摘要
研究海洋初级生产力,对于理解全球生态系统健康状况、生物化学循环和气候变化具有重要意义。笔者于2014年发表了用于海洋初级生产力遥感监测的ABPM模型,该模型利用MODIS卫星2003-2012年月度产品数据中的浮游植物吸收系数、真光层深度、490 nm漫衰减系数和光合有效辐射4类产品数据和2009年世界海洋地图集中的氮浓度剖面观测数据,计算出全球海洋初级生产力遥感监测数据集。该数据集包括了近10年来共120个月的全球海洋初级生产力9 km分辨率月度空间分布数据。为了检验定量反演的精度,本文应用海表三个固定站点和三条海上走航的实测数据对数据集结果进行验证。三个固定站点包括美国夏威夷海洋站点、大西洋百慕大群岛站点和美国加利福尼亚站点;三条海上走航数据包括地中海海域走航(DYFAMED)、南极斯科舍海域走航(AMLR)和南极帕尔默站海域走航(WAP)数据。验证结果表明,用ABPM模型计算得到的全球海洋初级生产力遥感监测数据比其他模型计算所得的数据精度较高。由于该数据反映了全球海表碳循环过程中海洋生物固碳量的时空变化特征,因此,可以为全球碳循环、气候变化和生物资源潜在生产力研究提供基础性的参考数据。
The research of ocean primary productivity is important for understanding the global ecosystem health, biogeochemical cycles and climate change. The global ocean primary productivity dataset was developed based on the monthly remote sensing products of MODIS(phytoplankton absorption coefficient, euphotic depth, diffuse attenuation coefficient at 490 nm and photosynthetically available radiation) from 2003 to 2012 with the model support from phytoplankton absorption model of ocean primary productivity(ABPM). The dataset includes monthly global ocean primary productivity data. The total cover periods of the data are ten years, 120 months and the spatial resolution is 9 km. To test the quantitative inversion accuracy, the research team collected the data of three fixed sites and three on deck monitoring sites to verify the accuracy of the dataset results. Three fixed sites are Hawaii(USA), Bermuda(Atlantic), California(USA). Three on deck monitoring sites are Atmospheric Dynamics and Fluxes in the Mediterranean Sea(DYFAMED), Antarctic Marine Living Resources Program(AMLR) and Antarctic Marine Living Resources Program(AMLR). Verification results demonstrate that there is more accuracy of global ocean primary productivity calculated by the ABPM model. The dataset can reflect the spatial and temporal variations of ocean biological carbon fixation in the process of global sea surface carbon cycle. So, it can be used as a basic reference data for the research of the global carbon cycle, climate change and biological resources potential productivity.
作者
陶醉
周翔
马胜
Tao Z.;Zhou X.;Ma S.(State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, ChineseAcademy of Sciences, Beijing 100101, China)
出处
《全球变化数据学报（中英文）》
2017年第2期149-156,168-175,共16页
Journal of Global Change Data & Discovery
基金
国家自然科学基金(41501389)
遥感科学国家重点实验室开放基金(OFSLRSS201509)
关键词
全球
海洋
初级生产力
遥感监测
月度数据
global
ocean
primary productivity
remote sensing monitoring
monthly data
作者简介
通讯作者:陶醉,L-4530-2016,中国科学院遥感与数字地球研究所,taozui@radi.ac.cn
