Abstract The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world. In the current operational algorithm of SMAP (level 2), vegetation water content (VWC) is considered as a proxy to compute VOD which is calculated by an empirical conversion function of NDVI. Avoiding the empirical estimation of VOD, the SMOS algorithm is used to retrieve simultaneously SM and VOD from TB observations. The present study attempted to improve SMAP TB simulations and SM retrievals by benefiting from the advantages of the SMOS (L-MEB) algorithm. This was achieved by using a synergy method based on replacing the default value of SMAP VOD with the retrieved value of VOD from the SMOS multi angular and bi-polarization observations of TB. The insitu SM measurements, used as reference SM in this study, were obtained from the International Soil Moisture Network (ISMN) over 180 stations located in arid regions of the world. Furthermore, four stations were randomly selected to analyze the temporal variations in VOD and SM. Results of the synergy method showed that the accuracy of the TB simulations and SM retrievals was respectively improved at 144 and 124 stations (out of a total of 180 stations) in terms of coefficient of determination (R2) and unbiased root mean squared error (UbRMSE). Analyzing the temporal variations in VOD showed that the SMOS VOD, conversely to the SMAP VOD, can better illustrate the presence of herbaceous plants and may be a better indicator of the seasonal changes in the vegetation density and biomass over the year.

中文翻译：

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利用 SMAP 和 SMOS 之间的协同作用改进干旱地区的亮温模拟和土壤水分反演

摘要 本研究的目的是利用基于植被光学深度 (VOD) 的 SMOS 和 SMAP 之间的协同作用，以改善世界干旱地区的亮温 (TB) 模拟和陆表土壤水分 (SM) 反演。在 SMAP（级别 2）的当前操作算法中，植被含水量 (VWC) 被视为计算 VOD 的代理，VOD 由 NDVI 的经验转换函数计算。避免了 VOD 的经验估计，SMOS 算法用于从 TB 观测中同时检索 SM 和 VOD。本研究试图通过受益于 SMOS (L-MEB) 算法的优势来改进 SMAP TB 模拟和 SM 检索。这是通过使用基于从 TB 的 SMOS 多角度和双极化观测中检索到的 VOD 值替换 SMAP VOD 的默认值的协同方法来实现的。在本研究中用作参考 SM 的原位 SM 测量值来自位于世界干旱地区的 180 多个站点的国际土壤水分网络 (ISMN)。此外，随机选择了四个站点来分析 VOD 和 SM 的时间变化。协同方法的结果表明，在确定系数 (R2) 和无偏均方根误差 (UbRMSE) 方面，TB 模拟和 SM 反演的准确性分别在 144 和 124 个站点（总共 180 个站点中）得到提高）。分析 VOD 的时间变化表明，SMOS VOD 与 SMAP VOD 相反，