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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >An Observing System Simulation Experiment for the Aquarius/SAC-D Soil Moisture Product
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An Observing System Simulation Experiment for the Aquarius/SAC-D Soil Moisture Product

机译:Aquarius / SAC-D土壤水分产品的观测系统模拟实验

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摘要

An Observing System Simulation Experiment (OSSE) for the Aquarius/SAC-D mission has been developed for assessing the accuracy of soil moisture retrievals from passive L-band remote sensing. The implementation of the OSSE is based on the following: a 1-km land surface model over the Red-Arkansas River Basin, a forward microwave emission model to simulate the radiometer observations, a realistic orbital and sensor model to resample the measurements mimicking Aquarius operation, and an inverse soil moisture retrieval model. The simulation implements a zero-order radiative transfer model. Retrieval is performed by direct inversion of the forward model. The Aquarius OSSE attempts to capture the influence of various error sources, such as land surface heterogeneity, instrument noise, and retrieval ancillary parameter uncertainty, all on the accuracy of Aquarius surface soil moisture retrievals. In order to assess the impact of these error sources on the estimated volumetric soil moisture, a quantitative error analysis is performed by comparison of footprint-scale synthetic soil moisture with “true” soil moisture fields obtained from the direct aggregation of the original 1-km soil moisture field input to the forward model. Results show that, in heavily vegetated areas, soil moisture retrievals have a positive bias that can be suppressed with an alternative aggregation strategy for ancillary parameter vegetation water content (VWC). Retrieval accuracy was also evaluated when adding errors to 1-km VWC (which are intended to account for errors in VWC derived from remote sensing data). For soil moisture retrieval root-mean-square error on the order of 0.05 $hbox{m}^{3}/hbox{m}^{3}$, the error in VWC should be less than 12%.
机译:已经开发了用于水瓶座/ SAC-D任务的观测系统模拟实验(OSSE),用于评估从无源L波段遥感获取的土壤水分的准确性。 OSSE的实施基于以下内容:Red-Arkansas流域上的1 km地表模型,模拟辐射计观测的正向微波发射模型,模拟水瓶座运行的测量值的真实采样的真实轨道和传感器模型,以及土壤水分反演模型。该仿真实现了零级辐射传递模型。通过正向模型的直接反演进行检索。水瓶座OSSE试图捕获各种误差源的影响,例如陆地表面非均质性,仪器噪声和恢复辅助参数的不确定性,所有这些都对水瓶座表层土壤水分恢复的准确性产生影响。为了评估这些误差源对估计土壤含水量的影响,通过将足迹规模的合成土壤含水量与从原始1-km的直接聚集获得的“真实”土壤含水量进行比较,进行了定量误差分析。土壤水分场输入到正演模型。结果表明,在植被茂密的地区,土壤水分取回具有正偏见,可以通过使用辅助参数植被水分含量(VWC)的替代聚集策略来抑制。当将误差添加到1公里的VWC中时,还评估了检索准确性(其目的是考虑到从遥感数据得出的VWC中的误差)。对于土壤水分的均方根误差约为0.05 $ hbox {m} ^ {3} / hbox {m} ^ {3} $,VWC的误差应小于12%。

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