Heat flux data collected from the Baiyangdian Heterogeneous Field Experiment were analyzed using the footprint method. High resolution （25 m） Landsat-5 satellite imaging was used to determine the land cover as one o...Heat flux data collected from the Baiyangdian Heterogeneous Field Experiment were analyzed using the footprint method. High resolution （25 m） Landsat-5 satellite imaging was used to determine the land cover as one of four surface types： farmland, lake, wetland, or village. Data from two observation sites in September 2005 were used. One site （Wangjiazhai） was characterized by highly heterogeneous surfaces in the central area of the Baiyangdian： lake/wetland. The other site （Xiongxian） was on land with more uniform surface cover. An improved Eulerian analytical flux footprint model was used to determine “source areas” of the heat fluxes measured at towers located at each site from surrounding landscapes of mixed surface types. In relative terms results show that wetland and lake areas generally contributed most to the observed heat flux at Wangjiazhai, while farmland contributed most at Xiongxian. Given the areal distribution of surface type contributions, calculations were made to obtain the magnitudes of the heat flux from lake, wetland and farmland to the total observed flux and apportioned contributions of each surface type to the sensible and latent heat fluxes. Results show that on average the sensible heat flux from wetland and farmland were comparable over the diurnal cycle, while the latent heat flux from farmland was somewhat larger by about 30-50 W m-2 during daytime. The latent and sensible fluxes from the lake source in daytime were about 50 W m-2 and 100 W m-2 less, respectively, than from wetland and farmland. The results are judged reasonable and serve to demonstrate the potential for flux apportionment over heterogeneous surfaces.展开更多
Spatial heterogeneity poses a major challenge for the appropriate interpretation of eddy covariance data. The quantification of footprint climatology is fundamental to improving our understanding of carbon budgets, as...Spatial heterogeneity poses a major challenge for the appropriate interpretation of eddy covariance data. The quantification of footprint climatology is fundamental to improving our understanding of carbon budgets, assessing the quality of eddy covariance data, and upscaling the representativeness of a tower flux to regional or global scales. In this study, we elucidated the seasonal variation of flux footprint climatologies and the major factors that influence them using the analytical FSAM （Flux Source Area Model）, KM （Kormann and Meixner, 2001）, and H （Hsieh et al., 2000） models based on eddy covariance measurements at two and three times the canopy height at the Qianyanzhou site of ChinaFLUX in 2003. The differences in footprints among the three models resulted from different underlying theories used to construct the models. A comparison demonstrated that atmospheric stability was the main factor leading to differences among the three models. In neutral and stable conditions,the KM and FSAM values agreed with each other, but they were both lower than the H values. In unstable conditions, the agreement among the three models for rough surfaces was better than that for smooth surfaces, and the models showed greater agreement for a low measurement height than for a high measurement height. The seasonal flux footprint climatologies were asymmetrically distributed around the tower and corresponded well to the prevailing wind direction, which was north-northwest in winter and south-southeast in summer. The average sizes of the 90% flux footprint climatologies were 0.36 0.74 and 1.5-3.2 kin2 at altitudes of two and three times the canopy height, respectively. The average sizes were ranked by season as follows： spring 〉 summer 〉 winter 〉 autumn. The footprint climatology depended more on atmospheric stability on daily scale than on seasonal scale, and it increased with the increasing standard deviation of the lateral wind fluctuations.展开更多
选取2005年5月24日-6月18日在金塔开展的“绿洲系统能量与水分循环过程的观测实验”中的3层CSAT3的实验数据，应用Schmid的FSAM（The Flux-Source Area Model）模型，分析了不同观测高度的通量贡献源区分布以及观测高度对通量贡献源区...选取2005年5月24日-6月18日在金塔开展的“绿洲系统能量与水分循环过程的观测实验”中的3层CSAT3的实验数据，应用Schmid的FSAM（The Flux-Source Area Model）模型，分析了不同观测高度的通量贡献源区分布以及观测高度对通量贡献源区分布的影响，同时分析了不同大气层结条件下源区的分布以及稳定度对通量贡献源区分布的影响。结果表明,稳定条件下的通量贡献源区大于不稳定条件下的通量贡献源区，并且随着观测高度的增加通量贡献源区会显著增大。展开更多
文摘Heat flux data collected from the Baiyangdian Heterogeneous Field Experiment were analyzed using the footprint method. High resolution （25 m） Landsat-5 satellite imaging was used to determine the land cover as one of four surface types： farmland, lake, wetland, or village. Data from two observation sites in September 2005 were used. One site （Wangjiazhai） was characterized by highly heterogeneous surfaces in the central area of the Baiyangdian： lake/wetland. The other site （Xiongxian） was on land with more uniform surface cover. An improved Eulerian analytical flux footprint model was used to determine “source areas” of the heat fluxes measured at towers located at each site from surrounding landscapes of mixed surface types. In relative terms results show that wetland and lake areas generally contributed most to the observed heat flux at Wangjiazhai, while farmland contributed most at Xiongxian. Given the areal distribution of surface type contributions, calculations were made to obtain the magnitudes of the heat flux from lake, wetland and farmland to the total observed flux and apportioned contributions of each surface type to the sensible and latent heat fluxes. Results show that on average the sensible heat flux from wetland and farmland were comparable over the diurnal cycle, while the latent heat flux from farmland was somewhat larger by about 30-50 W m-2 during daytime. The latent and sensible fluxes from the lake source in daytime were about 50 W m-2 and 100 W m-2 less, respectively, than from wetland and farmland. The results are judged reasonable and serve to demonstrate the potential for flux apportionment over heterogeneous surfaces.
基金Supported by the National Basic Research and Development(973)Program of China(2012CB416903)National Natural Science Foundation of China(31470500 and 31290221)Knowledge Innovation Project of the Chinese Academy of Sciences(KZCX2-EW-QN305)
文摘Spatial heterogeneity poses a major challenge for the appropriate interpretation of eddy covariance data. The quantification of footprint climatology is fundamental to improving our understanding of carbon budgets, assessing the quality of eddy covariance data, and upscaling the representativeness of a tower flux to regional or global scales. In this study, we elucidated the seasonal variation of flux footprint climatologies and the major factors that influence them using the analytical FSAM （Flux Source Area Model）, KM （Kormann and Meixner, 2001）, and H （Hsieh et al., 2000） models based on eddy covariance measurements at two and three times the canopy height at the Qianyanzhou site of ChinaFLUX in 2003. The differences in footprints among the three models resulted from different underlying theories used to construct the models. A comparison demonstrated that atmospheric stability was the main factor leading to differences among the three models. In neutral and stable conditions,the KM and FSAM values agreed with each other, but they were both lower than the H values. In unstable conditions, the agreement among the three models for rough surfaces was better than that for smooth surfaces, and the models showed greater agreement for a low measurement height than for a high measurement height. The seasonal flux footprint climatologies were asymmetrically distributed around the tower and corresponded well to the prevailing wind direction, which was north-northwest in winter and south-southeast in summer. The average sizes of the 90% flux footprint climatologies were 0.36 0.74 and 1.5-3.2 kin2 at altitudes of two and three times the canopy height, respectively. The average sizes were ranked by season as follows： spring 〉 summer 〉 winter 〉 autumn. The footprint climatology depended more on atmospheric stability on daily scale than on seasonal scale, and it increased with the increasing standard deviation of the lateral wind fluctuations.
文摘选取2005年5月24日-6月18日在金塔开展的“绿洲系统能量与水分循环过程的观测实验”中的3层CSAT3的实验数据，应用Schmid的FSAM（The Flux-Source Area Model）模型，分析了不同观测高度的通量贡献源区分布以及观测高度对通量贡献源区分布的影响，同时分析了不同大气层结条件下源区的分布以及稳定度对通量贡献源区分布的影响。结果表明,稳定条件下的通量贡献源区大于不稳定条件下的通量贡献源区，并且随着观测高度的增加通量贡献源区会显著增大。
