Scientists have discovered that the Southern Ocean releases 40% more carbon dioxide during winter than previously estimated. Using laser satellite data and machine learning, researchers pierced the polar darkness to reveal this hidden emission burst. The findings reshape understanding of the ocean's role in the global carbon cycle.
A new study published in Science Advances on November 5 reveals that the Southern Ocean emits far more carbon dioxide (CO2) during the lightless Antarctic winter than previously believed, with wintertime releases underestimated by up to 40%. Led by scientists from the Second Institute of Oceanography, Ministry of Natural Resources (SIO-MNR), and the Nanjing Institute of Geography and Limnology (NIGLAS) of the Chinese Academy of Sciences, the research addresses a major gap in global CO2 flux calculations.
The Southern Ocean plays a crucial role in regulating Earth's carbon balance by absorbing a significant portion of human-emitted CO2. However, its winter behavior has remained an 'observational black box' due to complete darkness and extreme weather, which prevent traditional passive satellite sensors—reliant on reflected sunlight—from gathering data. To overcome this, the team analyzed 14 years of data from the LIDAR instrument on NASA's CALIPSO mission, which uses laser pulses to measure ocean properties even in polar night, combined with machine learning for the first continuous, observation-based record of winter CO2 exchange.
The results highlight regional variations through a new 'three-loop framework.' In the Antarctic Loop (south of 60°S), sea ice and salinity drive CO2 exchange. The Polar Front Loop (45°S-60°S) sees influences from atmospheric CO2 and biological activity like chlorophyll. North of 45°S in the Subpolar Loop, sea surface temperature dominates.
"Our findings suggest that the Southern Ocean's role in the global carbon cycle is more complex and dynamic than previously known," said Prof. Kun Shi of NIGLAS. This data could refine global carbon budgets, improving climate projections used by bodies like the Intergovernmental Panel on Climate Change (IPCC) and demonstrating the potential of active satellite sensing with AI for remote environmental monitoring.