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研究调查了Ekman流对浮游植物生态动力过程的驱动机制。采用新的光学遥感算法提取浮游植物光学有效信息。该算法结合了近红外波段的浮游植物荧光信号以及可见光部分的弹性散射的辐射传输模型,通过两次迭代优化算法,提取浮游植物光学信号。采用辐射传输软件Hydrolight对海水水下光场进行了数值模拟,并结合新算法对模拟数据进行了对比分析。结果表明,新算法较好地表征了浮游植物叶绿素光学参数。利用MERIS光学遥感数据并结合了动力学参数,利用该算法分析了强台风尼格对我国海域浮游植物分布的影响。研究结果表明,Ekman流是我国海域浮游植物分布异常的原因之一。
The study investigated the driving mechanism of Ekman flow on phytoplankton ecological dynamics. Optical Retrieval of Phytoplankton Optically Effective Information Using a New Optical Remote Sensing Algorithm. The algorithm combines the fluorescence signal of phytoplankton in the near infrared band and the elastic scattering radiation transmission model of visible light. The phylogeny of the phytoplankton is extracted by two iterative optimization algorithms. The seawater underwater optical field was numerically simulated by using the radiation transmission software Hydrolight, and the simulation data were compared with the new algorithm. The results show that the new algorithm better characterizes phytoplankton chlorophyll optical parameters. Using MERIS optical remote sensing data combined with kinetic parameters, this algorithm is used to analyze the influence of strong typhoon Niger on phytoplankton distribution in China. The results show that Ekman flow is one of the reasons for the abnormal distribution of phytoplankton in China.