地理学报 ›› 2003, Vol. 58 ›› Issue (4): 483-493.doi: 10.11821/xb200304001

• 环境遥感 •    下一篇

东海初级生产力遥感反演及其时空演化机制

李国胜1, 王芳1, 梁强1, 李继龙2   

  1. 1. 中国科学院地理科学与资源研究所,北京 100101;
    2. 中国水产科学院研究院,北京 100039
  • 收稿日期:2003-01-09 修回日期:2003-03-05 出版日期:2003-07-25 发布日期:2010-09-09
  • 作者简介:李国胜 (1963-), 男, 研究员, 博士生导师, 主要从事海陆相互作用及海洋环境遥感与GIS模拟研究。E-mail:ligs@igsnrr.ac.cn
  • 基金资助:

    国家“九五”科技专项资助项目 (HY126-06-04-04)

Estimation of Ocean Primary Productivity by Remote Sensing and Introduction to Spatio-temporal Variation Mechanism for the East China Sea

LI Guosheng1, WANG Fang1, LIANG Qiang1, LI Jilong2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Chinese Academy of Fishery Sciences, Beijing 100039, China
  • Received:2003-01-09 Revised:2003-03-05 Online:2003-07-25 Published:2010-09-09
  • Supported by:

    The Key Project for the National Ninth Five-Year Plan, No.HY126-06-04-04

摘要:

针对基于SeaWiFS的海洋叶绿素浓度SeaBAM模型反演结果,在中国东海海域分别建立了Ⅰ、Ⅱ类水体的修订模式,反演计算获得了我国东海海域1998年各月叶绿素浓度的分布,并根据真光层深度与海水漫射衰减系数之间的关系,利用SeaWiFS的K490遥感资料反演获得的1998年各月真光层深度的分布,在VGPM模型支持下,反演计算获得了中国东海海域1998年的逐月初级生产力时空分布以及全年累积初级生产力分布状况。对东海海域海洋初级生产力逐月时空变化特征及其影响机制的初步研究结果表明,整个东海海域初级生产力的逐月变化具有明显的双峰特征,表现为冬季最低,春季迅速上升达到最高,夏季略有下降,秋季又略有回升。海域初级生产力日平均值为560.03 mg/m2/d,远高于世界亚热带海域平均状况。年平均值为236.95 g/m2/a。控制东海海洋初级生产力时空变化的主要因素可能包括叶绿素浓度分布、温度条件、长江冲淡水变化,以及真光层深度、海流锋面过程等,不同海区初级生产力时空变化的主要控制因素有所不同。

关键词: 东海, 初级生产力, 叶绿素浓度, 遥感反演, 时空变化, 影响机理

Abstract:

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for Case-I and Case-II water respectively. The monthly chlorophyll distributions in the East China Sea in 1998 have been obtained from this improved model on the calculation results of SeaBAM. The relative coefficient analysis between the ship-measured chlorophyll concentration and the calculation results of the improved model shows that the relative coefficient is 0.5752, which means they have obvious dependence. The fact that the coefficient of linear regressive equation is nearly 1 confirms their dependence further. Therefore, it can be said for certain that the improved model is suitable for calculation of the chlorophyll distribution for Case-I and Case-II water in the East China Sea. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With the data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distribution in the East China Sea in 1998 have been obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m2/a, which is fit with the primary productivity obtained from the investigation in the Kuroshio zone in the East China Sea. The research on the seasonal variety mechanism of primary productivity shows that several elements that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River dilute water variety, the euphotic depth and ocean current variety etc. But the main influencing elements may be different in each local sea area.

Key words: East China Sea, primary productivity, chlorophyll concentration, remote sensing algorithms, spatio-temporal variation, mechanism