1,721,517 research outputs found
Uncertainty budget of solid Earth data reductions to global gravity models
Full text linkSolid Earth applications of satellite gravity models commonly involve some type of data reduction - i.e. forward
modelling the gravity effect of known mass distributions to isolate an anomaly from the observed field, which is
then attributed to the enquired phenomenon. The adopted "known masses" suffer from the uncertainties arising
from the non-modelled variance in the shape of geological bodies and the density distribution therein. These
uncertainties are propagated to the reduced gravity field, superimposed to the formal errors provided with the
gravity model. Given the different origin between formal errors of satellite global gravity models (GGM), arising
from observation and noise models, and the contribution of geophysical data reductions, we aimed at assessing
the comprehensive error characteristics of reduced-GGMs.
In order to do so, we computed a set of common reductions (topography, crustal layers, mantle inhomogeneities)
using a combination of spectral- and space-domain forward modelling. Uncertainties in the input
quantities (depths and densities) were propagated trough Monte Carlo methods.
Geometries were constrained by a topography-bedrock-ice model (Earth2014), by a global layered model of the
lithosphere (LITHO1.0), and by local higher detail models of the crust and sediments, where available. Depth
uncertainties, if not provided with the input data, were assigned according to method-specific assumptions. Estimates of density and its variance come from probability distributions fitted to literature data, from petrophysical
relationships (e.g. velocity-composition-temperature) and from worst-case assumptions where no sufficient data is
available.
We report the outcome of a set of global models, at a resolution and spectral content coherent with the
currently available satellite-only GGMs. We resort to global uncertainty maps and to the familiar representations
employed in GGM sensitivity assessments (e.g. degree error curves). Different combinations of data reductions
were applied, simulating the interest in different anomalies (e.g. by correcting either for the crust or the mantle)
Uncertainity of satellite – gravity – derived Moho estimates : Contribution of data reductions
Full text linkIn the last years, the unparalleled spatial homogeneity provided by satellite-only global gravity models has been successfully exploited to obtain estimates on mass distribution in the solid Earth. Among these, the depth of the crust-mantle boundary (Mohorovicic discontinuity), has been a successful target of regional and global studies. Even when simplified to a sharp density discontinuity surface, its knowledge enables a reliable infill between terrestrial data, chiefly from seismic methods, and can be applied to the evaluation and comparison of different crustal models, at similar spatial scales.
Owing to the high degrees of GOCE-based GGMs, the theoretical resolving power can be estimated on the order of 0.1 km depth-wise, at less than 1 arc-degree of horizontal resolution. Such estimate assumes a perfectly isolated signal, i.e. no unmodelled masses in the data reductions, in a correctly constrained inversion (no unknown a-priori parameters, e.g. crust-mantle density contrast).
The Moho depth can be estimated from gravity data by solving the inverse problem relating the relief of a density discontinuity to the observed gravity field. This problem requires two input parameters, a density contrast and a reference depth; it is also necessary to isolate the signal due to Moho relief from all other contributions to the gravity field.
Input parameters are usually constrained by seismic data. Data reductions, applied to isolate a "residual anomaly", commonly consists in the forward-modelled effect of topography, of masses both above (e.g. sediments, upper crustal boundaries), and below the crust-mantle boundary (e.g. lateral density variations in the mantle).
Any variance in the input densities and geometries used in the data reduction, if not accounted for, and any uncertainty in the adopted constraints, is mapped in the inversion results, and thus propagated in any subsequent modelling that makes use of crustal thickness (e.g. temperature, rheology, velocity corrections). An uncertainty estimate is now commonly distributed alongside Moho depth models.
Starting from the theoretical Moho depth-error estimate, obtained from formal errors in the global gravity model, we compute the uncertainty effect that each data reduction step adds to this estimate. The gravity uncertainty is then propagated to a depth estimate using a reference inversion operator. This provides a quantitative assessment of the suitability of satellite-only GGMs in detecting Moho features, at different wavelengths, in a realistic geophysical framework. It also highlights where improvement in critical parameters would be more rewarding in terms of uncertainty reduction.
Up to degree and order 280, the cumulative reduction uncertainty can exceed 200 mGal, in terms of gravity anomaly. This results in local Moho depth uncertainties in the order of 10 km. A 10 points percent simulated improvement in the sediment thickness error improves the Moho depth uncertainty range by up to 1 km. This indicates that even slight improvements, such as the harmonisation of existing near-surface data, can pay off in terms of quality of gravity inversion estimates
Error Characteristics of Satellite-only Global Gravity Models after Solid Earth Data Reductions
Full text linkThe spatial homogeneity provided by satellite-only gravity models has been successfully exploited to probe the lithosphere density structure and its related quantities (e.g. composition and temperature). Compared with other observables, these models provide an unparalleled spatial coverage, which comes with the price of lower resolution.
Geophysical applications of gravity products start with data reduction, stripping the gravity effect of "known masses" to isolate an anomalous field. Uncertainties in the reductions, which rely on a-priori data, accumulate in the anomaly and are non-trivially propagated to the inversion results. The static spatial distribution of mass in the lithosphere is responsible for a large part of the observed signal, well above the sensitivity of the products. At the same time, the uncertainties in reductions can reach the same magnitude as the enquired source.
We aimed at providing an error estimate for solid Earth applications, in the form of error curves "after reduction", in the spectral domain, and maps of the spatial distribution of uncertainty. We computed a set of reductions for crustal and mantle inhomogeneities. Uncertainties in the input quantities were propagated trough Monte Carlo methods. Depth uncertainties, if not provided with the input data, were assigned according to method-specific assumptions. Estimates of density and its variance come from distributions fitted to literature data, from petrophysics, and from worst-case assumptions where no data is available. We report the results of these tests globally. Simulated improvements in the input data show how slight improvements in quality would pay off in terms of error reduction
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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