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Position: Home > Articles > Impacts of uncertainty in data processing on estimation of CO_2 flux components. Chinese Journal of Applied Ecology 2010,21 (9) 2389-2396

数据处理方法不确定性对CO_2通量组分估算的影响

作  者：
刘敏;何洪林;于贵瑞;孙晓敏;朱旭东;张黎;赵新全;王辉民;石培礼;韩士杰
单  位：
中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室;中国科学院研究生院;中国科学院沈阳应用生态研究所;中国科学院西北高原生物研究所
关键词：
涡度相关技术;CO2通量;数据处理;方差分析;不确定性
摘  要：
基于中国陆地生态系统通量观测研究网络(ChinaFLUX)4个站点(2个森林站和2个草地站)的涡度相关通量观测资料,分析了CO2通量数据处理过程中异常值剔除参数设置、夜间摩擦风速(u*)临界值(u*c)确定及数据插补模型选择对CO2通量组分估算的影响.结果表明:3种数据处理方法均对净生态系统碳交换量(NEE)年总量估算有显著影响,其中u*c确定是影响NEE估算的重要因子;异常值剔除、u*c确定及数据插补模型选择导致NEE年总量估算偏差分别为0.62～21.31 g C.m-2.a-1(0.84%～65.31%)、4.06～30.28 g C.m-2.a-1(3.76%～21.58%)和0.69～27.73 g C.m-2.a-1(0.23%～55.62%),草地生态系统NEE估算对数据处理方法参数设置更敏感;数据处理方法不确定性引起的总生态系统碳交换量和生态系统呼吸年总量估算相对偏差分别为3.88%～11.41%和6.45%～24.91%.
译  名：
Impacts of uncertainty in data processing on estimation of CO_2 flux components.
作  者：
LIU Min1,2,HE Hong-lin1,YU Gui-rui1,SUN Xiao-min1,ZHU Xu-dong1,2,ZHANG Li1,ZHAO Xin-quan3,WANG Hui-min1,SHI Pei-li1,HAN Shi-jie4 (1Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;2Graduate University of Chinese Academy of Sciences,Beijing 100049,China;3Northwest Plateau Institute of Biology,Chinese Academy of Sciences,Xining 810001,China;4Institute of Applied Ecology,Chinese Academy of Sciences,Shenyang 110016,China).
关键词：
eddy covariance technique;CO2 flux;data processing;variance analysis;uncertainty.
摘  要：
Based on the eddy covariance observations at 4 sites(2 forested sites and 2 grassland sites) in Chinese Terrestrial Ecosystem Flux Research Network(ChinaFLUX),this paper analyzed the effects of three data processing methods,i.e.,spike detection,threshold(u*c) determination of nocturnal friction velocity(u*),and gap-filling model selection,on the estimation of CO2 flux components.All the three methods had significant impacts on the estimation of annual net ecosystem exchange(NEE),and the determination of(u*c) was an important factor affecting the annual NEE estimation.The estimation deviation of the annual NEE caused by spike detection,determination of(u*c),and gap-filling model selection was 0.62-21.31 g C·m-2·a-1(0.84%-65.31%),4.06-30.28 g C·m-2·a-1(3.76%-21.58%),and 0.69-27.73 g C·m-2·a-1(0.23%-55.62%),respectively.Comparing with that of forested ecosystem,the NEE estimation of grassland ecosystem was more sensitive to the parameter setting of data processing method,and the relative estimation deviation of annual gross ecosystem exchange and ecosystem respiration induced by the uncertainty in data processing was 3.88%-11.41% and 6.45%-24.91%,respectively.

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