数据处理方法不确定性对CO2通量组分估算的影响

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%.

Impacts of uncertainty in data processing on estimation of CO2 flux components.

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 gC·m^-2·a^-1 (0.84%-65.31%), 4.06-30.28g 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 ofgrassland ecosystem was more sensitive to the parameter setting of data processing method, and the relative estimation deviation of annual gross ecosystem exchangeand ecosystem respiration induced by the uncertainty in data processing was 3.88%-11.41% and 6.45%-24.91%, respectively.