Vertical Postseismic Deformation of the 2019 Ridgecrest Earthquake Sequence

Ward, L. A.; Guns, K. A.; Smith-Konter, B. R.; Xu, Xiaohua; Bock, Yehuda; Sandwell, David T.

doi:10.1029/2021jb023331

Cited by 5 publications

(1 citation statement)

References 65 publications

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“…1). We see postseismic uplift around the 1999 Hector Mine, 1992 Landers [22], and uplift and subsidence associated with 2019 Ridgecrest earthquake [24]. Most of these large-scale natural processes appear to be stable in this study time-span (temp.…”

Section: Estimating Spatially and Temporally Varying Vertical Land Mo...mentioning

confidence: 68%

Variable vertical land motion for sea level rise projections

Govorcin,

Bekeart,

Hamlington

et al. 2024

Preprint

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Accurate projections of future sea level depend on adequately representing contributions from the land and ocean. The Intergovernmental Panel On Climate Change-6th Assessment Report made significant progress with most contributors to relative sea level rise. However, coastal vertical land motion (VLM) remained unchanged from previous assessments, due in part to challenges with its spatial and temporal variability. Here, we outline a framework for estimating varying VLM in fine detail, and projecting it into the future. Along the 1700-km long California coast, we show that localized VLM, often missing in current frameworks, could double current sea-level projections by 2050 in parts of San Francisco and Los Angeles. We introduce a temporary variability metric to distinguish locations with stable from changing VLM trends, typically driven by human activities. This research underscores nonlinear VLM and its uncertainties in projections, and calls out for localized monitoring to address its impacts on relative sea-level changes.

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Section: Estimating Spatially and Temporally Varying Vertical Land Mo...mentioning

confidence: 68%

Variable vertical land motion for sea level rise projections

Govorcin,

Bekeart,

Hamlington

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Sensitivity of GNSS to vertical land motion over Europe: effects of geophysical loadings and common-mode errors

Hohensinn,

Ruttner,

Bock

2024

J Geod

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We perform a statistical sensitivity analysis on a parametric fit to vertical daily displacement time series of 244 European Permanent GNSS stations, with a focus on linear vertical land motion (VLM), i.e., station velocity. We compare two independent corrections to the raw (uncorrected) observed displacements. The first correction is physical and accounts for non-tidal atmospheric, non-tidal oceanic and hydrological loading displacements, while the second approach is an empirical correction for the common-mode errors. For the uncorrected case, we show that combining power-law and white noise stochastic models with autoregressive models yields adequate noise approximations. With this as a realistic baseline, we report improvement rates of about 14% to 24% in station velocity sensitivity, after corrections are applied. We analyze the choice of the stochastic models in detail and outline potential discrepancies between the GNSS-observed displacements and those predicted by the loading models. Furthermore, we apply restricted maximum likelihood estimation (RMLE), to remove low-frequency noise biases, which yields more reliable velocity uncertainty estimates. RMLE reveals that for a number of stations noise is best modeled by a combination of random walk, flicker noise, and white noise. The sensitivity analysis yields minimum detectable VLM parameters (linear velocities, seasonal periodic motions, and offsets), which are of interest for geophysical applications of GNSS, such as tectonic or hydrological studies.

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