Finite element modelling of atmosphere loading effects on strain, tilt and displacement at multi-sensor stations

Abstract

SUMMARY Strain- and tiltmeter observations are composed of signals of different origin. Tides are a wellknown phenomenon that can be extracted from the time series by tidal analysis. Depending on the location of the station, residuals, however, contain contributions of different magnitudes from ocean loading, changes in atmospheric or hydrological loading, anthropogenic induced signals and tectonics. Reductions of the residual variations are indispensable for extraction of, for example the pure tectonical signal. One of the challenges in view of the reductions is to understand transfer mechanisms between loading and local conditions, such as topography, cavity and geological features, which lead to additional or modified deformations. In this study, systematic numerical modelling using the Finite Element method with elastic rheology is carried out to estimate these effects. Barometric pressure changes are used as example for the load to determine the additional deformations. Strain- and tiltmeters are considered as instrumentation, having nominal resolutions of 0.2 nstrain and 1 nrad, respectively. The cavity and the topographic effect are systematically investigated with sophisticated models incorporating typical topographic features, such as a plain, a hill flank and a valley. Representative for stations worldwide, four observatories in Central Europe are modelled: the Geodetic Observatory Wettzell (Germany), the Sopron Observatory (Hungary), the Geodynamic Observatory Moxa and the Black Forest Observatory (BFO) (both Germany). The modelling shows that cavity and topographic effects occur in the same order of magnitude and that both effects interact leading to deformations partly intertwined in a complex way. This notwithstanding, the results explain observed deformation signals at the observatories. The systematic modelling helps to better understand the basic processes, from which criteria for the selection of future observation sites are inferred.