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Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information.

Research paper by Huan-Huan HH Chen, Rui R Tang, Hao-Ran HR Zhang, Yi Y Yu, Yuntao Y Wang

Indexed on: 01 Jul '20Published on: 01 Jul '20Published in: Journal of visualized experiments : JoVE



Abstract

Satellite observations offer a great approach to investigate the features of major marine parameters, including sea surface chlorophyll (CHL), sea surface temperature (SST), sea surface height (SSH), and factors derived from these parameters (e.g., fronts). This study shows a step-by-step procedure to use satellite observations to describe major parameters and their relationships in seasonal and anomalous fields. This method is illustrated using satellite datasets from 2002-2017 that were used to describe the surface features of the South China Sea (SCS). Due to cloud coverage, monthly averaged data were used in this study. The empirical orthogonal function (EOF) was applied to describe the spatial distribution and temporal variabilities of different factors. The monsoon wind dominates the variability in the basin. Thus, wind from the reanalysis dataset was used to investigate its driving force on different parameters. The seasonal variability in CHL was prominent and significantly correlated with other factors in a majority of the SCS. In winter, a strong northeast monsoon induces a deep mixed layer and high level of chlorophyll throughout the basin. Significant correlation coefficients were found among factors at the seasonal cycle. In summer, high CHL levels were mostly found in the western SCS. Instead of a seasonal dependence, the region was highly dynamic, and factors correlated significantly in anomalous fields such that unusually high CHL levels were associated with abnormally strong winds and intense frontal activities. The study presents a step-by-step procedure to use satellite observations to describe major parameters and their relationships in seasonal and anomalous fields. The method can be applied to other global oceans and will be helpful for understanding marine dynamics.