Validation of ShakeMaps Created From Global Navigation Satellite System (GNSS) Velocities

Ground velocity observations generated through a time difference of Global Navigation Satellite Systems (GNSS) phase observables and orbits have been shown to be comparable to seismic recordings without clipping during intense ground motions. Computing GNSS velocities is also computationally scalable and increases the density of ground motion observations during significant earthquakes, so their inclusion into ShakeMaps can potentially improve rapid assessments of strong ground motion. Here, we present ShakeMaps created using GNSS velocities as an additional instrumental recording in the existing interpolation scheme for a total of 16 unique earthquake events. We thoroughly analyze four of these earthquakes (2016 M6.6 Norcia, Italy; 2019 M7.1 Ridgecrest, California; 2016 M7.8 Kaikoura, New Zealand; and 2020 M6.5 Challis, Idaho) with the goal of showcasing the broad application for a variety of earthquake rupture characteristics and regional instrument coverage. We validate all ShakeMap instances against published results that currently use only seismic instrumental recordings in their interpolation scheme. For both our approach and published results, we compare the instrument‐derived ground motions and the ShakeMap‐inferred ground motions directly. In our approach, we find the geodetic stations exhibit a standard deviation of 0.36 natural log units while the seismic stations are not degraded in performance. Additionally, where collocated geodetic and seismic observations exist, we quantitatively assess any biases between the geodetically derived velocity waveforms and the seismically derived velocity waveforms. Lastly, we assess the optimal weighting within the interpolation for intensity observations produced with peak ground accelerations (PGA), peak ground velocities (PGVs) from seismic instruments and geodetic instruments. This article shows that including GNSS velocities can further constrain the interpolation schemes used in ShakeMaps and potentially lead to a better constraint on ground motions and shaking intensity realized for different earthquakes observed by real‐world irregular sensor network geometries.