Optimal interpolation of global dissolved oxygen: 1965–2015. (31st August 2021)

• Record Type: Journal Article
• Authors: Ito, Takamitsu
• Is Part Of: Geoscience data journal. Volume 9:Number 1(2022)
• Page Start: 167
• Page End: 176
• Publication Date: 2021-08-31
• Subjects: climate change impacts -- ocean deoxygenation -- optimal interpolation; Earth sciences -- Research -- Periodicals; Earth sciences -- Data processing -- Periodicals; Earth sciences -- Documentation -- Periodicals; 550.28557
• DOI: 10.1002/gdj3.130
• Languages: English
• ISSNs: 2049-6060

Abstract

Abstract: Oxygen inventory of the global ocean has declined in recent decades potentially due to the warming‐induced reduction in solubility as well as the circulation and biogeochemical changes associated with ocean warming and increasing stratification. Earth System Models predict continued oxygen decline for this century with profound impacts on marine ecosystem and fisheries. Observational constraint on the rate of oxygen loss is crucial for assessing the ability of models to accurately simulate these changes. There are only a few observational assessments of the global oceanic oxygen inventory reporting a range of oxygen loss. This study develops a gridded data set of dissolved oxygen for the global oceans using optimal interpolation method. The resulting gridded product includes full‐depth map of dissolved oxygen as 5‐year moving average 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. This estimate is more conservative than previous works. In this study, the grid points far from the observations are essentially set equal to zero anomaly from the climatology. Calculating global inventory with this approach produces a relatively conservative estimate; thus, the results from this study likely provide a useful lower bound estimate of the global oxygen loss. Abstract : This study develops a gridded data set of dissolved oxygen for the global oceans using optimal interpolation method.