Seasonal changes and controlling factors of sea surface pCO2 in the Yellow Sea

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Qin, B.Y.^1 ; Tao, Z.^1 ; Li, Z.W.^1 ; Yang, X.F.^1

State Key Laboratory of Remote Sensing Science, Chinese Academy of Sciences, Beijing Normal University, Beijing, China^1

关键词: Chlorophyll-a concentration;    Correlation analysis;    Global carbon cycle;    Negative correlation;    Positive correlations;    Root mean squared errors;    Sea surface temperature (SST);    Shipboard measurements;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012025/pdf
DOI  :  10.1088/1755-1315/17/1/012025

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Sea surface partial pressure of carbon dioxide (pCO2) is an important parameter in the ocean carbon cycle system. By using accurate global sea surface pCO2data, we can directly estimate the ratio of net CO2uptake of global ocean, which can provide a support for further research of global carbon cycle. This article mainly discussed the seasonal changes of sea surface pCO2and the relationships of pCO2with sea surface temperature (SST) and chlorophyll-a concentration (Chla) in the Yellow Sea during winter, spring and summer, based on the data obtained by the shipboard measurements in February, May and August 2010. The results showed that the correlations of pCO2with SST and Chla were different in different seasons. SST and pCO2had a strong positive correlation in the range of higher SST for both spring and summer, and a relative weak correlation in winter, which can be fitted by a quadratic curve in each season. There was a linear correlation between pCO2and Chla in each season. The data of pCO2and Chla showed a negative correlation during winter and summer, and a positive one during spring. Based on the correlation analyses, we proposed a regression equation of pCO2with SST and Chla as two parameters in the Yellow Sea for summer, which showed a root mean squared error (RMSE) of 16.68μatm when the shipboard-observed data were used. By using the satellite-observed SST and Chla instead of the field data, the RMSE of the result is 21.46μatm.