Spatial representativeness and the location bias of flux footprints over inhomogeneous areas
Spatial representativeness and the location bias of flux footprints over inhomogeneous areas
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DOI：
10.1016/s0168-1923(98)00119-1
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发表时间：
1999-03
影响因子：
6.2
通讯作者：
H. Schmid;C. Lloyd
中科院分区：
文献类型：
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作者：
H. Schmid;C. Lloyd
自然植被上的湍流通量在空间上是不均匀的，直到称为物理混合高度的水平。低于这个混合高度的测量受到位置偏差的影响，该偏差随传感器高度、风向和稳定性而变化。位置偏差是在给定位置测量的通量与聚集的生态系统尺度通量的差异程度。使用源区/足迹方法分析这种位置偏差，其中足迹中包含的汇总表面条件与生态系统中的平均表面条件进行比较。当考虑在给定位置的单个观测事件时，该方法导致传感器位置偏差的定量测量。它提供了一个客观的估计，如何一个给定的通量观测相比，生态系统规模的通量。预期的传感器位置偏差表示为在给定的传感器高度的测量值不占表面变化的分数，独立于其在生态系统中的位置。它是足迹过滤函数与详细的表面状况数据库的卷积的结果。这些用于检查通量测量的空间代表性的工具被应用于尼日尔萨赫勒地区的不均匀萨凡纳表面（虎灌丛），以及HAPEX-萨赫勒实地活动期间收集的蒸发测量。
Turbulent fluxes over natural vegetation are spatially inhomogeneous up to a level called the physical blending height. Measurements below this blending height suffer from a location bias that varies with sensor height, wind direction and stability. The location bias is the degree, to which a flux measured at a given location differs from the aggregated ecosystem-scale flux. This location bias is analyzed using the source area/footprint approach, where the aggregated surface conditions contained in the footprint are compared to average surface conditions in the ecosystem. When a single observation event at a given location is considered, this method leads to a quantitative measure of the sensor location bias. It provides an objective estimate of how a given flux observation compares to the ecosystem scale flux. The expected sensor location bias is expressed as the fraction of surface variability not accounted for by measurements at a given sensor height, independent of its location within the ecosystem. It results from a convolution of the footprint filter function with a detailed surface condition database. These tools to examine the spatial representativeness of flux measurements are applied to an inhomogeneous savannah surface (Tiger bush) in the Sahel region of Niger, and to measurements of evaporation collected during the HAPEX-Sahel field campaign.