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essd-15-1711-2023.pdf

🔗 Source: essd.copernicus.org

📊 Size: 20.55 MB

📄 Pages: 21 pages

⬇️ Downloads: 51

Summary

Researchers used a machine-learning-based method to reconstruct a dataset of monthly sea surface partial pressure of CO2 (pCO2) in the South China Sea from 2003 to 2020, with a spatial resolution of 0.05° × 0.05°. The model used remote-sensing-derived sea surface salinity, temperature, and chlorophyll, as well as atmospheric pCO2 and time labels. The reconstruction was validated with three independent testing datasets, showing a root mean square error (RMSE) of ~10 µatm, which is ~50% smaller than that between remote-sensing-derived data and in situ data. The study found that the South China Sea is a weak source of atmospheric CO2, but the northern part acts as a sink, with a trend of increasing strength over the past 2 decades.

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Description

Researchers used a machine-learning-based method to reconstruct a dataset of monthly sea surface partial pressure of CO2 (pCO2) in the South China Sea from...

Technical Information

File Format: PDF
File Size: 20.55 MB
Pages: 21
Language: EN
Total Downloads: 51
Last Updated: 3 weeks ago

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