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A pinboard by
Anna Riddell

PhD Candidate, University of Tasmania

PINBOARD SUMMARY

Vertical land motion confounds measurements of sea level from tide gauges and needs to be corrected.

Global mean sea level rise is one of the most important indicators of climate change. Sea level observations from tide gauges provide an observation that is relative to the land that the instrument is attached to and are subsequently affected by vertical land motion. Relative sea level measurements are important for understanding local implications of inundation and adaptation methods, but the combination of sea level estimates from satellite and ground techniques for global studies requires absolute estimates of sea level where vertical land motion is accounted for. A range of processes, which occur over various timescales, drive vertical movement of the Earth's surface. These processes include uplift and/or subsidence caused by mass changes such as the ongoing elastic response of the crust to ice-ocean loading changes, pressure from the atmosphere and oceans, as well as human induced effects like the extraction of resources like groundwater and natural gas. One method for observing vertical land motion is using a tracking network of permanently installed Global Positioning System (GPS) receivers that provide continuous time series of coordinate positions. Collecting continuous data allows the motion of the Australian plate to be tracked over time. My research will look at improving the processing of GPS stations in Australia by improving the understanding of how vertical land motion aliases with the input of different geophysical simulations. The resulting vertical land motion estimates will be compared to geophysical simulation outputs and applied to sea level measurements in Australia. This will improve sea level research around the Australian coastline, allowing for better coastal management and preparedness for global change monitoring and assessment.

7 ITEMS PINNED

Lithospheric controls on magma composition along Earth's longest continental hotspot track.

Abstract: Hotspots are anomalous regions of volcanism at Earth's surface that show no obvious association with tectonic plate boundaries. Classic examples include the Hawaiian-Emperor chain and the Yellowstone-Snake River Plain province. The majority are believed to form as Earth's tectonic plates move over long-lived mantle plumes: buoyant upwellings that bring hot material from Earth's deep mantle to its surface. It has long been recognized that lithospheric thickness limits the rise height of plumes and, thereby, their minimum melting pressure. It should, therefore, have a controlling influence on the geochemistry of plume-related magmas, although unambiguous evidence of this has, so far, been lacking. Here we integrate observational constraints from surface geology, geochronology, plate-motion reconstructions, geochemistry and seismology to ascertain plume melting depths beneath Earth's longest continental hotspot track, a 2,000-kilometre-long track in eastern Australia that displays a record of volcanic activity between 33 and 9 million years ago, which we call the Cosgrove track. Our analyses highlight a strong correlation between lithospheric thickness and magma composition along this track, with: (1) standard basaltic compositions in regions where lithospheric thickness is less than 110 kilometres; (2) volcanic gaps in regions where lithospheric thickness exceeds 150 kilometres; and (3) low-volume, leucitite-bearing volcanism in regions of intermediate lithospheric thickness. Trace-element concentrations from samples along this track support the notion that these compositional variations result from different degrees of partial melting, which is controlled by the thickness of overlying lithosphere. Our results place the first observational constraints on the sub-continental melting depth of mantle plumes and provide direct evidence that lithospheric thickness has a dominant influence on the volume and chemical composition of plume-derived magmas.

Pub.: 15 Sep '15, Pinned: 17 Aug '17

Earth's first stable continents did not form by subduction.

Abstract: The geodynamic environment in which Earth's first continents formed and were stabilized remains controversial. Most exposed continental crust that can be dated back to the Archaean eon (4 billion to 2.5 billion years ago) comprises tonalite-trondhjemite-granodiorite rocks (TTGs) that were formed through partial melting of hydrated low-magnesium basaltic rocks; notably, these TTGs have 'arc-like' signatures of trace elements and thus resemble the continental crust produced in modern subduction settings. In the East Pilbara Terrane, Western Australia, low-magnesium basalts of the Coucal Formation at the base of the Pilbara Supergroup have trace-element compositions that are consistent with these being source rocks for TTGs. These basalts may be the remnants of a thick (more than 35 kilometres thick), ancient (more than 3.5 billion years old) basaltic crust that is predicted to have existed if Archaean mantle temperatures were much hotter than today's. Here, using phase equilibria modelling of the Coucal basalts, we confirm their suitability as TTG 'parents', and suggest that TTGs were produced by around 20 per cent to 30 per cent melting of the Coucal basalts along high geothermal gradients (of more than 700 degrees Celsius per gigapascal). We also analyse the trace-element composition of the Coucal basalts, and propose that these rocks were themselves derived from an earlier generation of high-magnesium basaltic rocks, suggesting that the arc-like signature in Archaean TTGs was inherited from an ancestral source lineage. This protracted, multistage process for the production and stabilization of the first continents-coupled with the high geothermal gradients-is incompatible with modern-style plate tectonics, and favours instead the formation of TTGs near the base of thick, plateau-like basaltic crust. Thus subduction was not required to produce TTGs in the early Archaean eon.

Pub.: 28 Feb '17, Pinned: 17 Aug '17

Spatiotemporal filtering for regional GPS network in China using independent component analysis

Abstract: Abstract Removal of the common mode error (CME) is a routine procedure in postprocessing regional GPS network observations, which is commonly performed using principal component analysis (PCA). PCA decomposes a network time series into a group of modes, where each mode comprises a common temporal function and corresponding spatial response based on second-order statistics (variance and covariance). However, the probability distribution function of a GPS time series is non-Gaussian; therefore, the largest variances do not correspond to the meaningful axes, and the PCA-derived components may not have an obvious physical meaning. In this study, the CME was assumed statistically independent of other errors, and it was extracted using independent component analysis (ICA), which involves higher-order statistics. First, the ICA performance was tested using a simulated example and compared with PCA and stacking methods. The existence of strong local effects on some stations causes significant large spatial responses and, therefore, a strategy based on median and interquartile range statistics was proposed to identify abnormal sites. After discarding abnormal sites, two indices based on the analysis of the spatial responses of all sites in each independent component (east, north, and vertical) were used to define the CME quantitatively. Continuous GPS coordinate time series spanning \(\sim \) 4.5 years obtained from 259 stations of the Tectonic and Environmental Observation Network of Mainland China (CMONOC II) were analyzed using both PCA and ICA methods and their results compared. The results suggest that PCA is susceptible to deriving an artificial spatial structure, whereas ICA separates the CME from other errors reliably. Our results demonstrate that the spatial characteristics of the CME for CMONOC II are not uniform for the east, north, and vertical components, but have an obvious north–south or east–west distribution. After discarding 84 abnormal sites and performing spatiotemporal filtering using ICA, an average reduction in scatter of 6.3% was achieved for all three components.AbstractRemoval of the common mode error (CME) is a routine procedure in postprocessing regional GPS network observations, which is commonly performed using principal component analysis (PCA). PCA decomposes a network time series into a group of modes, where each mode comprises a common temporal function and corresponding spatial response based on second-order statistics (variance and covariance). However, the probability distribution function of a GPS time series is non-Gaussian; therefore, the largest variances do not correspond to the meaningful axes, and the PCA-derived components may not have an obvious physical meaning. In this study, the CME was assumed statistically independent of other errors, and it was extracted using independent component analysis (ICA), which involves higher-order statistics. First, the ICA performance was tested using a simulated example and compared with PCA and stacking methods. The existence of strong local effects on some stations causes significant large spatial responses and, therefore, a strategy based on median and interquartile range statistics was proposed to identify abnormal sites. After discarding abnormal sites, two indices based on the analysis of the spatial responses of all sites in each independent component (east, north, and vertical) were used to define the CME quantitatively. Continuous GPS coordinate time series spanning \(\sim \) 4.5 years obtained from 259 stations of the Tectonic and Environmental Observation Network of Mainland China (CMONOC II) were analyzed using both PCA and ICA methods and their results compared. The results suggest that PCA is susceptible to deriving an artificial spatial structure, whereas ICA separates the CME from other errors reliably. Our results demonstrate that the spatial characteristics of the CME for CMONOC II are not uniform for the east, north, and vertical components, but have an obvious north–south or east–west distribution. After discarding 84 abnormal sites and performing spatiotemporal filtering using ICA, an average reduction in scatter of 6.3% was achieved for all three components. \(\sim \) \(\sim \)

Pub.: 19 Nov '16, Pinned: 07 Aug '17

Long-term vertical land motion from double-differenced tide gauge and satellite altimetry data

Abstract: We present a new approach to estimate precise long-term vertical land motion (VLM) based on double-differences of long tide gauge (TG) and short altimetry data. We identify and difference rates of pairs of highly correlated sea level records providing relative VLM estimates that are less dependent on record length and benefit from reduced uncertainty and mitigated biases (e.g. altimeter drift). This approach also overcomes the key limitation of previous techniques in that it is not geographically limited to semi-enclosed seas and can thus be applied to estimate VLM at TGs along any coast, provided data of sufficient quality are available. Using this approach, we have estimated VLM at a global set of 86 TGs with a median precision of 0.7 mm/year in a conventional reference frame. These estimates were compared to previous VLM estimates at TGs in the Baltic Sea and to estimates from co-located Global Positioning System (GPS) stations and Glacial Isostatic Adjustment (GIA) predictions. Differences with respect to the GPS and VLM estimates from previous studies resulted in a scatter of around 0.6 mm/year. Differences with respect to GIA predictions had a larger scatter in excess of 1 mm/year. Until satellite altimetry records reach enough length to estimate precise VLM at each TG, this new approach constitutes a substantial advance in the geodetic monitoring of TGs with major applications in long-term sea level change and climate change studies.

Pub.: 08 Dec '13, Pinned: 31 Jul '17

The IGS contribution to ITRF2014

Abstract: Following the first reprocessing campaign performed by the International GNSS Service (IGS) in 2008, a second reprocessing campaign (repro2) was finalized in 2015. Nine different Analysis Centers (ACs) reanalyzed the history of GNSS data collected by a global tracking network back to 1994 using the latest available models and methodology, and provided daily terrestrial frame solutions among other products. Daily combinations of the AC terrestrial frame solutions provided the IGS input to the next release of the International Terrestrial Reference Frame (ITRF2014). From weighted root mean squares values of the residuals of the daily repro2 combinations, the overall inter-AC level of agreement is assessed to be 1.5 mm for the horizontal components and 4 mm for the vertical component of station positions, 25–40 \(\upmu \)as for pole coordinates, 140–200 \(\upmu \)as/day for pole rates, 8–20 \(\upmu \)s/day for calibrated length-of-day estimates, 4 mm for the X and Y components of geocenter motion, 8 mm for its Z component and 0.5 mm for the terrestrial scale. On the long term, the origins (resp. scales) of the AC terrestrial frames show relative offsets and rates within \(\pm \)3 mm and \(\pm \)0.3 mm/year (resp. \(\pm \)0.5 mm and \(\pm \)0.05 mm/year). The combination residuals also present AC-specific features, some of which are explained by known analysis specifics, while others remain under investigation.

Pub.: 08 Apr '16, Pinned: 31 Jul '17

GPS Imaging of vertical land motion in California and Nevada: Implications for Sierra Nevada uplift.

Abstract: 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.

Pub.: 06 Dec '16, Pinned: 31 Jul '17