1,720,960 research outputs found
Evaluation of a satellite multispectral VIS/IR daytime statistical rain-rate classifier and comparison with passive microwave rainfall estimates
No full textA daytime surface rain-rate classifier, based on Artificial Neural Networks (ANN), is proposed for the Spinning Enhanced Visible and Infra Red Imager (SEVIRI), on board the Meteosat-8 geostationary satellite. It is developed over the British Isles and surrounding waters, where the Met Office radar network provided the “ground precipitation truth” for training and validation. The algorithm classifies rain-rate in five classes at 15 minutes and 5 km of time and spatial resolution, and is applied on daytime hours in a summer and winter database. A further ANN application is restricted to hours between 12 and 14 UTC for which the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) on board the AQUA polar-orbiting satellite scans the U.K. area: ANN-classifier algorithms for the SEVIRI and AMSR-E data have been developed and the results compared. A reliable validation procedure is adopted in order to quantify the performance in view of the operational application of the daytime classifier and to investigate the relative skills of passive microwave and visible-infrared radiances in sensing precipitation if processed with equivalent algorithms. The key statistical parameters used are the Equitable Threat Score (ETS) and the BIAS for rain-no rain classes, and the Heidke Skill Score (HSS) for rain-rate classes. The SEVIRI daytime classifier shows, for mean seasonal conditions, the best performance in summer, with ETS=47% and HSS=22%, while in winter ETS=36% and HSS=17% were found. The comparison between AMSR-E and SEVIRI noon classifiers reveals a similar overall skill: in detecting rain areas SEVIRI is slightly better than AMSR-E, while the opposite is true for rain-rate classification
Probability of precipitation using SEVIRI-like data and artificial neural networks.
No full textMETEOSAT-8 provides new means to address the challenge of using geostationary satellite data to estimate precipitation: the SEVIRI sensor has higher spatial and temporal resolution and a higher number of spectral channels than the old METEOSAT sensor. This work aims to assess quantitatively the potential
improvement due to the new channels. Appropriate visible (VIS) and infrared (IR) channels on the MODIS instrument have been used to simulate SEVIRI channels. Artificial Neural Network (ANN) techniques have been adopted to establish an indirect procedure to estimate Probability of Precipitation (PoP). The PoP ANN estimator is used to classify cloudy pixels into rain and no rain classes (with a threshold value of 1/32 mm h-1) and its performance has been assessed in terms of the Equitable Threat Score (ETS). The analysis involves winter season and morning/early night hours. The results obtained were compared with the most nearly corresponding METEOSAT-based scheme available in the Nimrod nowcasting system of the Met Office (UK). The evident impact of new channels on the performance shows that a new SEVIRIbased scheme could provide better estimation of precipitation. An optimum set of channels and features (Local Variability and Textural) useful for an operational operative PoP estimator has been selected and proposed in both day and night-time cases. In daytime, the 1.6μm channel combined with a visible
channel showed remarkable skill at distinguishing raining from non-raining pixels
Estimation of water vapor vertical distribution over the sea from Meteosat and SSM/I observations
No full textObject of this work is to explore the capabilities of multi-sensor water vapor (WV) observations for identification and classification of fronts and air masses in northern Atlantic and Mediterranean areas. We used data from the 6.3 micromete channel of the European geostationary satellite Meteosat: we retrieved the distribution of WV mean content in the layer between 600 and 300 hPa for cloudless areas. Multifrequency data from Special Sensor Microwave/Imager (SSM/I) are used to estimate: 1) the distribution of WV mean content in lowermost 500 m of the troposphere, and 2) the distribution of total WV content in the troposphere. The retrieval is performed over marine areas and outside heavy precipitation areas. We combined the three WV retrievals and we estimated the vertical WV profile at three tropospheric levels: the lowest one below 500 m (1000-960 hPa, from the SSM/I), the layer between 600 and 300 hPa (from the Meteosat) and the layer between 500 m and 600 hPa (as difference between these two fields and the total columnar content as from SSM/I). The performances of the three techniques are evaluated by comparison with European Center for Medium Range Weather Forecast (ECMWF) analysis: good agreement is found for both SSM/I retrievals (percentage of error between 15 and 25%) while for the 6.3 micrometer retrieval higher values are reported (about 45%). The combined approach is used to estimate vertical profiles of WV content with an accuracy suitable for semi-quantitative analysis of the moisture structure. Vertical cross sections of WV fields are obtained in proximity of frontal surfaces and discussed for one case study
La stima della precipitazione
No full textIn questo lavoro si presenta una analisi delle problematiche relative alla validazione delle stime di precipitazione da sensore remoto, mostrando alcune tecniche recenti, discutendone vantaggi e svantaggi. Approcci più recenti alla stima della precipitazione verranno mostrati, utilizzando strumenti innovativi, che consentono un maggior dettaglio fisico nell’analisi della precipitazione: si discuteranno brevemente l’uso dei disdrometri (per la misura della distribuzione dimensionale degli elementi di precipitazione), dei radar polarimetrici (per la classificazione delle idrometeore) e dei sensori multispettrali su satellite (per la stima di precipitazione)
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
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