ORCID Profile
0000-0002-2620-295X
Current Organisation
L-Università ta' Malta
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Copernicus GmbH
Date: 27-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-4477
Abstract: & & The maximum achievable resolution of a tomographic model varies spatially and depends on the data s ling and errors in the data. The significant and continual measurement-error decreases in seismology and data-redundancy increases have reduced the impact of random errors on tomographic models. Systematic errors, however, are resistant to data redundancy and their effect on the model is difficult to predict often this results in models dominated by noise if the target resolution is too high. Here, we develop a method for finding the optimal resolving length at every point, implementing it for surface-wave tomography. As in the Backus-Gilbert method, every solution at a point results from an entire-system inversion, and the model error is reduced by increasing the model-parameter averaging. The key advantage of our method consists in its direct, empirical evaluation of the posterior model error at a point.& & & & We first measure interstation phase velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Numerous versions of the maps with varying smoothness are then computed, ranging from very rough to very smooth. Phase-velocity curves extracted from the maps at every point can be inverted for shear-velocity (V& sub& S& /sub& ) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. We evaluate the error by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure and determine the optimal resolving length at a point such that the error of the local phase-velocity curve is below a threshold.& & & & A 3-D V& sub& S& /sub& model is then computed by the inversion of the composite phase-velocity maps with an optimal resolution at every point. Importantly, the optimal resolving length does not scale with the density of the data coverage: some of the best-s led locations display relatively low lateral resolution, due to systematic errors in the data.& & & & We apply this method to image the lithosphere and underlying mantle beneath Ireland and Britain. Our very large data produces a total of 11238 inter-station dispersion curves, spanning a very broad total period range (4& #8211 s), yielding unprecedented data coverage of the area and providing state-of-the-art regional resolution from the crust to the deep asthenosphere. Our tomography reveals pronounced, previously unknown variations in the lithospheric thickness beneath Ireland and Britain, with implications for their Caledonian assembly and for the mechanisms of the British Tertiary Igneous Province magmatism.& &
Publisher: American Geophysical Union (AGU)
Date: 08-2012
DOI: 10.1029/2012GC004138
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-11942
Abstract: & & The maximum achievable resolution of a tomographic model varies spatially and depends on the data s ling and errors in the data. Adaptive parameterization schemes match the spatial variations in data s ling but do not address the effects of the errors. The propagation of systematic errors, however, is resistant to data redundancy and results in models dominated by noise if the target resolution is too high. This forces us to look for smoother models and thus limits the imaging resolution.& br& & br& We develop a surface-wave tomography method that finds optimal lateral resolution at every point by means of error tracking. We first measure inter-station phase-velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Unlike in the classical approach, multiple versions of the maps with varying smoothness constraints are computed, so that the maps range from very rough to very smooth. Phase-velocity curves extracted from the maps at every point can then be inverted for shear-velocity (V& sub& s& /sub& ) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. Very smooth V& sub& s& /sub& models computed from very smooth phase-velocity maps will be the most robust, but at a cost of a loss of most structural information. At the other extreme, models that are too rough will be dominated by noise. We define the optimal resolution at a point such that the error of the local phase-velocity curve is below an empirical threshold. The error is estimated by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure. A 3D V& sub& s& /sub& model is then computed by the inversion of the phase-velocity maps with the optimal resolution at every point. The estimated optimal resolution shows smooth lateral variations, confirming the robustness of the procedure. Importantly, optimal resolution does not scale with the density of the data coverage: some of the best-s led locations require relatively low lateral resolution, probably due to systematic data errors. We apply the method to image the Ireland& #8217 s and Britain& #8217 s upper mantle, using our large, new regional dataset. We report a pronounced thinning of the lithosphere beneath the British Tertiary Igneous Province, with important implications for the Paleogene uplift and volcanism in the region.& &
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-11754
Abstract: & & Spatial resolution, as the ability to distinguish different features that are close together, is a fundamental concept in seismic tomography and other imaging fields. In contrast with microscopy or telescopy, seismic tomography& #8217 s images are computed, and their resolution has a complex, non-linear dependence on the data s ling and errors. Linear inverse theory provides a useful resolution-analysis approach, defining resolution in terms of the closeness of the resolution matrix to the identity matrix. This definition is similar to the universal, multi-disciplinary one in some contexts but erges from it markedly in others. In this work, we adopt the universal definition of resolution (the minimum distance at which two spike anomalies can be resolved). The highest achievable resolution of a tomographic model then varies spatially and depends on the data s ling and errors in the data. We show that the propagation of systematic errors is resistant to data redundancy and results in models dominated by noise if the target resolution is too high. This forces one to look for smoother models and effectively limits the resolution. Here, we develop a surface-wave tomography method that finds optimal lateral resolution at every point by means of error tracking.& br& We first measure interstation phase velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Multiple versions of the maps with varying smoothness are computed, ranging from very rough to very smooth. Phase-velocity curves extracted from the maps at every point are then inverted for shear-velocity (V& sub& S& /sub& ) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. Very smooth V& sub& S& /sub& models computed from very smooth phase-velocity maps will be the most accurate, but at a cost of a loss of most structural information. At the other extreme, models that are too rough will be dominated by noise. We define the optimal resolution at a point such that the error of the local phase-velocity curve is below an empirical threshold. The error is estimated by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure.& br& A 3D V& sub& S& /sub& model is then computed by the inversion of the phase-velocity maps with the optimal resolution at every point. The estimated optimal resolution shows smooth lateral variations, confirming the robustness of the procedure. Importantly, optimal resolution does not scale with the density of the data coverage: some of the best-s led locations require relatively low lateral resolution, probably due to systematic errors in the data.& br& We apply the method to image the lithosphere and underlying mantle beneath Ireland and Britain, using 11238 newly measured, broadband, inter-station dispersion curves. The lateral resolution of the 3D model is computed explicitly and varies from 39 km in central Ireland to over 800 km at the region boundaries, where the data coverage declines. Our tomography reveals pronounced, previously unknown variations in the lithospheric thickness beneath the region, with implications for the Caledonian assembly of the islands& #8217 landmass and the mechanism of the magmatism of the British Tertiary Igneous Province.& &
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Matthew Agius.