1,720,980 research outputs found
On the use of decadal predictions for agricultural climate services: bridging the gap between service providers and users
Full text linkTesi en modalitat de compendi de publicacions(English) Unfavorable and extreme climate events such as drought and heat stress heavily impacts the agriculture sector and food security globally, and the impact of these climate hazards is expected to increase over the upcoming years (or decades) due to anthropogenic climate change. Recently developed decadal climate forecast systems aim to provide a future outlook of the Earth’s climate system for a period ranging from 1 to 10 years. Skilful prediction of extreme climate events using this climate information shows potential for supporting risk reduction and adaptation strategies in the agriculture sector, fostering food security and better planning crop insurance schemes. In this context, the ability of state-of-the-art probabilistic decadal climate forecast systems at predicting climate extremes on a multi-annual timescale is explored in this thesis, which is an important step in determining whether such climate information can provide useful, and ultimately actionable, information to stakeholders in the agricultural sector, a sector that has been identified as one of the most vulnerable to climate-related risks.
As a first step, the deterministic forecast skill of decadal climate forecast systems at predicting multi-year drought conditions during European summer over the recent past was assessed in this thesis. Evaluating the quality of such predictions is considered a fundamental step because it assesses whether the prediction systems can be trusted to reliably forecast impactful events. The results revealed that the decadal forecast systems are able to skillfully predict the summer drought conditions over most of Europe using two user-relevant drought indices: Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Following these encouraging results, the probabilistic skill in predicting multi-year drought and heat stress conditions over global wheat harvest areas was then assessed. Wheat is the most harvested cereal crop in the world, contributing to the local food security of many countries. The results demonstrated the decadal predictions are generally more skillful than forecasts built on the observed climatology in predicting the tercile categories of the multi-year averages of drought and heat stress indices over several wheat-growing regions. In addition, the initialization of the decadal forecasting system enhances skill and reliability over the wheat producing regions for both indices. This implies that there exist opportunities to support wheat stakeholders in their decision-making processes as well as policy development, implementation and evaluation on a multi-annual timescale.
Building on these results, an illustration of the potential of decadal predictions in the development of climate services was made by establishing interactions and collaborations with stakeholders from the agriculture sector. The main goal of this exercise was to understand how the decadal climate information should be conveyed to stakeholders in order to enhance its usability for decision making. In this context, a climate service product presenting the forecast of dry conditions for the coming five years over global wheat harvesting regions was designed. The product was presented to stakeholders that had interest in various crops (wheat, grape, and cotton among others) and in food security. During the interaction, the stakeholders expressed interest in uptaking decadal climate information and it was found that the climate information at decadal timescale can be of great value for a broad range of users. Particularly, it can support planning decisions that require several years to be implemented, such as choosing crop varieties, deciding on crop plantation sites, and devising strategic policies.(Español) Los fenómenos climáticos desfavorables y extremos, como la sequía y el estrés térmico, tienen un fuerte impacto en el sector agrario y la seguridad alimentaria a nivel mundial. Se espera que el impacto de estos eventos aumente en los próximos años (o décadas) a causa del cambio climático antropogénico. Las predicciones decadales tienen como objetivo proporcionar información climática de los próximos 10 años. Dichas predicciones representan un potencial de mejora en la gestión de los riesgos asociados al clima y el desarrollo de estratégias de adaptación al cambio climático. En este contexto, esta tesis estudia la capacidad de dichas predicciones en reproducir fenómenos climáticos extremos a una escala temporal plurianual.
En primer lugar, se han utilizado métricas de verificación deterministas para evaluar la calidad de las predicciones climáticas decadales prediciendo condiciones de sequía durante la estación de verano, sobre la región europea, y en el pasado reciente. Dicha evaluación se considera un paso fundamental en el proceso de verificación, ya que permite determinar si se puede confiar en los sistemas de predicción al pronosticar de forma fiable eventos de gran impacto. Los resultados obtenidos revelan que las predicciones decadales son capaces de predecir las condiciones de sequía estival en la mayor parte de Europa, utilizando dos índices de sequía relevantes para el usuario: el Índice de Precipitación Estandarizado (SPI, en sus siglas en inglés) y el Índice Estandarizado de Precipitación y Evapotranspiración (SPEI, en sus siglas en inglés). En segundo lugar, se han utilizado métricas de verificación probabilística para estimar la calidad de la predicción de sequía y estrés térmico en aquellas zonas donde se cultiva trigo de todo el mundo. Se ha elegido este cultivo, ya que es el cereal más cosechado en el mundo y es clave para la seguridad alimentaria local de muchos países. Los resultados obtenidos demuestran que las predicciones decadales presentan un valor añadido frente a las elaboradas a partir de la climatología observada, concretamente, en la predicción por terciles de las medias plurianuales, y paralos índices de sequía y de estrés térmico en varias regiones productoras de trigo. Además, la inicialización del sistema de predicción decadal tiene un efecto de mejora en la calidad de las predicciones de ambos índices sobre las regiones productoras de dicho cereal. Esto implica nuevas oportunidades para la mejora en los procesos de toma de decisiones del sector, así como en el desarrollo, la aplicación y la evaluación de políticas agrarias en una escala temporal plurianual.
A partir de estos resultados, se ha explorado el potencial de las predicciones decadales en el desarrollo de servicios climáticos, estableciendo interacciones y colaboraciones con usuarios del sector agrario. El objetivo principal de este ejercicio fué entender cuál es la mejor forma de transmitir la información climática decadal a los usuarios con el objetivo de potenciar su usabilidad en el contexto de la toma de decisiones. Con tal fin, se diseñó un producto de servicio climático que muestra la predicción global de las condiciones de sequía para los próximos cinco años en las regiones productoras de trigo. Este producto fue presentado a usuarios de diferentes sectores agrícolas (trigo, uva y algodón, entre otros) y expertos en seguridad alimentaria. Durante las sesiones de interacción, los usuarios mostraron interés en recibir información climática decadal para su uso en la toma de decisiones, comprobando que ésta puede ser de gran valor para una amplia gama de usuarios. En particular, las predicciones decadales pueden servir de apoyo a la planificación de actividades que requieren varios años en ser implementadas,como la elección de nuevas variedades y áreas de cultivos, entre otras.DOCTORAT EN ENGINYERIA AMBIENTAL (Pla 2012
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
How reliable are decadal climate predictions of near-surface air temperature?
Full text linkDecadal climate predictions are being increasingly used by stakeholders interested in the evolution of climate over the coming decade. However, investigating the added value of those initialized decadal predictions over other sources of information typically used by stakeholders generally relies on forecast accuracy, while probabilistic aspects, although crucial to users, are often overlooked. In this study, the quality of the near-surface air temperature from initialized predictions has been assessed in terms of reliability, an essential characteristic of climate simulation ensembles, and compared to the reliability of noninitialized simulations performed with the same model ensembles. Here, reliability is defined as the capability to obtain a true estimate of the forecast uncertainty from the ensemble spread. We show the limited added value of initialization in terms of reliability, the initialized predictions being significantly more reliable than their noninitialized counterparts only for specific regions and the first forecast year. By analyzing reliability for different forecast system ensembles, we further highlight the fact that the combination of models seems to play a more important role than the ensemble size of each individual forecast system. This is due to sampling different model errors related to model physics, numerics, and initialization approaches involved in the multimodel, allowing for a certain level of error compensation. Finally, this study demonstrates that all forecast system ensembles are affected by systematic biases and dispersion errors that affect the reliability. This set of errors makes bias correction and calibration necessary to obtain reliable estimates of forecast probabilities that can be useful to stakeholders.The EUCP project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement 776613. The research leading to these results has also received funding from the Spanish Ministerio de Ciencia, Innovación y Universidades as part of the CLINSA project with funding reference CGL2017-85791-R. MGD is also supported by the Spanish Ministry of Science, Innovation and Universities Grant RYC-2017-22964. BSM acknowledges financial support from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement 713673 and from a fellowship of “la Caixa” Foundation (ID 100010434). The fellowship code is LCF/BQ/IN17/11620038. SW has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433. We acknowledge the use of the s2dverification (Manubens et al. 2018), startR (BSC/CNS and Manubens 2020), SpecsVerification (Siegert 2017), CSTools (Perez-Zanon et al. 2019), ClimProjDiags (BSC/CNS et al. 2020), and boot (Davison and Hinkley 1997; Canty and Ripley 2020) R (R Core Team 2013) software packages. We also thank Nicolau Manubens, An-Chi Ho, Pablo Ortega, Rashed Mahmood, Yohan Ruprich-Robert, and Roberto Bilbao from the BSC for their technical and scientific support. We further express our gratitude to Charles Pelletier from ELI for his careful reading of the manuscript. Finally, we would like to thank Antje Weisheimer (University of Oxford) and two anonymous reviewers for constructive comments that helped us greatly improve this article.Peer ReviewedPostprint (published version
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