An accurate temporal and spatial characterization of errors is required for the efficient processing, evaluation, and assimilation of remotely-sensed surface soil moisture retrievals. However, empirical evidence exists that passive microwave soil moisture retrievals are prone to periodic artifacts which may complicate their application in data assimilation systems (which commonly treat observational errors as being temporally white). In this paper, the link between such temporally-periodic errors and spatial land surface heterogeneity is examined. Both the synthetic experiment and site-specified cases reveal that, when combined with strong spatial heterogeneity, temporal periodicity in satellite sampling patterns (associated with exact repeat intervals of the polar-orbiting satellites) can lead to spurious high frequency spectral peaks in soil moisture retrievals. In addition, the global distribution of the most prominent and consistent 8-day spectral peak in the Advanced Microwave Scanning Radiometer - Earth Observing System soil moisture retrievals is revealed via a peak detection method. Three spatial heterogeneity indicators - based on microwave brightness temperature, land cover types, and long-term averaged vegetation index - are proposed to characterize the degree to which the variability of land surface is capable of inducing periodic error into satellite-based soil moisture retrievals. Regions demonstrating 8-day periodic errors are generally consistent with those exhibiting relatively higher heterogeneity indicators. This implies a causal relationship between spatial land surface heterogeneity and temporal periodic error in remotely-sensed surface soil moisture retrievals.

中文翻译：

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空间异质性对微波卫星土壤水分周期误差影响的评估

对遥感表层土壤水分反演的有效处理、评估和同化需要对误差进行准确的时间和空间表征。然而，经验证据表明，被动微波土壤水分反演容易产生周期性伪影，这可能会使它们在数据同化系统中的应用复杂化（通常将观测误差视为时间上的白色）。在本文中，研究了这种时间周期误差与空间地表异质性之间的联系。综合实验和特定地点的案例都表明，当结合强烈的空间异质性时，卫星采样模式的时间周期性（与极轨卫星的精确重复间隔相关）可能导致土壤水分反演中的虚假高频频谱峰值。此外，通过峰值检测方法揭示了高级微波扫描辐射计 - 地球观测系统土壤水分反演中最突出和一致的 8 天光谱峰值的全球分布。提出了三个空间异质性指标——基于微波亮温、土地覆盖类型和长期平均植被指数——来表征地表变化能够在基于卫星的土壤水分反演中引入周期性误差的程度。表现出 8 天周期误差的区域通常与表现出相对较高异质性指标的区域一致。这意味着空间地表异质性与遥感表层土壤水分反演中的时间周期误差之间存在因果关系。