1,720,966 research outputs found
Effects of singular-vector-type initial errors on the short-range prediction of Kuroshio extension transition processes
Get PDFThe effects of optimal initial error on the short-range prediction of transition processes between the Kuroshio Extension (KE) bimodalities are analyzed using a reduced-gravity shallow-water model and the singular vector (SV) approach. Emphasis is placed on the spatial structures, growing processes, and effects of the SVs. The results show that the large values of the SVs are mainly located in the first crest region of the KE (around 35°N, 144°E) and in the Kuroshio large meander (KLM) region south of Japan (around 32°N, 139.5°E). The fast growths of the SVs have important impacts on the prediction of transition of the KE bimodality. The initial error with +SV pattern (with positive anomalies in the first crest region of the KE and negative anomalies in the KLM region) tends to strengthen the KE and shift it toward the high-energy state, while the error with -SV pattern is prone to weaken the KE and shift it toward the low-energy state. In addition, the SV-type initial errors grow more quickly in the transition phase of the KE from the high-energy to the low-energy state than in the opposite transition phase. A perturbation energy analysis illustrates that different physical processes are responsible for the error growth in the KE region for different transition phases of the KE; barotropic instability plays a dominant role in the error growth in the low-to-high (LH) energy phase, while the error evolution in the high-to-low (HL) energy phase is mainly caused by advection processes
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
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
Sigma-point Kalman filter data assimilation methods for strongly nonlinear dynamical models.
Get PDFPerformance of an advanced derivative-less, sigma-point Kalman filter (SPKF) data assimilation scheme in a strongly nonlinear dynamical model is investigated. The SPKF data assimilation scheme is compared against standard Kalman filters such as the extended Kalman filter (EKF) and the ensemble Kalman filter (EnKF) schemes. Three particular cases, namely the state estimation, parameter estimation, and joint estimation of states and parameters from a set of discontinuous noisy observations are studied. The problems associated with the use of the tangent linear model (TLM) or the Jacobian when using standard Kalman filters are eliminated when using SPKF data assimilation algorithms. Further, the constraints and issues of SPKF data assimilation in real ocean or atmospheric models are emphasized. A reduced sigma-point subspace approach is proposed and investigated for higher dimensional systems. A low dimensional Lorenz '63 model and a higher dimensional Lorenz '95 model are used as the test-bed for data assimilation experiments. The results of the SPKF data assimilation schemes are compared with those of the standard EKF and EnKF where a highly nonlinear chaotic case is studied. It is shown that the SPKF is capable of estimating the model state and parameters with better accuracy than EKF and EnKF. Numerical experiments show that in all cases, the SPKF can give consistent results with better assimilation skills than EnKF and EKF, and can overcome the drawbacks associated with the use of EKF and EnKF. --P.iii-iv.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b151781
Evaluation of climate predictability for multiple climate models at various time scales.
Get PDFThe predictability of the Pacific North American (PNA) pattern is evaluated on time scales from days to months using state-of-the-art dynamical multiple model ensembles including the Canadian Historical Forecast Project (HFP2) ensemble, the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual prediction (DEMETER) ensemble, and the Ensemble Based Predictions of Climate Changes and their Impacts (ENSEMBLES). Some interesting findings in this study include (i) Multiple-model ensemble (MME) skill was better than skill from most of the individual models (ii) both actual prediction skill and potential predictability increased as the averaging time scale increased from days to months (iii) There is no significant difference in actual skill between coupled and uncoupled models, in contrast with the potential predictability where coupled models performed better than uncoupled models (iv) relative entropy (RE[subscript]A) is an effective measure in characterizing the potential predictability of individual predictions, whereas the mutual information (MI) is a reliable indicator of overall prediction skill (v) Compared with conventional potential predictability measures of the signal-to-noise ratio, the MI-based measures characterized more potential predictability when the ensemble spread varied over initial conditions. It is also confirmed that from monthly to seasonal time scales, the potential predictability of PNA is teleconnected with ENSO. The predictive skill on intra-seasonal time scales in the tropics is linked to Madden-Julian Oscillations (MJO). Using recently developed framework of potential predictability, information-based and ensemble based predictability measures were explored on multiple time scales for MJO predictability. Results show that there is no significant difference in the simulation of MJO in coupled (CanCM3) and uncoupled (GCM3) models. Both models simulated the tropical low frequency variability reasonably well compared with observations with some positive bias iThe original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b197655
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
An analysis of multi-model ensemble for seasonal climate predictions.
Get PDFIn this study, the superiorities of the super ensemble for seasonal climate prediction are investigated based on the 500mb geopotential height (GPH500) hindcasts produced by four Canadian seasonal climate prediction models. The investigations are cared out mainly in two aspects: i) a comprehensive evaluation of predictions for each grid over the global domain by the deterministic, probabilistic and potential prediction skill measures 2) the Empirical Orthogonal Function (EOF) and Maximum Signal-to-Noise (MSN) EOF analyses in the northern hemisphere (NH). It is found that improvements of the super ensemble are mainly due to the increase of ensemble size in the med-high latitudes, and the offsets of model uncertainties in the tropical regions. Measures of temporal correlation coefficient (COOR), the relative root mean square error (RRMSE), reliability (REL) are more affected by the ensemble size whereas resolution (RES) is sensitive to the offsets of model uncertainties. In addition, the super ensemble shows advantages in both EOF and MSN EOF analyses. The contributions of the sea surface temperature anomaly (SSTA) to the seasonal mean climate predictability are closely related to El Nińo-Southern Oscillation (ENSO) forcing. --P. ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b174094
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