In this paper, a soil moisture (SM) retrieval model from spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) observations that incorporates soil surface temperature (SST) for the first time is evaluated. Here, based on the grid scale, Cyclone GNSS (CYGNSS) reflectivity, SST and vegetation optical depth (VOD) are employed to estimate SM by a trilinear regression, while the other influence factors such as soil roughness and texture are regard as static. The results are compared with globally Soil Moisture Active Passive (SMAP) SM and in-situ measurements from International Soil Moisture Network (ISMN) over the year of 2018 respectively, showing a good consistency (R = 0.929 and RMSE = 0.043 cm³cm⁻³ against SMAP SM; R = 0.927 and RMSE = 0.042 cm³cm⁻³ against in-situ SM). Although the sensitivity of reflectivity to SST is found to be much smaller than that to SM from the simulation, the incorporation of SST is demonstrated to be effective in SM estimation for its coupling relationship with SM. In the comparison with SMAP SM, the improvements of RMSE by incorporating SST are varying degrees globally, and significant in many arid areas with an improvement of over 40%. In the in-situ validation, the overall RMSE decreases from 0.047 to 0.042 cm³cm⁻³ with an improvement of 10.6%. This work demonstrates the necessity and improvement for incorporating SST into SM retrieval for GNSS-R. Moreover, the findings provide a potential method to obtain global SST dataset from CYGNSS observations.

在本文中，评估了首次结合土壤表面温度（SST）的星载全球导航卫星系统反射仪（GNSS-R）观测的土壤水分（SM）反演模型。这里，基于网格尺度，采用旋风GNSS（CYGNSS）反射率、SST和植被光学深度（VOD）通过三线性回归估计SM，而土壤粗糙度和质地等其他影响因素则视为静态的。结果分别与 2018 年全球土壤水分主动被动 (SMAP) SM 和国际土壤水分网络 (ISMN) 的原位测量结果进行了比较，显示出良好的一致性（R = 0.929 和 RMSE = 0.043 cm ³ cm ^{- 3}对 SMAP SM；R = 0.927 和 RMSE = 0.042 cm ³cm ^-3对抗原位 SM）。尽管从模拟中发现反射率对 SST 的敏感性远小于对 SM 的敏感性，但由于其与 SM 的耦合关系，SST 的结合被证明在 SM 估计中是有效的。与 SMAP SM 相比，全球范围内纳入 SST 对 RMSE 的改善程度不同，在许多干旱地区显着改善了 40% 以上。在原位验证中，整体 RMSE 从 0.047 降低到 0.042 cm ³ cm ^-3，提高了 10.6%。这项工作证明了将 SST 纳入 GNSS-R 的 SM 检索的必要性和改进。此外，这些发现提供了一种从 CYGNSS 观测中获取全球 SST 数据集的潜在方法。