EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Predicting elastic deformations of the crust induced by environmental loading on time-scales from days to decades

Robert Dill1, Henryk Dobslaw1, and Anna Klos2
Robert Dill et al.
  • 1GFZ, Helmholtz Centre Potsdam, 1.3 Earth System Modelling, Potsdam, Germany (
  • 2Military University of Technology Warsaw, Poland

Earth’s surface is elastically deformed by time-variable surface mass loads such as variations in atmospheric surface pressure, ocean bottom pressure, and terrestrial water storage. We look at the individual environmental loading contributions from the three different subsystems (atmosphere, terrestrial water storage, ocean) as well as from sea-level variations induced by the global water mass balance between land and ocean. Dividing the contributions into a set of period bands by means of a Wavelet decomposition, we show that non-tidal atmospheric surface loading (NTAL) by far dominates non-tidal ocean (NTOL) and hydrospheric loading (HYDL) for periods as long as a few months. The contribution of terrestrial water storage is continuously growing for increasingly longer periods and dominates atmospheric pressure at periods of 300 days and above. Ocean dynamics including sea-level variations due to the seasonal global mass balance are only important in the immediate vicinity of the coast.

In representative regions, we compare different environmental loading estimates, e.g. ESMGFZ based on ECMWF operational atmospheric data, NTAL and NTOL based on ECMWF ERA5, HYDL based on GRACE/GRACE-FO. Depending on the geographical location and considered frequency range, different estimates for NTOL and HYDL can exhibit large differences. In contrast, all latest loading models show a very consistent picture of atmospheric surface pressure loading deformations.  To evaluate the ability of different GNSS solutions to confirm the vertical deformations predicted by the geophysical fluid models, we compared at selected sites vertical station coordinates from six GNSS solutions with loading model predictions. In many cases, GNSS-derived variations heavily dependent on subjective choices within the GNSS data processing.

How to cite: Dill, R., Dobslaw, H., and Klos, A.: Predicting elastic deformations of the crust induced by environmental loading on time-scales from days to decades, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2197,, 2021.

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