| 基于2002-2018年MODIS数据的黄海叶绿素a时空变化研究 |
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| 引用本文： | 田洪阵,刘沁萍,Joaquim I. Goes,Helga do Rosario Gomes,杨萌萌.基于2002-2018年MODIS数据的黄海叶绿素a时空变化研究[J].海洋通报,2020,39(1):101-110. |
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| 作者姓名： | 田洪阵 刘沁萍 Joaquim I. Goes Helga do Rosario Gomes 杨萌萌 |
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| 作者单位： | 天津工业大学 经济与管理学院,天津 300387;哥伦比亚大学 拉蒙特多尔蒂地球观测站,美国 纽约 10964;天津工业大学 经济与管理学院,天津 300387;哥伦比亚大学 拉蒙特多尔蒂地球观测站,美国 纽约 10964;名古屋大学 环境学研究生院,日本 爱知 4648601 |
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| 基金项目： | 天津市哲学社会科学研究规划项目 （TJGL15-028）；天津市高等学校创新团队培养计划 （TD13-5038）；教育部人文社会科学研究项目 （16YJCZH082）；天津市高等学校人文社会科学研究项目 （20142111） |
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| 摘 要： | 浮游植物作为食物链的基础,对海洋生态系统具有重要影响。黄海作为我国重要的渔场,渔业资源面临枯竭的危险,因此对该区浮游植物进行研究具有重要意义。叶绿素a浓度是反映浮游植物生物量的重要指标。利用谷歌地球引擎平台对2002-2018年的MODIS Aqua叶绿素a浓度数据进行处理,并研究其时空分布与变化特征,然后结合区域气候、水文与地理特征以及海洋表面温度、风速、盐度、光合有效辐射和混合层厚度数据分析了其分布与变化的原因。研究发现:受陆源营养物质输入、近岸上升流以及黄海中央冷水团影响,叶绿素a浓度分布呈现由近岸向黄海中部递减特征;在季风、气候、水文的控制下,受风速、海洋表面温度、光合有效辐射、中央冷水团的影响,叶绿素a浓度的最大值出现在4月份,而最小值出现在6、7月份;受苏北沿岸海域海水污染和水体富营养化影响,沿岸海域盐度明显增加,海州湾叶绿素a浓度增速较大;影响黄海叶绿素a浓度变化的环境因子较复杂,除了部分月份存在显著的相关影响因子外,在全年和各季中不存在主导影响因子。
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| 关 键 词： | 叶绿素A浓度 MODIS AQUA 谷歌地球引擎 黄海 |
| 收稿时间： | 2019/6/14 0:00:00 |
| 修稿时间： | 2019/8/14 0:00:00 |
Temporal and spatial changes in chlorophyll-a concentrations in the Yellow Sea from 2002 to 2018 based on MODIS data |
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| TIAN Hong-zhen,LIU Qin-ping,Joaquim I. Goes,Helga do Rosario Gomes and YANG Meng-meng.Temporal and spatial changes in chlorophyll-a concentrations in the Yellow Sea from 2002 to 2018 based on MODIS data[J].Marine Science Bulletin,2020,39(1):101-110. |
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| Authors: | TIAN Hong-zhen LIU Qin-ping Joaquim I Goes Helga do Rosario Gomes and YANG Meng-meng |
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| Institution: | School of Economics and Management, Tianjin Polytechnic University, Tianjin 300387, China; Lamont Doherty Earth Observatory,Columbia University, New York 10964, USA,School of Economics and Management, Tianjin Polytechnic University, Tianjin 300387, China,Lamont Doherty Earth Observatory,Columbia University, New York 10964, USA,Lamont Doherty Earth Observatory,Columbia University, New York 10964, USA and Graduate School of Environmental Studies, Nagoya University, Aichi 4648601, Japan |
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| Abstract: | Phytoplankton, the base of the oceanic food chain, play a fundamental role in marine ecosystems. Since the Yellow Sea, an important place for fisheries in China, is facing the grim situation of depletion of fishery resources, it is critical to understand the distribution and changes of phytoplankton in this area. Chlorophyll-a (Chl-a) concentration is an important proxy for phytoplankton biomass. Chl -a data derived from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor on the Aqua satellite from 2002 to 2018 were processed using Google Earth Engine. The temporal and spatial distribution of and changes in Chl -a concentrations were analyzed. Combined with regional climate, hydrological and geographical features, sea surface temperature (SST), wind speed, salinity, photosynthetically available radiation (PAR) and mixed layer depth data were analyzed to investigate the causes of the distribution and variability of Chl-a concentrations in the Yellow Sea. It is found that Chl-a concentration decreased from the nearshore to the middle of the Yellow Sea, which was contributed by the input of terrestrial nutrients, nearshore upwelling and the Yellow Sea Cold Water Mass (YSCWM). Under the control of monsoons, climate and hydrology and influence of wind speed, SST, PAR and YSCWM, the peak of Chl-a concentration appeared in April and the minimum values were in June and July. Under the influence of pollution in the coastal areas of northern Jiangsu Province and the eutrophication in seawaters, the salinity of seawater increased in the nearshore waters and so did the Chl-a concentrations in Haizhou Bay. The environmental factors, which affected the changes in Chl-a concentrations in the Yellow Sea, were complicated. Significant correlation between environmental factors and Chla concentration only appeared in some months. There was no one dominant factor which could influence Chl-a concentrations in the whole years and seasons. |
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| Keywords: | chlorophyll-a MODIS Aqua Google Earth Engine Yellow Sea |
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