On October 14, 2024, Liu’ group published a research paper entitled " Satellite retrieval of oceanic particulate organic carbon: Towards an accurate and seamless dataset for the global ocean " in the journal Science of The Total Environment. Zhengxin Zhang, a postgraduate student from Shenzhen University, is the first author. Huizeng Liu is the corresponding author. Shenzhen University is the primary affiliation. Co-authors of the paper include Academician Li Qingquan, Prof. Wu Guofeng, Dr. Zhang Yu, and Wang Yongquan from Shenzhen University, Prof. He Xianqiang from Second Institute of Oceanography, Ministry of Natural Resources, and Dr. Wang Yanru from Shenzhen Marine Development & Promotion Center.
As the world's largest carbon reservoir, ocean plays a crucial role in the global carbon cycle by interacting with the atmosphere and biosphere, significantly impacting the global climate change. The intricate interplay and robust feedback mechanisms among carbon fluxes and transformations within the oceanic carbon cycle challenge our ability to predict global climate system behavior and its evolution throughout the Earth's history. These interactions obscure numerous potential physical and biogeochemical processes underlying ocean observations, which reflect carbon cycle processes. Meanwhile, there are different forms and functions of marine carbon at various stages of the ocean carbon cycle. Therefore, studies in the spatiotemporal variations and the roles of each carbon forms would improve our understanding of the carbon export and sequestration in global carbon cycle.
Satellite remote sensing has been demonstrated to be an effective technique for the retrieval of surface oceanic POC concentration. However, the complex spatiotemporal variations of the relationships between POC and oceanic optical properties across different waters posed challenges for accurate retrieval of POC concentration from satellite observations. Additionally, interference factors, such as cloud cover and sun glint, resulted in severe data missing problems and impeding daily coverage of the global ocean.
The research group collected global in situ POC measurements and mainstream ocean color satellite remote sensing products from MODIS-Terra and Aqua. They extracted synchronous observation datasets from both satellite and in situ measurements, identified the bio-optical indicators suitable for the remote sensing inversion of oceanic POC, applied artificial intelligence methods to develop accurate remote sensing inversion models for oceanic PON concentrations, and explored the possibility of using the empirical orthogonal function interpolation technique (DINEOF) to reconstruct satellite-retrieved POC data to generate gap-free global oceanic POC products. This study provided a suite of long time-series accurate and seamless POC products across the global ocean, which would contribute to better and comprehensive understanding the global oceanic POC variations and oceanic carbon cycle.
This work was supported in part by the Guangdong Major Project of Basic and Applied Basic Research (Grant No. 2023B0303000017), the National Natural Science Foundation of China (Grant No. 42371337 and 42471387), the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2024A1515011388 and 2023A1515011946) and the Shenzhen Science and Technology Program (Grant No. JCYJ20230808105709020).
Research findings have been published in the journal of Science of The Total Environment:
Zhang Zhengxin, Liu Huizeng*, He Xianqiang, Zhang Yu, Wang Yanru, Wang Yongquan, Liang Feifei, Li Qingquan, Wu Guofeng, Satellite retrieval of oceanic particulate organic carbon: Towards an accurate and seamless dataset for the global ocean. Sci Total Environ, 2024, 176910, 0048-9697, https://doi.org/10.1016/j.scitotenv.2024.176910
Figure 1. Accurate and seamless satellite retrieval of oceanic particulate organic carbon across the global surface ocean
