Error Characterization of Soil Moisture Satellite Products: Retrieving Error Cross-Correlation Through Extended Quadruple Collocation
Error Characterization of Soil Moisture Satellite Products: Retrieving Error Cross-Correlation Through Extended Quadruple Collocation
复制标题
土壤湿度卫星产品的误差表征：通过扩展四元组搭配检索误差互相关
DOI：
--
复制
发表时间：
2017
影响因子：
5.5
通讯作者：
R. Crapolicchio
中科院分区：
文献类型：
--
作者：
N. Pierdicca;F. Fascetti;L. Pulvirenti;R. Crapolicchio
三重配置（TC）技术正越来越多地用于验证来自不同系统的土壤水分检索，如卫星、水文模型或原位探针。近年来，为了评估三个以上系统的误差标准偏差和软化TC假设，提出了该方法的几种扩展。为了考虑产品误差之间相互关联的可能性，提出了一种新的扩展四重配置（E-QC）方法，自动识别误差相互关联系统的耦合。该方法甚至适用于大量的并置数据集，尽管在实践中可能无法收集它们。一个综合实验显示了有希望的结果，结论是E-QC能够个性化（如果有的话）具有交叉相关误差的系统对。它正确地补偿了后一种贡献，并准确地检索每个系统的误差标准偏差，否则如果不考虑相互关系就会产生偏差。E-QC应用于卫星（SMOS、ASCAT和SMAP）、模型（ERA Interim）和原位探针（ISMN）提供的土壤水分反演。E-QC方法识别了卫星产品之间存在的误差互相关。这也通过分析五个数据集得到了证实。E-QC显示，卫星产品，特别是SMAP的性能尚可，但不如没有正确考虑误差相关的情况好。
The triple collocation (TC) technique is being increasingly used to validate soil moisture retrievals derived from different systems, like satellites, hydrological models, or in situ probes. In recent years, several extensions of this method were proposed in order to evaluate the error standard deviations of more than three systems and to soften the TC hypothesis. In this paper, a novel extended quadruple collocation (E-QC) method is proposed, in order to consider the possibility of a cross correlation between product errors, identifying automatically the couple of error cross-correlated systems. The method is applicable even to a larger number of collocated datasets, although it may be unfeasible to collect them in practice. A synthetic experiment showed promising results, concluding that the E-QC is able to individuate (if any) the pair of systems with cross-correlated errors. It correctly compensates for the latter contribution and accurately retrieves error standard deviations of each system, otherwise biased if cross correlation is not taken into account. The E-QC was applied to soil moisture retrievals provided by satellite (SMOS, ASCAT, and SMAP), model (ERA Interim), and in situ probes (ISMN). The E-QC method identified the presence of error cross-correlation between the satellite products. This was also confirmed by analyzing the five datasets all together. E-QC showed fair performances of satellite products, especially of SMAP, although not as good as in case the presence of error correlation is not correctly taken into account.