- Institute of Geophysics of the Czech Academy of Sciences, Prague 4, Czechia (j.kvapil@ig.cas.cz)
We assembled a large dataset of seismic waveforms with a non-uniform geographical distribution of permanent and temporary stations from regional-scale passive seismic experiments in central Europe, including the recent large-scale pan-European experiments AlpArray, PACASE and AdriaArray. This integrated dataset provides a viable source of observables for high-resolution travel-time surface wave tomography. However, the resolution and clarity of images resulting from various tomographic methods using different seismic waves are often compromised by the need of regularisation (i.e., damping and smoothing) to balance images from irregular input data distribution.
In this study, we developed a weighted regularisation scheme (WRS) for surface-wave travel-time tomography to reduce the bias caused by non-uniformly distributed data. The WRS is based on the implementation of ray-path coverage weights in localised azimuth-distance geographical segments in the inversion.
We present calibration of spatial weighting function on synthetic inter-station travel-times with regular ray-path distribution. On the integrated dataset with real ray-path distribution, we compare results of surface-wave travel-time tomography of synthetic travel times (calculated over the “spike” and “checkerboard” velocity fields) and observed travel times (derived from the cross-correlation delay times of the ambient noise) by applying:
- conventional regularisation approach (i.e., smoothing and damping)
- station de-selection to regular geographical grid, followed by conventional approach
- weighted regularisation scheme(WRS)
We show that the conventional surface-wave travel-time inversion is biased in favour of solutions in areas with the dense ray-path coverage and has poor resolution and reliability in areas with sparse ray-path coverage. The proposed WRS balances the inversion bias from the non-uniform distribution of travel-time measurements, allows the use of milder regularisation parameters (i.e., lower smoothing and damping), and resolves better broader areas with higher reliability.
How to cite: Kvapil, J. and Plomerová, J.: Weighted regularisation scheme for surface-wave tomography to mitigate bias caused by non-uniformly distributed ray-path coverage., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16815, https://doi.org/10.5194/egusphere-egu25-16815, 2025.