Impacts of Local Green's Functions on Modeling Atmospheric Loading Effects for GNSS Reference Stations.

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. Plain Language Summary: In any location worldwide, we employ a consistent set of numbers, known as load Green's functions that characterize the elastic properties of the Earth, to model the deformation caused by mass transfer on Earth's surface, which is referred to as surface mass loading effects. Most research and data products adopt same set of global mean Green's functions for any location on Earth, which neglects the differences in elastic properties of various regions of the Earth, leading to modeling errors to some extent. This study aims to optimize the modeling using local load Green's functions, with the objective of obtaining results that are more theoretically valuable. "Local" means that the Green's functions for each site are derived from an Earth model that takes into account the local crustal structure. The modeled atmospheric loading displacements exhibit enhanced alignment with GNSS position time series. This, in turn, further elucidates that deformations can be more attributed to atmospheric loading. Moreover, the model shows improved performance in the horizontal components when compared to the vertical components. Key Points: Local load Green's Functions enable a more precise modeling of loading displacements than global mean Green's FunctionsThe modeled atmospheric loading displacements based on Local Green's Functions can improve scatter reduction of GNSS position time seriesTwo sets of local load Green's Functions, based on CRUST1.0 model and TEA12 model, are compared. We recommend TEA12 for European region [ABSTRACT FROM AUTHOR]