[SSS14-P05] Inversion analyses of long-term slow slip events using GNSS and strain data
Keywords:Strain observation, GNSS, Long-term SSE, Inversion
In this study, we tried to estimate slip distribution of long-term SSE by joint inversion of GNSS and strain data using ABIC and compare the result with the analyses using GNSS data. Also, we evaluate the error of observed strain change and verify the possibility that strain data change may be due to long-term SSE. If long-term SSE could be detected by strain observation other than GNSS observation, it can support GNSS analysis and prove the certainty of long-term SSE analysis using strain stacking data. We apply a joint inversion method [Garth et al., 2014] to the inversion analyses using strain and GNSS data. Figure shows an example of inversion analysis of long-term SSE at Bungo Channel. This shows consistency with the result from spatio-temporal inversion using GNSS data [GSI, 2018-2020]. Error of strain observation data is estimated about 10-11 strain and we have confirmed that the changes of strain observation data are caused by long-term SSE.