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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Toward an Optimal SMOS Ocean Salinity Inversion Algorithm
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Toward an Optimal SMOS Ocean Salinity Inversion Algorithm

机译：最优SMOS海洋盐度反演算法

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摘要

As part of the preparation for the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission, empirical sea-surface emissivity (forward) models have been used to retrieve sea-surface salinity from L-band brightness-temperature $(T_{B})$ measurements. However, the salinity inversion is not straightforward, and substantial effort is required to define the most appropriate cost function. Various Bayesian-based configurations of the cost function are examined, depending on whether a priori information is used in the inversion. A sensitivity analysis of $T_{B}$ to several geophysical parameters has been performed and has shown that the instrument has low sensitivity to the parameters that modulate the $T_{B}$ (including salinity). The SMOS end-to-end simulator is used to test the accuracy of different cost-function configurations. Currently, the general opinion in the SMOS community is that a partially constrained cost function, in which the salinity constraint is effectively removed, is the most appropriate for salinity retrieval. The purpose of this letter is to show that we found no evidence that such a configuration performs better than a fully constrained or a nonconstrained one. Moreover, in contrast to previous results, we found that the fully constrained inversion does not converge to the reference or auxiliary salinity value and produces the most accurate salinity retrievals of the tested configurations. Therefore, such a configuration should not be disregarded for future tests.
机译：作为欧洲航天局土壤水分和海洋盐度（SMOS）卫星任务的准备工作的一部分，经验海面发射率（正向）模型已用于从L波段亮度-温度$（T_ { B}）$测量值。但是，盐度反演不是直接的，需要花费大量精力来定义最合适的成本函数。根据是否在反演中使用先验信息，对成本函数的各种基于贝叶斯的配置进行了检查。已对$ T_ {B} $对几个地球物理参数进行了敏感性分析，结果表明该仪器对调制$ T_ {B} $的参数（包括盐度）具有较低的敏感性。 SMOS端到端模拟器用于测试不同成本函数配置的准确性。当前，SMOS社区中的普遍观点是，部分地受约束的成本函数（其中有效地去除了盐度约束）最适合盐度检索。这封信的目的是表明我们发现没有证据表明这种配置比完全约束或非约束的性能更好。此外，与先前的结果相反，我们发现完全受约束的反演不会收敛到参考盐度或辅助盐度值，并且会生成测试配置的最准确的盐度值。因此，在以后的测试中不应忽略这种配置。

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