Oral Presentation

On behalf of the Community Geodetic Model (CGM) Working Group, I present the current status of the CGM and future plans and challenges. The CGM provides the SCEC community, and beyond, with Earth surface displacements and velocities from two satellite-based sources: Global Navigation Satellite Systems (GNSS) and interferometric synthetic aperture radar (InSAR). The GNSS measurements come from both continuously operating stations as well as valuable historical survey data. These two methods combined provide both temporal and spatial density of measurements, producing a near-continuous field of surface deformation with up to daily time resolution at continuous GNSS stations. The CGM is intended to combine several sources consistently to ensure the most complete collation of geodetic data across southern California.
Version 1 of the CGM was released in 2016, near the end of SCEC 4, and consisted of time-independent velocities and interpolated grids. Version 2 of the CGM has been developed during SCEC 5, where the major changes have been to introduce time-dependent data (time series) for both GNSS and InSAR, and to have data from multiple InSAR tracks provide the dense spatial coverage across the southern California region rather than an interpolation of GNSS stations.
The major challenge with the CGM is that it is not as static as other CXMs due to the ever-extending nature of the incorporated data: Continuous GNSS time series gain an additional data point once per day and InSAR missions currently or plan to collect new data every few days. Given the occurrence of a major, or even subtle, geophysical event, these regular updates become important for researchers wishing to study such phenomena immediately, such as during SCEC 4's Transient Detection Exercise.
A more methodological challenge that remains is the consistency of the GNSS and InSAR products. This is particularly critical to success as InSAR data is used more frequently for long-term tectonic studies with small displacement rates rather than for discrete events with high signal-to-noise ratios. Current and future research includes corrections that are commonly applied to GNSS but not to InSAR, such as ocean tide and solid Earth loading, tropospheric and ionospheric signal propagation delays, and temporal correlations in the time series, including in the presence of post-seismic decays.