摘要
二氧化碳(CO_(2))是大气中主要温室气体之一,对全球气候变化具有重要影响,其浓度变化以及时空分布受到广泛关注。本文以CO_(2)浓度作为研究对象,以2002-2012年全球对流层CO_(2)浓度产品(AIR×3C2M 005)为数据源,对改进的CO_(2)浓度正弦估算模型进行逐像元参数率定与模拟,得到1992-2020年全球2°×2.5°分辨率的CO_(2)浓度月均值数据集,并利用站点观测数据对产品精度进行验证与分析。研究表明:(1)本文数据集与站点观测的CO_(2)浓度数据一致性较高,在拟合(2002-2012:R^(2)=0.94,RMSE=1.34 ppm)、回溯(1992-2001:R^(2)=0.92,RMSE=1.50 ppm)以及预测(2013-2019:R^(2)=0.93,RMSE=1.58 ppm)方面表现良好。(2)本数据集显示全球大气CO_(2)浓度具有明显的空间异质性,CO_(2)浓度高值区域主要位于北美洲北部,低值区域主要位于南半球中纬度地区。该数据集具有全球尺度、时序长、精度高等优点,可在一定程度上改进全球变化模拟中使用单一站点数值表征全球CO_(2)浓度的不足,为地理学、生态学等学科相关研究提供数据支持。
Carbon dioxide(CO_(2))is one of the main greenhouse gases in the atmosphere.It plays a crucial role in global climate change,of which temporal and spatial patterns have been paid great attention to.Taking CO_(2)concentration as the research object,this study developed a global gridded dataset of monthly CO_(2)concentration with a spatial resolution of 2°×2.5°from 1992 to 2020.The time series of CO_(2)concentration was simulated by an improved sinusoidal model,which was calibrated by the remotely-sensed product of tropospheric CO_(2)concentration from 2002 to 2012(AIR×3C2M 005),for each grid cell.Then,field-observed data of CO_(2)concentration were adopted to evaluate the accuracy of our product.The results showed that:(1)the CO_(2)concentration of our production was highly consistent with that observed at the stations.Especially,it performed well in the fitting(2002-2012:R^(2)=0.94,RMSE=1.34 ppm),reconstruction(1992-2001:R^(2)=0.92,RMSE=1.50 ppm)and prediction(2013-2019:R^(2)=0.93,RMSE=1.58 ppm)of CO_(2)concentration,respectively.(2)our data showed that the global atmospheric CO_(2)concentration exhibited an obvious spatial heterogeneity.The high value regions of CO_(2)concentration were mainly located in the northern of North America,while the low values dominated middle latitudes of the southern hemisphere.
作者
侯炜烨
金佳鑫
严涛
刘颖
Hou,W.Y.;Jin,J.X.;Yan,T.;Liu,Y.(College of Hydrology and Water Resources,Hohai University,Jiangsu,Nanjing 210024,China;National Earth System Science Data Center,National Science&Technology Infrastructure of China,Beijing 100101,China)
出处
《全球变化数据学报（中英文）》
CSCD
2022年第2期191-199,363-371,共18页
Journal of Global Change Data & Discovery
基金
中华人民共和国科学技术部(2018YFA0605402)
国家自然科学基金(41971374)
关键词
二氧化碳
遥感
模拟
AIRS
全球
carbon dioxide
remote sensing
simulation
AIRS
global
作者简介
通讯作者:金佳鑫,ABE-5925-2021,河海大学,国家科技基础条件平台-国家地球系统科学数据中心,jiaxinking@hhu.edu.cn
