G018-08
Delineating the phases of the crustal deformation cycle for the Western U.S. from geodetic data, 1995-2020
Delineating the phases of the crustal deformation cycle for the Western U.S. from geodetic data, 1995-2020
Tuesday, 15 December 2020: 07:28
Virtual
Abstract:
The crustal deformation cycle is driven by interseismic elastic strain accumulation on locked or partially locked faults restrained by frictional forces. It is traditionally divided into coseismic, postseismic, and interseismic phases on which transient motions from various sources may be superimposed. It is important to distinguish between coseismic slip and the transition to mostly aseismic postseismic deformation to improve our understanding of the physics of earthquakes and crustal deformation processes and to assess postseismic moment. Furthermore, to estimate interseismic rates it is important to identify and understand the duration of the postseismic phase when using space geodetic data to invert for interseismic slip models and, to maintain a consistent underlying reference frame in the process. Large earthquakes can generate a postseismic phase that can last for decades and affect the positions of geodetic stations thousands of km from the source. In a previous study, we introduced the concept of a kinematic reference frame based on weekly displacement time series from GNSS and InSAR data processed at SIO. Here we expand the scope in space from California to the Western U.S. and in time from 2018.5 to 2020.5, which includes the effects of the July 2019 Ridgecrest earthquake sequence. We also employ a NASA MEaSUREs combination of independent JPL and SIO GNSS displacement time series and identify deviations from an interseismic slip model for the Western U.S. As discussed in another abstract by Golriz et al., we incorporate sub-daily displacements for earthquake dates after bracketing the coseismic phase using a combination of GNSS and seismic data. Finally, we assess the improvement in precision of measured surface displacements and velocities using a combination of GNSS and InSAR data.