Bayesian Estimation of Surface Strain Rates from GNSS Measurements: application to the Southwestern US

Pagani, Colin; Bodin, Thomas; Métois, Marianne; Lasserre, Cécile

doi:10.1002/essoar.10506326.1

Cited by 2 publications

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“…The 3‐D velocity maps derived from the InSAR/GNSS combination have small spatial scale variations that are associated with hydrological processes and residual atmospheric error. These models must be smoothed to extract the underlying tectonic strain rate (e.g., Pagani et al., 2021; Weiss et al., 2020). This is accomplished by using a smoothing interpolator that has constraints from elasticity to couple the two horizontal velocity components (Haines & Holt, 1993) as implemented in the GMT program gpsgridder (Sandwell & Wessel, 2016).…”

Section: Analysis Results and Discussionmentioning

confidence: 99%

Integrated Sentinel‐1 InSAR and GNSS Time‐Series Along the San Andreas Fault System

Sandwell

Klein

et al. 2021

JGR Solid Earth

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An improved understanding of how energy and seismic moment accumulate in the crust and upper mantle along major plate boundaries is essential for forecasting the size and timing of major earthquakes (Field et al., 2015;Rollins et al., 2020;Smith-Konter & Sandwell, 2009;Weiss et al., 2020). Recent studies have shown that most damaging earthquakes occur in areas where the crustal strain rate exceeds 100 nanostrain/yr (e.g., Bayona et al., 2021;Elliott et al., 2016;Zeng et al., 2018). Many of these areas are heavily populated and have been struck by major destructive earthquakes in the past (Ward et al., 2021). Moreover, one of the largest uncertainties in earthquake hazard models (e.g., California's UCERF-3 model (Field et al., 2014(Field et al., , 2015 is the amount of plate boundary deformation that is accommodated by off-fault strain and whether this strain is accumulating as elastic or plastic deformation. Therefore, accurate strain rate measurements are needed to improve earthquake forecasts. Achieving an ideal 100-nanostrain/yr accuracy in California at an ideal 10-km resolution (i.e., the typical fault locking depth) requires a horizontal velocity model that has an accuracy of 1 mm/yr. Besides, moderate earthquakes, fault creep, and other

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Section: Analysis Results and Discussionmentioning

confidence: 99%

Integrated Sentinel‐1 InSAR and GNSS Time‐Series Along the San Andreas Fault System

Sandwell

Klein

et al. 2021

JGR Solid Earth

View full text Add to dashboard Cite

show abstract

“…The 3-D velocity maps derived from the InSAR/GNSS combination have small spatial scale variations that are associated with hydrological processes and residual atmospheric error. These models must be smoothed to extract the underlying tectonic strain rate (e.g., Pagani et al, 2021;Weiss et al, 2020). This is accomplished by using a smoothing interpolator that has constraints from elasticity to couple the two horizontal velocity components (Haines & Holt, 1993) as implemented in the GMT program gpsgridder .…”

Section: Strain Ratementioning

confidence: 99%

Integrated Sentinel-1 InSAR and GNSS time-series along the San Andreas fault system

Sandwell

Klein

et al. 2021

Preprint

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Bayesian Estimation of Surface Strain Rates from GNSS Measurements: application to the Southwestern US

Cited by 2 publications

References 0 publications

Integrated Sentinel‐1 InSAR and GNSS Time‐Series Along the San Andreas Fault System

Integrated Sentinel‐1 InSAR and GNSS Time‐Series Along the San Andreas Fault System

Integrated Sentinel-1 InSAR and GNSS time-series along the San Andreas fault system

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