Satellite remote sensing of the aquatic pCO2 in the basin of the South China Sea

Abstract

The South China Sea (SCS) is one of the largest marginal seas in the world, and the air-sea CO 2 flux in the SCS may contribute significantly to the global air-sea CO 2 flux. In the past decade, many researches on the aquatic p CO 2 and air-sea CO 2 flux mainly in the north SCS were carried out based on the underway measurement of the p CO 2 , and the results revealed that the SCS is a source of the CO 2 as a whole in the annual scale. However, the air-sea CO 2 flux is high spatial variability in the SCS, for example, the north shelf of the SCS is a CO 2 sink while the basin is a source. To monitor the spatial and temporal variations of the air-sea CO 2 flux in the SCS, few satellite remote sensing algorithms have been developed to estimate the aquatic p CO 2 in the north SCS. However, these algorithms are all the empirical models which depend on the training dataset from the in situ measurement. In this study, we apply the semi-analytical algorithm MeSAA to retrieve the aquatic p CO 2 in the SCS basin. The MeSAA algorithm was proposed by the Bai et al. (2016) and was evidenced to be widely applicable to the different marginal seas including the East China Sea and Bering Sea. Based on the underway measured aquatic p CO 2 and water temperature, we found that the variation of the p CO 2 in the SCS basin is mainly controlled by the temperature. In addition, the increase of the atmosphere p CO 2 can also contribute the systematical increase of the aquatic p CO 2 . Therefore, we established a semi-analytical algorithm for the aquatic p CO 2 retrieval in the SCS basin, which considers the thermodynamic effect and air-sea CO 2 fluxes. The results showed that the thermodynamic effect in the SCS basin was consistent with the theoretical result with the aquatic p CO 2 increasing 4.23% for the 1°C rising of the water temperature. Moreover, the satellite-retrieved aquatic p CO 2 match well with the in situ p CO 2 . Based on the established algorithm, the monthly time-series of the aquatic p CO 2 in the SCS basins from 2003 to 2016 were generated from the MODIS datasets from both the Aqua and Terra satellite, and the long-term trends of the aquatic p CO 2 in the different parts of the SCS basin were analyzed.