中文摘要：

[目的]通量塔观测的CO2通量数据具有较高的缺失比率,给通量塔数据的应用带来困难,因此,需要建立合理的插补方法对缺失数据进行插补,获取完整和可靠的CO2通量数据。本研究分析了不同参数估计窗口大小条件下基于夜间数据（NB）和基于白天数据（DB）的插补方法对CO2通量估算的影响,从而为选择最优的插补方法提供参考依据。[方法]以2011年毛竹林生态系统碳通量塔观测的净生态系统交换量、温度以及光合有效辐射为基础数据,给定不同的参数估计窗口大小,采用NB和DB插补方法对CO2通量缺失数据进行插补,以实测数据评价参数估计窗口大小对CO2通量估算的影响。[结果]参数估计窗口影响插补的波动程度随窗口增大而降低,窗口过大时结果不能体现局部变化,过小时结果出现异常,最优值与观测数据缺失量密切相关;在本研究案例情况下,对于NB方法,生态系统总呼吸速率Re插补的最优移动窗口和参数估计窗口分别为15天和90天,总初级生产力GPP插补的最优移动窗口和参数估计窗口分别为2天和4天;而对于DB方法,最优移动窗口和参数估计窗口分别为2天和60天;NB方法估算的年尺度GPP和Re分别高出DB方法的13.8%和26.8%,净生态系统交换量低于DB方法的32.2%;NB和DB方法得到的白天净生态系统交换量非常接近,但两者的Re分量具有较大差异。[结论]缺失数据比率对参数估计窗口大小的选择具有重要影响。通量塔缺失数据插补时,综合考虑数据缺失比率和下垫面的碳通量季节变化特征,选择合适的插补方法及其参数估计窗口对提高CO2通量估算准确性具有帮助。

英文摘要：

[Objective]Due to high ratio of missing CO2 flux data,a suitable interpolation method is necessary to collect continuous and reliable CO2 flux data. The objective of this study is to analyze effect of interpolation （ nighttime data-based method （ NB） and daytime data-based method （ DB） ） with different window sizes for fitting parameters on CO2 flux data estimation,which provides a basis for selecting suitable interpolation method. [Method]]Based on the data of net ecosystem exchange （ NEE） ,temperature and photosynthetically active radiation obtained from the carbon flux tower for moso bamboo forest ecosystem in 2011,interpolation （ NB and DB ） with different time window sizes for fitting parameters were used to estimate missing data through interpolation. Then,the estimated data from interpolation was compared with the observed data.[Results]Time window size for fitting parameter has an effect on the fluctuation of CO2 flux. Fluctuation of CO2 flux decreases as time window size increases. If the time window size is too large,the result can not reflect the local specific variation in CO2 flux,and if the time window size is too small,it can get abnormal CO2 flux.＆amp;nbsp;The optimal time window size is closely related to the amount of missing data. As to this case study,for NB method,the 15-day moving window size and 90-day window size for fitting parameters are suitable to interpolate ecosystem respiration （ Re） . The 2-day moving window size and 4-day window size for fitting parameters are suitable to interpolate gross primary production （GPP）. For DB method,the 2-day moving window size and 60-day window size for fitting parameters are optimal. Annual GPP and Re from NB method are 13. 8% and 26. 8% greater than those from DB method,respectively. While NEE from NB method is 32. 2% lower than that from DB method. Daytime NEE from NB and DB methods are very similar,but there is great difference in Re between NB and DB methods.[Conclusion]The proportion of missing data has important e