Land surface temperature (LST) is an important parameter that critically contributes to Earth’ s climate. Thermal anisotropy is a major challenge that must be addressed while generating long-term LST products from satellites. For instance, the differences between GOES-16 and GOES-17 LST products caused by thermal anisotropy have not yet been resolved, which impacts the high-frequency monitoring of the land surface. The coupled contributions of the gap fraction and hotspot effects in the thermal infrared domain result in the existence of thermal anisotropy effect. The time-evolving kernel-driven model (TEKDM) is a recently proposed practical tool for conducting LST angular normalization for geostationary satellites. However, the existing six-parameter TEKDM considers only the hotspot effect and ignores the gap fraction effect, which may limit the TEKDM-based angular normalization method. In this study, we proposed an extended seven-parameter TEKDM considering both the gap fraction and hotspot effects and normalized the angular effect of GOES-16 and GOES-17 LST products over the overlapping region using this model. The accuracy of this seven-parameter TEKDM was evaluated using a physically based discrete anisotropic radiative transfer (DART) simulation dataset. Subsequently, the seven-parameter TEKDM-based angular normalization method was evaluated using the GOES-16 and GOES-17 LST products of the overlapping region for one year against ten AmeriFlux sites. The results showed that the seven-parameter TEKDM had a RMSE (MBE) of 0.36 K (0.0019 K). Compared with the RMSE of the NOAA-released GOES LST products, the seven-parameter TEKDM-based normalization method could reduce the RMSE of GOES-16 and GOES-17 LST products from 2.2 K and 2.6 K to 1.7 K, respectively, with a reduction of 0.5 K (22.7 %) and 0.9 K (34.6 %), respectively. Furthermore, the RMSE/MBE of GOES-17 LST exhibited a different diurnal variation pattern than that of GOES-16 LST, which could be explained by the different illumination-viewing geometries of the two satellites. This emphasizes the necessity of conducting angular normalization of current geostationary satellite LST products. The seven-parameter TEKDM provides a feasible method for generating long-term high-quality LST datasets for remote sensing communities.

中文翻译：

---

使用扩展时间演化核驱动模型对 GOES-16 和 GOES-17 地表温度在重叠区域进行角度归一化


地表温度 （LST） 是影响地球气候的重要参数。热各向异性是从卫星生成长期 LST 产品时必须解决的一个主要挑战。例如，热各向异性引起的 GOES-16 和 GOES-17 LST 产品之间的差异尚未解决，这影响了地表的高频监测。热红外域中间隙分数和热点效应的耦合贡献导致了热各向异性效应的存在。时间演化核驱动模型 （TEKDM） 是最近提出的一种实用工具，用于对地球静止卫星进行 LST 角度归一化。然而，现有的六参数 TEKDM 只考虑了热点效应，忽略了间隙分数效应，这可能会限制基于 TEKDM 的角度归一化方法。在这项研究中，我们提出了一个同时考虑间隙分数和热点效应的扩展七参数 TEKDM，并使用该模型对 GOES-16 和 GOES-17 LST 产物在重叠区域上的角度效应进行了归一化。使用基于物理的离散各向异性辐射传输 （DART） 仿真数据集评估了该七参数 TEKDM 的精度。随后，使用重叠区域的 GOES-16 和 GOES-17 LST 产品对 10 个 AmeriFlux 位点进行了为期一年的基于 TEKDM 的七参数角度归一化方法。结果表明，七参数 TEKDM 的 RMSE （MBE） 为 0.36 K （0.0019 K）。与 NOAA 发布的 GOES LST 产品的 RMSE 相比，基于 TEKDM 的七参数归一化方法可以将 GOES-16 和 GOES-17 LST 产品的 RMSE 从 2.2 K 和 2.6 K 降低到 1。7 K，分别减少了 0.5 K （22.7%） 和 0.9 K （34.6%）。此外，GOES-17 LST 的 RMSE/MBE 表现出与 GOES-16 LST 不同的日变化模式，这可以通过两颗卫星不同的照明观察几何形状来解释。这强调了对当前对地静止卫星 LST 产品进行角度归一化的必要性。七参数 TEKDM 为遥感社区生成长期高质量 LST 数据集提供了一种可行的方法。