) for understanding the contribution of the individual error sources to the oxygen change estimates. The results will also be a starting point for resolving the uncertainty of the budget for ocean oxygen climatology and change estimates.