Chen Huan-Huan, Tang Rui, Zhang Hao-Ran, Yu Yi, Wang Yuntao
College of Oceanography, Hohai University; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources.
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources.
J Vis Exp. 2020 Jun 13(160). doi: 10.3791/61172.
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.
卫星观测为研究主要海洋参数的特征提供了一种很好的方法，这些参数包括海表面叶绿素（CHL）、海表面温度（SST）、海表面高度（SSH）以及从这些参数导出的因子（如锋面）。本研究展示了一个逐步的程序，用于利用卫星观测来描述季节性和异常场中的主要参数及其关系。使用2002 - 2017年的卫星数据集对该方法进行了说明，这些数据集用于描述南海（SCS）的表面特征。由于云覆盖，本研究使用了月平均数据。应用经验正交函数（EOF）来描述不同因子的空间分布和时间变化。季风主导了该海域的变化。因此，利用再分析数据集中的风来研究其对不同参数的驱动力。CHL的季节变化显著，并且在南海的大部分区域与其他因子显著相关。在冬季，强烈的东北季风在整个海域诱导出深厚的混合层和高叶绿素水平。在季节周期中各因子之间发现了显著的相关系数。在夏季，高CHL水平主要出现在南海西部。该区域并非呈现季节性依赖，而是高度动态的，并且在异常场中各因子显著相关，以至于异常高的CHL水平与异常强风及强烈的锋面活动相关。该研究展示了一个逐步的程序，用于利用卫星观测来描述季节性和异常场中的主要参数及其关系。该方法可应用于其他全球海洋，将有助于理解海洋动力学。
