Ocean Acidification and Sea Surface pH assessment - Ocean Acidification & Hypoxia

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Research Background

Since the onset of the Industrial Revolution, anthropogenic activities such as the combustion of fossil fuels and deforestation have resulted in the release of excessive CO₂ into the atmosphere. Approximately one-third of this CO₂ has been absorbed by the oceans, a process known as carbon sequestration, which has mitigated the effects of global warming and climate change. However, the absorption of anthropogenic CO₂ by seawater has led to the reduction of seawater pH and carbonate ion concentrations, causing a phenomenon called ocean acidification. The pH of seawater is a crucial parameter for quantifying the concentration of hydrogen ions in water. The distribution of pH in seawater profiles is non-uniform, typically exhibiting higher pH values at the surface and lower values at the seafloor. The depth at which the minimum pH is observed varies across different regions due to varying biogeochemical characteristics. As depth increases, seawater experiences increased pressure and decreased temperature, resulting in a gradual increase in pH; however, it remains significantly lower than the pH values observed at the sea surface. Consequently, deep seawater tends to exhibit more pronounced acidification than surface waters, and the pH of surface seawater often reflects certain characteristics of the deep ocean environment.

To address the scientific challenge of constructing a high-precision global remote sensing retrieval model and product for sea surface pH, this study proposes a research approach that expands the existing dataset of measured pH values using a measured pCO₂ dataset. Building upon this dataset, a machine learning model for remote sensing inversion of pH is developed to produce remote sensing products of sea surface pH. The distribution and long-term changes of global sea surface pH are subsequently analyzed and discussed.

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Fig1 Research Route Map
Fig 2: Spatial Distribution of Monthly Average Sea Surface pH in Climatology

Scientific Progress

Ocean acidification and sea surface pH measurement mainly include global sea surface pH parameters, using the total scale. The global sea surface pH dataset has a spatial resolution of 0.25° × 0.25° and covers the time range from 2003 to 2019. This dataset calculated the reconstructed sea surface pH navigation dataset through the seawater carbonate system, utilizing the measured pCO2 of the global sea surface pCO2 navigation dataset released by LDEO and the thermohaline reconstructed TA. The random forest model was then used to model this dataset. The model training reached the accuracy of R²=0.96 and RMSE=0.008. The model was also independently verified using GLODAP's sea surface pH dataset, with results of R²=0.54 and RMSE=0.029.

The input data of the global sea surface pH dataset are the monthly average SST and Chla products of MODIS-Aqua and the MLD reanalysis product of CMEMS (GLOBAL_MULTIYEAR_PHY_001_030). The sea surface pH products are produced through the random forest model. Compared with similar seawater surface pH products from JMA and CMEMS, it has obvious advantages in spatial resolution and accuracy. This dataset can be applied to the study of global seawater carbon cycle and seawater inorganic carbon system, and also provides data support for marine ecology and climate change processes.

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References

Jiang, Zhiting, Zigeng Song, Yan Bai, Xianqiang He, Shujie Yu, Siqi Zhang, and Fang Gong. 2022. “Remote Sensing of Global Sea Surface PH Based on Massive Underway Data and Machine Learning.” Remote Sensing 14 (10). https://doi.org/10.3390/rs14102366.

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Research Background

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Scientific Progress

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