The Green's function approach is well-established and widely used for modeling the surface mass loading displacements. Global mean Green's functions (MGFs) are commonly applied without considering local variations of the crustal structure. Derived from the modified layered Earth structure, the local Green's functions (LGFs) are theoretically beneficial to generate more accurate deformation, since they consider interior information of the local crust. This paper analyzed the differences among MGFs from Gutenberg–Bullen A model and two sets of LGFs derived from modified PREM Earth models consolidating with two crust models TEA12 and CRUST1.0, hereafter called PREMTEA and PREMCRU, respectively. Utilizing MGFs and two sets of LGFs, we modeled the corresponding 3D atmospheric loading displacements for 984 ITRF2014 stations and compared them with the ITRF2014 residuals. The results show that LGFs from PREMTEA and PREMCRU perform well in further promoting scatter reduction for ∼72%, ∼56%, and ∼85% of stations for the Up, East and North components, respectively. The improvements for the North components are significant (up to 3.6%). In particular, stations in the east coastal areas of North America and the west edge of Greenland exhibit further promoting scatter reduction for the East components (up to ∼2.5%), while those located in west coastline of North America show better performance for the North components. Nevertheless, there are significant anomalies in northern Europe for PREMCRU, the mutation margin of which should be carefully considered when using a resolution higher than 1°. In the area around station MORP (358.31°W, 55.21°N, sited at coastline of Britain), we suggest using PREMTEA model.

中文翻译：

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局部格林函数对 GNSS 参考站大气负荷效应建模的影响

格林函数方法已得到广泛应用，并广泛用于表面质量载荷位移建模。应用全球平均格林函数 (MGF) 时通常不考虑地壳结构的局部变化。源自修改后的层状地球结构，局部格林函数（LGF）理论上有利于产生更准确的变形，因为它们考虑了局部地壳的内部信息。本文分析了 Gutenberg-Bullen A 模型中的 MGF 和源自修正 PREM 地球模型并合并两个地壳模型 TEA12 和 CRUST1.0（以下分别称为 PREMTEA 和 PREMCRU）的两组 LGF 之间的差异。利用 MGF 和两组 LGF，我们对 984 个 ITRF2014 站的相应 3D 大气载荷位移进行了建模，并将其与 ITRF2014 残差进行了比较。结果表明，PREMTEA 和 PREMCRU 的 LGF 在进一步促进上行、东行和北行部分约 72%、约 56% 和约 85% 站点的散射减少方面表现良好。北方组件的改进非常显着（高达 3.6%）。特别是，位于北美东海岸地区和格陵兰岛西边缘的站点进一步促进了东部成分的散射减少（高达~2.5％），而位于北美西海岸线的站点则对北部成分表现出更好的表现成分。然而，北欧的 PREMCRU 存在明显的异常，在使用高于 1° 的分辨率时应仔细考虑其突变裕度。在MORP站（358.31°W，55.21°N，位于英国海岸线）周围区域，我们建议使用PREMTEA模型。