Here, I present a new absolute plate motion model of the Earth's surface, determined from the alignment of present‐day surface motions with 474 published shear wave (i.e., SKS) splitting ...orientations. When limited to oceanic islands and cratons, splitting orientations are assumed to reflect anisotropy in the asthenosphere caused by the differential motion between lithosphere and mesosphere. The best fit model predicts a 0.2065°/Ma counterclockwise net rotation of the lithosphere as a whole, which revolves around a pole at 57.6°S and 63.2°E. This net rotation is particularly well constrained by data on cratons and/or in the Indo‐Atlantic region. The average data misfit is 19° and 24° for oceanic and cratonic areas, respectively, but the normalized root‐mean‐square misfits are about equal at 5.4 and 5.2. Predicted plate motions are very consistent with recent hot spot track azimuths (<8° on many plates), except for the slowest moving plates (Antarctica, Africa, and Eurasia). The difference in hot spot propagation vectors and plate velocities describes the motion of hot spots (i.e., their underlying plumes). For most hot spots that move significantly, the motions are considerably smaller than and antiparallel to the absolute plate velocity. Only when the origin depth of the plume is considered can the hot spot motions be explained in terms of mantle flow. The results are largely consistent with independent evidence of subasthenospheric mantle flow and asthenospheric return flow near spreading ridges. The results suggest that, at least where hot spots are, the lithosphere is decoupled from the mesosphere, including in western North America.
We extract significant spatially coherent strain variations from horizontal seasonal Global Positioning System (GPS) displacements in the American Southwest. The dilatational strain is largest in ...northern California with maximum margin‐normal contraction and extension in spring and fall, respectively, consistent with the Earth's surface going down and up at those times. The northern California signal has a phase shift with respect to that in southern California and the Great Basin. For northern and southern California the proportion of larger earthquakes are in‐phase and the aftershock productivity out of phase with the inferred Coulomb stress on the San Andreas fault system. The intensity of mainshocks is in‐phase in the north as well but not in the south. This suggests that a seasonal increase in fault‐normal extension may or may not trigger mainshocks, but when an earthquake happens at those times, they grow larger than they otherwise would, which would cause a larger stress reduction and result in fewer aftershocks.
Plain Language Summary
The changing amount of water and snow mass that lays on top of the Earth's surface is one possible explanation for observed seasonal variations in seismicity. This hydrological loading would change the state of stress inside the crust minutely with the seasons. We image the seasonal stress variation by using the horizontal seasonal displacements of GPS monuments in the southwestern United States. This reveals large‐scale seasonal patterns of the crust contracting and extending in‐phase with the Earth's surface going down and up, respectively, particularly in northern California which experiences a large excess of water and snow in late winter. The seasonal variations in horizontal deformation there correspond to variations in the number of mainshocks, with more earthquakes occurring when the crust is under extension. In southern California, we see no correlation with the number of mainshocks. In both regions, seasonal deformation correlates with the proportion of large earthquakes and shows an anticorrelation with the aftershock production. So even though seasonal deformation may not directly trigger earthquakes, if an earthquake happens during the right season, it seems to be able to grow a little larger, releasing a little more stress than it otherwise would and reducing the need for (more) aftershocks.
Key Points
We convert 1,202 horizontal seasonal GPS displacements into a strain field for California and surroundings
Seasonal variations in dilatational strain vary regionally and, at least in northern California, are related to vertical displacements
Seasonal strain may facilitate mainshock occurrence and causes an increase in earthquake magnitude and decrease in aftershock production
Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are ...often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil‐Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj–xi)/(tj–ti) computed between all data pairs i > j. For normally distributed data, Theil‐Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil‐Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one‐sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root‐mean‐square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.
Key Points
MIDAS is a robust estimator of time series trend
MIDAS estimates of GPS velocities are resistant to outliers, steps, and seasonality
MIDAS velocities are as accurate as the best methods involving step detection
We introduce Global Positioning System (GPS) Imaging, a new technique for robust estimation of the vertical velocity field of the Earth's surface, and apply it to the Sierra Nevada Mountain range in ...the western United States. Starting with vertical position time series from Global Positioning System (GPS) stations, we first estimate vertical velocities using the MIDAS robust trend estimator, which is insensitive to undocumented steps, outliers, seasonality, and heteroscedasticity. Using the Delaunay triangulation of station locations, we then apply a weighted median spatial filter to remove velocity outliers and enhance signals common to multiple stations. Finally, we interpolate the data using weighted median estimation on a grid. The resulting velocity field is temporally and spatially robust and edges in the field remain sharp. Results from data spanning 5–20 years show that the Sierra Nevada is the most rapid and extensive uplift feature in the western United States, rising up to 2 mm/yr along most of the range. The uplift is juxtaposed against domains of subsidence attributable to groundwater withdrawal in California's Central Valley. The uplift boundary is consistently stationary, although uplift is faster over the 2011–2016 period of drought. Uplift patterns are consistent with groundwater extraction and concomitant elastic bedrock uplift, plus slower background tectonic uplift. A discontinuity in the velocity field across the southeastern edge of the Sierra Nevada reveals a contrast in lithospheric strength, suggesting a relationship between late Cenozoic uplift of the southern Sierra Nevada and evolution of the southern Walker Lane.
Plain Language Summary
Mountain growth attributable to the steady action of plate tectonics is difficult to observe directly because it is extremely slow. We developed a new method called GPS Imaging to combine and filter large datasets of high precision GPS data that have been collected for many years in California and Nevada. We use the method to generate new informative images of the workings of the uplift of Sierra Nevada Mountains, earthquake cycle deformation, and regional subsidence attributable to groundwater withdrawal. The Sierra Nevada experiences uplift of up to 2 mm/yr (about 8 inches per century), and that uplift is faster in more recent years confirming that some of it is a response to climate change and human controlled pumping of groundwater that intensified during the drought of 2012–2015. The images also reveal a break in the Earth's plate, separating the Sierra Nevada from the Great Basin, and allowing the Sierra crest to rise more quickly.
Key Points
GPS Imaging is a new technique that provides a temporally and spatially robust vertical velocity field for geodynamic studies
The Sierra Nevada is the most rapid and extensive uplift feature in the western United States, rising up to 2 mm/yr
Images of an uplift discontinuity suggest that current rise of the Sierra Nevada is associated with evolution of the southern Walker Lane
The Global Positioning System (GPS) has revolutionized the ability to monitor Earth-system processes, including Earth’s water cycle. Several analysis centers process GPS data to estimate ...ground-antenna positions at daily temporal resolution. Differences in processing strategies can lead to inconsistencies in coordinate-position estimates and therefore influence the analysis of crustal displacement associated with variations in atmospheric and hydrologic mass loading. Here, we compare five GPS data products produced by three processing centers: the Nevada Geodetic Laboratory, Jet Propulsion Laboratory, and UNAVCO Consortium. We find that 5 to 30% of the scatter in residual GPS time series (commonly considered noise) can be explained by atmospheric loading in the contiguous USA and Alaska, but that the percentages vary widely by data product. Positions derived using high-resolution troposphere models (e.g., ECMWF) exhibit significantly lower scatter after correcting for atmospheric loading than positions estimated using constant or slowly varying troposphere models (e.g., GPT2w). The data products also exhibit differences in seasonal deformation (commonly attributed, in large part, to fluctuations in hydrologic mass loading): median vector differences in estimated seasonal amplitude range from 0.4–1.0 mm in the vertical component and 0.1–0.3 mm in the horizontal components, or about 10–40% of the mean amplitudes of seasonal oscillation. Newer products exhibit lower total scatter and stronger correlations than older products. Network-coherent differences in estimates of seasonal deformation reveal reference-frame inconsistencies between data products. We also cross-check two independent models of atmospheric pressure loading: ESMGFZ and LoadDef.
We estimate the rates and patterns of vertical land motion (VLM) on all locations on Earth's land surface using GPS Imaging. The solution is based on a large database of uniformly processed GPS data ...from solutions that are aligned to the International Terrestrial Reference Frame. We provide global maps and estimates of VLM at all tide gauges of the Permanent Service for Mean Sea Level to better constrain the difference between geocentric and relative sea level rise. To enable critical assessment of the VLM estimate, the temporal and spatial contributions to rate uncertainty and variability are generated and included for every gauge. Seasonality and trends of uplift are assessed and found to be strongly correlated with observations from gravity data suggesting that loading from the terrestrial hydrosphere is a dominant driver of non‐glacial isostatic adjustment (non‐GIA) VLM. Although stations are dominantly concentrated at subsiding parts of continents, GPS Imaging geographically balances VLM signals, correcting for bias associated with network distribution. This allows us to make a global assessment of the budget of uplift and subsidence attributable to GIA and non‐GIA sources. We show that the surface motion of the continents is on average upward, implying that the unobserved areas (composed of the ocean basins and ice‐covered areas) move on average downward with respect to Earth center. However, after correcting for the GIA the reverse is true, and observed areas subside on average implying that the unobserved areas undergo net non‐GIA‐related uplift.
Plain Language Summary
Sea level rise is a global problem. To project its impacts on coastal communities and understand its physical sources requires observation of active vertical land motion across all of the Earth's continents. Vertical motion of the land directly affects coastal relative sea level rise and has many possible driving mechanisms, for example, plate tectonic movements, earthquakes, subsidence from aquifer withdrawal, postglacial rebound, or other active geophysical processes. The precision, coverage, and prevalence of open data holdings that are now available from GPS stations around the world provide a unique data set for constraining these movements on a global scale. Since GPS stations around the world are very heterogeneously distributed on land our analysis emphasizes robust methods to obtain geographically balanced estimates of a global field. We use these estimates to show the rates and patterns of vertical land movement and evaluate the balance of uplift and subsidence across the Earth's surface. We provide maps and rates at over 2,300 tide gauges around the world which will be used to project the rates of sea level rise into the future.
Key Points
GPS stations constrain trends, seasonal and nonseasonal variability in vertical land motion (VLM) across the Earth's land surface
GPS Imaging provides robust VLM estimates and more completely assesses spatial and temporal signal uncertainty and variability
Average VLM is positive on the land areas and subsidence elsewhere, but average non‐GIA VLM is subsidence on average and uplift elsewhere
We distinguish between two models of solid Earth's viscoelastic response to unloading of the Laurentide ice sheet over the past 26,000 years. The upper mantle viscosity in both models is ...0.5 × 1021 Pa s. The viscosity of the top 500 km of the lower mantle (670–1,170 km) in model L17 is 13 × 1021 Pa s, eight times larger than the value of 1.6 × 1021 Pa s in ICE‐6G_D (VM5a). In ICE‐6G_D (VM5a), viscous relaxation of solid Earth was rapid 8,000 years ago and is slow today, with present‐day uplift at the Laurentide ice center being 12 mm/yr. In L17, solid Earth relaxed more slowly 8,000 years ago but is faster today, with present uplift of the ice center occurring at 20 mm/yr. The significant difference is not due to different ice histories given that total ice loss in L17 is just 12% less than in ICE‐6G_D. We determine a comprehensive set of GPS uplift rates for North America that is more accurate than in prior studies due to (1) more sites and a longer data time history, (2) removal of elastic loading produced by increase in Great Lakes water, and (3) technical advances in GPS positioning that have significantly reduced the dispersion in position estimates. We find uplift at the ice center to be about 12 mm/yr, supporting the low value of the viscosity of the top 500 km of the lower mantle in ICE‐6G_D (VM5a), but ruling out the high value in L17.
Key Points
Laurentia is today rising at just ≈12 mm/yr, showing that solid Earth has to a large extent viscously relaxed in response to ice unloading
The viscosity of the top third of the lower mantle is roughly 1.6 × 1021 Pa s, not 10 × 1021 Pa s or higher
Correcting Gravity Recovery and Climate Experiment data for glacial isostatic adjustment using the high viscosity value results in implausibly fast estimates of water loss
We present a new method to estimate common-mode components (CMC) in global positioning system (GPS) position time-series. The method (‘CMC Imaging’) is fully automated, relies entirely on robust ...statistics, and exploits the recent proliferation of GPS stations by allowing stations with relatively short time-series to be considered as filter stations as well. The spatial extent of the CMC is purposely defined as local as possible and constrained by the proximity of nearby GPS stations. Our approach also avoids the need for subjective assignment of filter stations; every station is considered and those stations that deviate significantly from the local CMC are flagged and excluded as filter stations. We study thousands of GPS position time-series in the intraplate area of western Europe, and we show that CMC Imaging method is superior to other approaches in terms of noise reduction: we obtain an RMS reduction of 50%, 44% and 39% in the residual time-series in vertical, east, and north components, respectively. We show the importance of using filter stations that are as local as possible, because of systematic lateral variations in inter-station correlations and indeed in CMC, particularly in the vertical component. Those spatial variations are largest for continental stations, particularly those around the Baltic Sea, and could be due to atmospheric and nontidal ocean loading. CMC filtering has a large influence on reducing the temporal trend variability and approximately doubles the trend accuracy (by comparing variability in short-term trends with the long-term estimate).
The 26 December 2004 Sumatra earthquake (Mw 9.2–9.3) generated the most deadly tsunami in history. Yet within the first hour, the true danger of a major oceanwide tsunami was not indicated by seismic ...magnitude estimates, which were far too low (Mw 8.0–8.5). This problem relates to the inherent saturation of early seismic‐wave methods. Here we show that the earthquake's true size and tsunami potential can be determined using Global Positioning System (GPS) data up to only 15 min after earthquake initiation, by tracking the mean displacement of the Earth's surface associated with the arrival of seismic waves. Within minutes, displacements of >10 mm are detectable as far away as India, consistent with results using weeks of data after the event. These displacements imply Mw 9.0 ± 0.1, indicating a high tsunami potential. This suggests existing GPS infrastructure could be developed into an effective component of tsunami warning systems.
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