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首页> 外文期刊>Journal of Geophysical Research, C. Oceans: JGR >Twenty-Year Variations in Satellite-Derived Chlorophyll-a and Phytoplankton Size in the Bohai Sea and Yellow Sea
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Twenty-Year Variations in Satellite-Derived Chlorophyll-a and Phytoplankton Size in the Bohai Sea and Yellow Sea

机译:渤海和黄海中卫星衍生叶绿素-A和浮游植物大小的二十年变异

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摘要

Phytoplankton cell size is a useful ecological indicator for evaluating the response of phytoplankton community structure to environmental changes. Ocean-color remote observations and algorithms have allowed us to estimate phytoplankton size classes (PSCs) at decadal scale, helping us to understand their trends under ocean warming. Here a large data set of pigments, derived through high performance liquid chromatography, was collected in the Bohai Sea (BS) and Yellow Sea (YS) between 2014 and 2016. The data set was used to reparametrize the sea surface temperature (SST)-dependent three-component model of Brewin et al. (2017) to the region. The model was validated using independent in situ data set and subsequently applied to satellite chlorophyll-a data from Ocean Colour Climate Change Initiative, spanning from 1997 to 2016, to derive percentages of three PSCs to total chlorophyll-a. Monthly-averaged PSCs exhibited spatial-temporal variations in the study area, linked to topography, temperature, solar radiation, currents, and monsoonal winds. In the surface central south Yellow Sea (SYS), influenced by bottom Yellow Sea Cold Water Mass, tight relationships between PSCs and environmental factors were observed, where high SST, high sea level anomaly, low mixed-layer depth, and low wind speed resulted in higher proportions of nanoplankton and picoplankton from June to October. Significant interannual anomlies in PSCs were found associated with El Nino events in the central SYS, related to anomalies in SST. The refined model characterized 20-year variations in chlorophyll-a concentration and PSCs in complicated optical, hydrodynamic, and biogeochemical environments in the BS and YS.
机译:浮游植物细胞尺寸是一种用于评估浮游植物群落结构对环境变化的响应的有用生态指标。 Ocean-Color远程观测和算法使我们能够在Decadal Scale中估算Phytoplankton大小课程(PSC),帮助我们在海洋变暖下了解他们的趋势。这里,通过高效液相色谱衍生的大数据组颜料在2014年和2016年间在渤海(BS)和黄海(ys)中收集。数据集用于重新处理海面温度(SST) - Brewin等人的依赖性三组分模型。 (2017)到该地区。使用独立的原位数据集进行验证该模型,随后应用于卫星叶绿素 - 来自海洋气候变化倡议的数据,从1997年到2016年,从1997年到2016年,从而导致三个PSC的百分比达到总叶绿素-A。每月平均PSC在研究区域中表现出与地形,温度,太阳辐射,电流和季风风力相关的空间变化。在地面中央南黄海(SYS),受到底部黄海冷水质量的影响,观察到PSC和环境因素之间的紧密关系,其中高SST,高海平面异常,低混合层深度,低风速从6月到10月的纳米代和Picollankton的更高比例。发现PSC中的重大续际异常与中央系统中的EL NINO事件有关,与SST中的异常有关。精细模型表征了BS和YS中复杂的光学,流体动力学和生物地良好环境中的叶绿素-A浓度和PSC的20年变化。

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