南海北部夏季叶绿素a分布规律及影响因素

doi:10.11978/2019018

热带海洋学报 ›› 2019, Vol. 38 ›› Issue (6): 9-20.doi: 10.11978/2019018CSTR: 32234.14.2019018

所属专题：南海专题

南海北部夏季叶绿素a分布规律及影响因素

杨威^1,^2,³, 董园², 俎婷婷², 刘长建³, 修鹏²()

^1. 中国科学院大学, 北京 100049
^2. 热带海洋环境国家重点实验室(中国科学院南海海洋研究所), 广东广州 510301
^3. 国家海洋局南海调查技术中心, 广东广州 510300;

收稿日期:2019-02-21 修回日期:2019-05-23 出版日期:2019-11-20 发布日期:2019-11-26
通讯作者: 修鹏
作者简介:杨威(1986—), 男, 安徽省定远县人, 博士研究生, 从事海洋生态动力过程研究, E-mail: yangwei@scsio.ac.cn
基金资助:
中国科学院前沿科学重点研究项目(QYZDJ-SSW-DQC022);国家自然科学基金项目(41576003);广东省杰出青年基金项目(2014A030306049);广东省自然科学基金项目(2017A030313251);国家海洋局南海分局局长基金(1415);国家海洋局南海分局局长基金(18106);中国科学院百人计划

Distribution of Chlorophyll-a and its influencing factors in the northern South China Sea in summer

YANG Wei^1,^2,³, DONG Yuan², ZU Tingting², LIU Changjian³, XIU Peng²()

^1. University of Chinese Academy of Sciences, Beijing 100049, China
^2. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
^3. South China Sea Marine Survey and Technology Center, State Oceanic Administration, Guangzhou 510300, China

Received:2019-02-21 Revised:2019-05-23 Online:2019-11-20 Published:2019-11-26
Contact: Peng XIU
Supported by:
Key Research Program of Frontier Sciences, CAS(QYZDJ-SSW-DQC022);National Natural Science Foundation of China(41576003);Natural Science Funds for Distinguished Young Scholar of Guangdong Province(2014A030306049);Natural Science Foundation of Guangdong Province(2017A030313251);Director Foundation of South China Sea Branch, State Oceanic Administration(1415);Director Foundation of South China Sea Branch, State Oceanic Administration(18106);100 Talents Program of The Chinese Academy of Sciences

摘要/Abstract

摘要：

采用2002—2016年6—9月Aqua/MODIS叶绿素a产品分析珠江冲淡水在南海北部生态效应的季节及年际变化特征。6月来自陆源的营养物质在西南季风作用下向河口以东陆架区输运, 浮游植物增殖, 叶绿素a含量增大; 7月河口以东高浓度叶绿素a覆盖面积达到最大; 8月在减弱的珠江径流和环境风场共同影响下, 口门外海高浓度叶绿素a覆盖面积明显减小; 9月北部陆架区处于东北季风影响之下, 河口以西覆盖面积逐渐增大。通过线性回归分析可知, 珠江径流量是口门外海高浓度叶绿素a覆盖面积的主要影响因素, 且这种影响有一个月左右的滞后效应。显著大于(小于)多年平均的珠江径流量和环境风场等因素共同作用, 导致2008(2004)年表现为高浓度叶绿素a覆盖面积的极大值(极小值)年份。叶绿素a在南海北部陆架区的时空变化特征主要受冲淡水过程影响, 订正过的卫星叶绿素a产品可以用来讨论珠江冲淡水的季节及年际变化。

关键词: Aqua/Modis, 叶绿素a, 南海北部, 珠江冲淡水

Abstract:

Summer (from June to September) time series of 15 years (2002-2016) of chlorophyll-a (Chl a) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua products were collected to discuss seasonal and interannual variability of ecological response of the Pearl River Plume in the Northern South China Sea (NSCS). In June, under the influence of southwest monsoon, nutrients from the Pearl River Delta were transported eastward to the shelf area, phytoplankton bloomed and Chla increased. The coverage area over the shelf in the NSCS reached the maximum in July, and decreased in August when the river discharge and wind reduced. In September when the northeasterly wind prevailed in the NSCS, the coverage area with high concentration of Chla (AHCHL) west of the estuary increased. Linear regression analysis suggested that the river discharge was the main reason for driving the AHCHL variability with a time lag of about one month. The combined effect of stronger (weaker) than the multi-year mean river discharge and wind resulted in extremely large (small) AHCHL in 2008 (2004). Because the spatiotemporal variability of Chl a in the NSCS was mainly influenced by the Pearl River Plume, the quality controlled satellite Chl a products can be used to discuss the variability of the Pearl River Plume.

Key words: Aqua/MODIS, Chlorophyll-a, Northern South China Sea, Pearl River Plume

杨威, 董园, 俎婷婷, 刘长建, 修鹏. 南海北部夏季叶绿素a分布规律及影响因素[J]. 热带海洋学报, 2019, 38(6): 9-20.

YANG Wei, DONG Yuan, ZU Tingting, LIU Changjian, XIU Peng. Distribution of Chlorophyll-a and its influencing factors in the northern South China Sea in summer[J]. Journal of Tropical Oceanography, 2019, 38(6): 9-20.

图/表 12

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区域	6月	7月	8月	9月
口门以东	3.74	4.86	2.76	2.34
口门以西	1.78	1.71	1.70	1.83
口门外海	5.52	6.57	4.46	4.17

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南海北部夏季叶绿素a分布规律及影响因素

Distribution of Chlorophyll-a and its influencing factors in the northern South China Sea in summer

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