1,720,959 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Representation of deep convection at gray-zone resolutions - Implementing and testing the HYbrid MAss flux Convection Scheme (HYMACS) in the ICON model
Get PDFDespite the increasing computing resources, the grids of contemporary atmospheric models are often still too coarse to explicitly represent convective processes. Since these processes are known to be an important driver of atmospheric dynamics, convection parametrization schemes must be deployed which have been developed over several decades. However, recent applications of regional climate and operational numerical weather prediction models have reached spatial resolutions where the overturning circulation of deep convection becomes partly resolved onto grid-scale. The so-called gray-zone of deep convection imposes challenges to the conventional parametrization approach which have attained increasing scientific attention in the last two decades.
The present work implements and tests extensively the HYbrid MAss flux Convection Scheme (HYMACS) in the ICOsahedral Non-hydrostatic (ICON) model. In contrast to other convection parametrization schemes, HYMACS passes the compensational subsidence to the grid-scale dynamics, thereby allowing for a net mass transport. While the scheme has been developed since the pioneering work of Kuell et al. (2007), it has only been tested in a couple of case studies with the COSMO (COnsortium for Small-scale Modeling) model. Although the hybrid scheme improved the representation of convection at gray-zone resolutions in these studies, a statistically well founded assessment of the merits of HYMACS is still outstanding. Besides, its implementation into ICON is appealing since the new hosting model is designed to operate over a broad range of spatial resolutions.
This thesis starts with a in-depth introduction of the theoretical framework of HYMACS and documents recent developments of the scheme. Apart from some required adaptions of the physics-dynamics coupling with ICON, problems in conjunction with the numerical filter in the model’s dynamical core are identified. The operational anisotropic divergence damping operator distorts the dynamical flow response to a parametrized net mass transport and therefore has to be revised. Different numerical filter operators are investigated in dynamical core tests on the sphere and in mass lifting experiments. Based on these tests, a revised filter configuration is proposed which is compatible with HYMACS and which efficiently removes computational noise.
With the revised numerical filter configuration, a series of re-forecasts over Central Europe spanning a summery three-monthly period is conducted to analyze the performance of HYMACS in ICON. It is demonstrated that the hybrid scheme captures the convectively driven diurnal cycle of precipitation better than the operational convection parametrization scheme. The modelled marginal distribution of precipitation amounts and the spatial patterns of precipitation also get improved. Albeit the statistical analysis confirms the results of former case studies, issues to the net mass transport of shallow convection are identified as well. Nonetheless, the merits are encouraging and this work is considered to serve as the basis for further developments focusing on the scale adaptivity of HYMACS in the modeling framework of ICON.Repräsentation von hochreichender Konvektion in der konvektiven Grauzone - Implementierung und Untersuchung des hybriden Massenfluss Konvektionsschemas HYMACY im ICON Modell
Trotz steigender Rechenleistung sind die Gitter heutiger Atmosphärenmodelle oft noch zu grob, um konvektive Prozesse explizit zu repräsentieren. Da diese einen wichtigen Antrieb der atmosphärischen Dynamik darstellen, werden Konvektionsparametrisierungen eingesetzt, die bereits seit mehreren Jahrzehnten entwickelt werden. Aktuelle Anwendungen regionaler Klima- und operationeller Wettervorhersage-Modelle erreichen jedoch eine räumliche Auflösung, die die Umwälzzirkulation hochreichender Konvektion teilweise auf der Gitterskala abbilden können. Diese so genannte Grauzone hochreichender Konvektion stellt den konventionellen Parametrisierungsansatz vor Herausforderungen, die in den letzten beiden Jahrzehnten zunehmende wissenschaftliche Beachtung erlangt haben.
In der vorliegenden Arbeit wird das hybride Massenfluss Konvektionsschema HYMACS in das ICOsahedral Non-hydrostatic (ICON) Modell implementiert und ausgiebig getestet. Anders als gängige Konvektionsparametrisierung-Schemata überlässt HYMACS das kompensatorische Absinken der gitterskaligen Dynamik und ermöglicht auf diese Weise einen Nettomassentransport. Obwohl das Schema bereits seit der wegweisenden Arbeit von Kuell et al. (2007) entwickelt wird, wurde es bisher nur in einigen Fallstudien mit dem COSMO (COnsortium for Small-scale Modeling) Modell getestet. Das hybride Schema verbesserte in diesen Studien zwar die Darstellung hochreichender Konvektion in der Grauzone, eine statistisch fundierte Auswertung der Vorzüge von HYMACS wurde jedoch noch nicht durchgeführt. Zudem erscheint eine Implementierung in ICON attraktiv, da dieses Modell für ein breites Spektrum räumlicher Auflösungen entwickelt wurde.
Diese Arbeit beginnt mit einer ausführlichen Einführung in die Grundlagen von HYMACS und dokumentiert die jüngsten Weiterentwicklungen des Schemas. Zusätzlich zu den notwendigen Anpassungen der Physik-Dynamik-Kopplung mit ICON aufgrund des alternativen Parametrisierungsansatzes, ergeben sich Probleme in Verbindung mit dem numerischen Filter des Modells. Die operative anisotrope Divergenzdämpfung verzerrt die dynamische Antwort auf einen parametrisierten Nettomassentransport, so dass diese angepasst werden muss. Verschiedene numerische Filteroperatoren werden sowohl in Tests des dynamischen Kerns auf der Kugel als auch in in Massenauftriebsexperimenten untersucht. Auf Grundlage dieser Tests wird eine revidierte Filterkonfiguration vorgeschlagen, die mit HYMACS kompatibel ist und die numerisches Rauschen effizient entfernt.
Mit der überarbeiteten numerischen Filterkonfiguration wird eine Testreihe von Vorhersagen über drei Sommermonate im mitteleuropäischen Raum durchgeführt, um die Leistung von HYMACS in ICON zu analysieren. Es wird gezeigt, dass das hybride Schema den konvektiv bestimmten Tagesgang des Niederschlags besser erfasst, als das operationelle Schema zur Parametrisierung von Konvektion. Die modellierte Randverteilung der Niederschlagsmengen und die räumlichen Muster des Niederschlags werden ebenfalls besser repräsentiert. Während die statistische Analyse damit die Ergebnisse früherer Fallstudien bestätigt, werden auch Probleme aufgrund des Nettomassentransports der flachen Konvektion identifiziert. Gleichwohl sind die Ergebnisse vielversprechend, so dass diese Arbeit als Ausgangspunkt für skalenadaptive Weiterentwicklungen von HYMACS in ICON dient
Time Filter Assisted Deep Learning to Predict Air Pollution
Get PDFExposure to ground-level ozone harms human health as well as the entire ecosystem, so accurate prediction of ozone exposure is of particular importance. Machine learning (ML), and deep learning (DL) in particular, has emerged as a powerful method with a vast variety of applications, including meteorology and Earth system sciences, making it a strong alternative to conventional methods such as chemical transport models (CTMs) or regression based solutions to forecast ground-level ozone. However, to date, classical as well as ML approaches have experienced challenges in reliably forecasting ozone pollution at the local scale. These shortcomings can be attributed to the challenges posed by inherent uncertainties about near-future weather conditions and the superposition of patterns on different time scales. In this thesis, a time series filtering approach to split up long-term and short-term variations and DL are applied to allow for accurate predictions of air pollution attributable to ground-level ozone. This is complemented by integrating large amounts of data from air quality monitoring stations distributed across Central Europe, climatological statistics on air pollutants and meteorological data from numerical weather models. The DL approach is framed by a well-defined workflow for training and validation called MLAir, which ensures the reproducibility of the findings. Results substantiate that the combination of sophisticated DL architectures and time series filtering enables accurate ozone prediction. The DL approach thereby achieves a nearly bias-free prediction and has a good performance with regard to the seasonal variability of ozone. This leads to a great improvement compared to simpler reference forecasts based on climatology and persistence, as well as to the Copernicus Atmosphere Monitoring Service (CAMS) regional multi-model ensemble forecast, which combines nine individual state-of-the-art CTMs deployed operationally by public weather services and research institutions. Averaged over a forecast horizon of four days, the prediction for the daily maximum 8-hour running average (dma8) of ozone by the CAMS regional ensemble has a root mean squared error (RMSE) of 7.6 ppb, whereas the newly developed method here achieves an RMSE of 5.1 ppb. The approach presented in this thesis thus marks an important advance in DL-based air pollution prediction, benefiting the general public through more reliable forecasts. Furthermore, this study opens up the prospect of further research opportunities towards the prediction of a range of other air pollutants or related applications in meteorology
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
