Turbulence data(2008–2012) from a 325 m meteorological tower in Beijing, which consisted of three layers(47,140, and 280 m), was used to analyze the vertical distribution characteristics of turbulent transfer over Beijing city according to similarity theory. The conclusions were as follows.(1) Normalized standard deviations of wind speeds/ui * were plotted as a function only of a local stability parameter. The values under near-neutral conditions were 2.15, 1.61, and 1.19 at 47 m, 2.39, 1.75,and 1.21 at 140 m, and 2.51, 1.77, and 1.30 at 280 m, showing a clear increase with height. The normalized standard deviation of wind components fitted the 1/3 law under unstable stratification conditions and decreased with height under both stable and unstable conditions.(2) The normalized standard deviation of temperature fitted the.1/3 law in the free convection limit, but was quite scattered with different characteristics under near-neutral conditions. The normalized standard deviations of humidity and the CO2 concentration fitted the.1/3 law under unstable conditions, and remained constant under near-neutral and stable stratification. The normalized standard deviation of scalars, i.e., temperature, humidity, and CO2 concentration, all increased with height.(3) Compared with momentum, and the water vapor and CO2 concentrations, the turbulence correlation coefficient for heat was smaller under near-neutral conditions, but larger under both stable and unstable conditions. A dissimilarity between heat, and the water vapor and CO2 concentrations was observed in urban areas. The relative correlation coefficients between heat and each of momentum, humidity, and CO2 concentration(|rwT/ruw|, |rwT/rwc| and |rwT/ruq|) in the lower layers were always larger than in higher layers, except for the relative correlation coefficient between heat and humidity in an unstable stratification. Therefore, the ratio between heat and each of momentum, humidity, and CO2 concentration decreased with height.
基于半干旱区2种不同下垫面(草地和旱作农田)2005和2008年涡动相关法取得的通量资料,分析了数据填补、能量收支闭合率以及摩擦风速(u*)阈值等对生态系统年净碳交换的影响.通过加入4种不同长度的人工空缺(空缺长度从0.5 h^12 d),比较了平均日变化法(MDV)、边缘分布抽样法(MDS)和非线性回归法等6种填补方法的填补效果.结果表明,MDS的整体表现最好,特别是对长空缺的填补效果优于其他方法,估算的年NEE偏差在5 g C m-2 a-1以内.非线性回归法估算的夜间NEE具有较大的正偏差,表明非线性回归法估算的夜间生态系统呼吸偏高.4种非线性回归法估算的年NEE偏差在8.0~30.8g C m-2 a-1.由于在半干旱区土壤含水量是生态系统碳交换的重要限制因子,非线性回归法中综合考虑土壤温度和土壤含水量影响的Non_linear3和Non_linear4表现较好.MDV对白天NEE空缺的填补优于夜间,估算的年NEE偏差在-2.6^-13.4 g C m-2 a-1.总体上,数据填补的精确度受下垫面类型、空缺长度以及空缺出现时间(白天、晚上)影响.2个观测站点的能量收支闭合率在80%左右.能量收支闭合率受湍流强度影响显著;当夜间摩擦风速较低时,湍流混合不充分,能量收支闭合率也较低.生态系统在某个风向的累积通量印痕较大时,有效能量和湍流通量源区的不匹配造成这一风向上的能量收支闭合率也较低.通过假设能量收支不闭合全部由感热通量和潜热通量的低估引起,评估了能量闭合订正对生态系统CO2通量的影响.结果表明经过订正后的草地、农田的年净碳交换量平均增加近10 g C m-2 a-1.此外当u*阈值从0.1增加到0.2 m s-1,年净碳交换平均增加37.5 g C m-2 a-1,这表明u*阈值的设定对生态系统的年净碳交换影响较大.
