呼伦贝尔草甸草原不同显热通量观测方法比较

显热通量（sensible heat flux,H）是反映地表湍流运动的重要参数,准确获取该参数对于区域内热量交换规律的认识和农业生产及水资源的有效管理具有重要意义。涡动相关仪（eddy covariance system,EC）和大孔径闪烁仪（large aperture scintillometer,LAS）是目前生态系统水热通量的主要测量手段,但两者观测范围的空间尺度存在差异。该研究以呼伦贝尔草甸草原生态系统为对象,通过对比分析两种方法观测的显热通量（H_LAS和H_EC）变化特征,对两者之间的差异（ΔH）及产生原因进行探究,并且定量研究了不同因子对ΔH的影响程度。结果表明,在不同时间尺度内,H_LAS和H_EC的变化趋势基本一致,显热通量主要受到净辐射的驱动作用,同时ΔH与净辐射存在正相关性;对应时刻H_LAS和H_EC之间线性回归方程斜率为1.13,拟合优度R²为0.81,说明大孔径闪烁仪在草甸草原区有着很好的适用性;EC能量平衡闭合程度会影响H_LAS和H_EC之间差异,剔除能量平衡闭合率（energy balance ratio,EBR）小于0.8的数据后,H_LAS和H_EC之间线性回归方程斜率减小至1.05,说明能量平衡闭合程度越高ΔH越小;净辐射（net radiation,R_n）、风速（wind speed,WS）、波文比（Bowen ratio,Bowen）和饱和水汽压差（saturated water vapor pressure difference,VPD）与ΔH之间相关性显著,是ΔH的主要气象环境因子;ΔH单个影响因子的解释能力从高到低依次为净辐射、风速、EC能量平衡闭合率、饱和水汽压差、波文比,任意两个不同影响因子之间均呈现双因子增强作用,解释能力较高的交互影响因子为净辐射/风速和风速/波文比。研究结果有利于准确理解LAS与EC显热通量观测过程中的空间尺度效应,同时可为区域尺度扩展和遥感地面验证过程中通量数据的质量控制提供科学参考依据。

Comparation of observation methods of sensible heat flux in Hulunbuir meadow steppe

Sensible heat flux is one of the most important parameters to represent the surface turbulent motion. Accurate and quantitative observation can greatly contribute to the patterns of water and heat balance within the region. It is also of great significance to climate observation, agricultural production, and water resources management. Eddy covariance (EC) and large aperture scintillometer (LAS) are the primary measurement techniques for the surface water and heat fluxes in the ecosystems at present. However, there are great differences in the spatial scales of the observation between the two techniques. Taking the Hulunbuir meadow steppe ecosystem as the research object, this study aims to clarify the variation characteristics of sensible heat flux observed by LAS and EC techniques. The contributing factors were also identified to determine the difference between sensible heat flux. A systematic analysis was finally made to quantitatively explore the influence of various factors on the difference between the two techniques. The results indicated that there was all the same trend of sensible heat flux observed by LAS and EC, which was predominantly driven by net radiation. There was also a positive correlation between the difference and net radiation at various temporal scales. The slope of 1.13 was found in the linear regression equation between the sensible heat flux observed by LAS and EC, indicating the better correlation (the goodness of fit was 0.81). The root mean square difference (RMSD) was 26.0 W/m², while the mean absolute percentage error (MAPE) was 26.9%. The difference fell within the range of −50 to 50 W/m² in the majority of cases, accounting for 94.2 % of all samples. The results showed that the LAS shared excellent applicability in the meadow steppe region. The energy balance closure of the EC system then posed some influence on the difference between sensible heat flux observed by LAS and EC. The difference between LAS and EC was reduced after the removal of the data with an energy balance ratio (EBR) less than 0.8. Therefore, the difference between LAS and EC tended to be smaller in the higher energy balance closure. The primary meteorological environmental factors were determined as the net radiation, wind speed (WS), Bowen ratio (Bowen), and saturated water vapor pressure difference (VPD), indicating the significant correlations with the difference between LAS and EC. The explanatory power of individual factors was ranked in the descending order of the net radiation, wind speed, EC energy balance closure ratio, saturated water vapor pressure difference, and Bowen ratio. Both net radiation and WS shared the greatest influence on the difference between LAS and EC, with an explanatory power of over 50%. There was a two-factor enhancement between any two distinct influencing factors, particularly with the interactive factors of net radiation/wind speed and wind speed/Bowen ratio, indicating the high explanatory power of over 70%. A more accurate understanding was gained for the observation of sensible heat flux at the spatial scale by LAS and EC. The findings can also provide a strong reference for the quality control of flux data during regional-scale extension and ground validation using remote sensing.