Improved seasonal prediction skill of rainfall for the Priera season in Central America

This study explores the predictive skill of seasonal rainfall characteristics for the first rainy (and planting) season, May–June, in Central America. Statistical predictive models were built using a Model Output Statistics (MOS) technique based on canonical correlation analysis, in which variables that forecast with the Climate Forecast System version 2 (CFSv2) were used as candidate predictors for the observed total precipitation, frequency of rainy days and mean number of extremely dry and wet events in the season. CFSv2 initializations from February to April were explored. The CFSv2 variables used in the study consist of rainfall, as in a typical MOS technique, and a combination of low-level winds and convective available potential energy (CAPE), a blend that has been previously shown to be a good predictor for convective activity. The highest predictive skill was found for the seasonal frequency of rainy days, followed by the mean frequency of dry events. In terms of candidate predictors, the zonal transport of CAPE (uCAPE) at 925 hPa offers higher skill across Central America than rainfall, which is attributed in part to the high model uncertainties associated with precipitation in the region. As expected, dynamical model predictors initialized in February provide lower skill than those initialized later. Nonetheless, the skill is comparable for March and April initializations. These results suggest that the National Meteorological and Hydrological Services in Central America, and the Central American Regional Climate Outlook Forum, can produce earlier more skilful forecasts for May–June rainfall characteristics than previously stated

Could the Recent Zika Epidemic Have Been Predicted?

Given knowledge at the time, the recent 2015–2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME), finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower—but still of potential use to decision-makers—for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics

Characterizing Venezuelan Elections through Twitter. Case: # 26s

This paper is aimed to discover the characteristic routines established by Twitter users along September 26th 2010, an Asamblea Nacional election day in Venezuela. It is based on previous studies by Boyd (2005), Masten and Plowman (2003) and FAO (2011) on digital ethnography and passive observation as the appropriate methods and techniques for modeling and characterizing the behavior of a digital community. The data acquisition was achieved using The Archivist, while the software CAVAnaTuit was developed by the authors for the corresponding analysis. Among the results, it is clear that Venezuelans have developed a series of practices, behaviors and games that they execute systematically along the Election Day; the users behave as digital journalists for covering the vote’s instauration, execution and counting. The whole process being started at 9am and finished on September 27th, the analysis revealed that the maximum amounts of tweets were written at 6 pm, while the minimum was detected to occur at 4 pm. Even when the data acquisition was designed to include the hashtag #26S, among the other most frequent hashtags were: #Venezuela, #Cuba, #ElNacional, cosasquepasaranantesdelboletín y #fuerafocas. During the early morning of September 27th were positioned into the Trending Topics 8 hashtags related to Venezuela and the elections results

Caracterizando las elecciones venezolanas a través de Twitter. Caso: #26s

Esta investigación tuvo como objetivo describir las rutinas que establecen los usuarios de la plataforma Twitter durante el día 26 de Septiembre de 2010, día de las elecciones de diputados a la Asamblea Nacional en Venezuela. Se basa en los aportes de boyd (2005), Masten y Plowman (2003) y la FAO (2011) relacionados a con la etnografía digital y observación pasiva como métodos y técnicas de estudio más apropiados para los trabajos que buscan modelar y caracterizar a los participantes de una comunidad digital. La recolección de datos se realizó con la herramienta The Archivist y para el procesamiento de los mismos se desarrolló el software CAVAnaTuit versión v0.9. Entre los primeros resultados se puede destacar que los venezolanos han desarrollado una serie de rutinas, prácticas y juegos que ejecutan durante el día del evento electoral de forma sistemática; asimismo se detectó que los usuarios se convierten en reporteros digitales durante el día cubriendo desde el establecimiento de los centros electorales hasta el ejercicio y conteo de los votos. La hora que registró la mayor cantidad de tuits fueron las 6 de la tarde mientras que el valor mínimo se tuvo a las 4pm (hay que tomar como punto de referencia que estas son las horas en las cuales comienza el cierre de mesas). La descarga de datos se estableció con la etiqueta #26S pero las más comunes, según su frecuencia de uso, fueron: #Venezuela, #Cuba, #ElNacional, #cosasquepasaranantesdelboletín y #fuerafocas. En la madrugada del 27S se posicionaron en las Tendencias del Momento Mundial de Twitter 8 de 10 etiquetas.  This paper is aimed to discover the characteristic routines established by Twitter users along September 26th 2010, an Asamblea Nacional election day in Venezuela. It is based on previous studies by Boyd (2005), Masten and Plowman (2003) and FAO (2011) on digital ethnography and passive observation as the appropriate methods and techniques for modeling and characterizing the behavior of a digital community. The data acquisition was achieved using The Archivist, while the software CAVAnaTuit was developed by the authors for the corresponding analysis. Among the results, it is clear that Venezuelans have developed a series of practices, behaviors and games that they execute systematically along the Election Day; the users behave as digital journalists for covering the vote’s instauration, execution and counting. The whole process being started at 9am and finished on September 27th, the analysis revealed that the maximum amounts of tweets were written at 6 pm, while the minimum was detected to occur at 4 pm. Even when the data acquisition was designed to include the hashtag #26S, among the other most frequent hashtags were: #Venezuela, #Cuba, #ElNacional, cosasquepasaranantesdelboletín y #fuerafocas. During the early morning of September 27th were positioned into the Trending Topics 8 hashtags related to Venezuela and the elections results

Caracterizando las elecciones venezolanas a través de Twitter. Caso: #26s

Esta investigación tuvo como objetivo describir las rutinas que establecen los usuarios de la plataforma Twitter durante el día 26 de Septiembre de 2010, día de las elecciones de diputados a la Asamblea Nacional en Venezuela. Se basa en los aportes de boyd (2005), Masten y Plowman (2003) y la FAO (2011) relacionados a con la etnografía digital y observación pasiva como métodos y técnicas de estudio más apropiados para los trabajos que buscan modelar y caracterizar a los participantes de una comunidad digital. La recolección de datos se realizó con la herramienta The Archivist y para el procesamiento de los mismos se desarrolló el software CAVAnaTuit versión v0.9. Entre los primeros resultados se puede destacar que los venezolanos han desarrollado una serie de rutinas, prácticas y juegos que ejecutan durante el día del evento electoral de forma sistemática; asimismo se detectó que los usuarios se convierten en reporteros digitales durante el día cubriendo desde el establecimiento de los centros electorales hasta el ejercicio y conteo de los votos. La hora que registró la mayor cantidad de tuits fueron las 6 de la tarde mientras que el valor mínimo se tuvo a las 4pm (hay que tomar como punto de referencia que estas son las horas en las cuales comienza el cierre de mesas). La descarga de datos se estableció con la etiqueta #26S pero las más comunes, según su frecuencia de uso, fueron: #Venezuela, #Cuba, #ElNacional, #cosasquepasaranantesdelboletín y #fuerafocas. En la madrugada del 27S se posicionaron en las Tendencias del Momento Mundial de Twitter 8 de 10 etiquetas.  This paper is aimed to discover the characteristic routines established by Twitter users along September 26th 2010, an Asamblea Nacional election day in Venezuela. It is based on previous studies by Boyd (2005), Masten and Plowman (2003) and FAO (2011) on digital ethnography and passive observation as the appropriate methods and techniques for modeling and characterizing the behavior of a digital community. The data acquisition was achieved using The Archivist, while the software CAVAnaTuit was developed by the authors for the corresponding analysis. Among the results, it is clear that Venezuelans have developed a series of practices, behaviors and games that they execute systematically along the Election Day; the users behave as digital journalists for covering the vote’s instauration, execution and counting. The whole process being started at 9am and finished on September 27th, the analysis revealed that the maximum amounts of tweets were written at 6 pm, while the minimum was detected to occur at 4 pm. Even when the data acquisition was designed to include the hashtag #26S, among the other most frequent hashtags were: #Venezuela, #Cuba, #ElNacional, cosasquepasaranantesdelboletín y #fuerafocas. During the early morning of September 27th were positioned into the Trending Topics 8 hashtags related to Venezuela and the elections results

Caracterizando las elecciones venezolanas a través de Twitter: caso: #26S

This paper is aimed to discover the characteristic routines established by Twitter users along September 26th 2010, an Asamblea Nacional election day in Venezuela. It is based on previous studies by Boyd (2005), Masten and Plowman (2003) and FAO (2011) on digital ethnography and passive observation as the appropriate methods and techniques for modeling and characterizing the behavior of a digital community. The data acquisition was achieved using The Archivist, while the software CAVAnaTuit was developed by the authors for the corresponding analysis. Among the results, it is clear that Venezuelans have developed a series of practices, behaviors and games that they execute systematically along the Election Day; the users behave as digital journalists for covering the vote�s instauration, execution and counting. The whole process being started at 9am and finished on September 27th, the analysis revealed that the maximum amounts of tweets were written at 6 pm, while the minimum was detected to occur at 4 pm. Even when the data acquisition was designed to include the hashtag #26S, among the other most frequent hashtags were: #Venezuela, #Cuba, #ElNacional, cosasquepasaranantesdelboletín y #fuerafocas. During the early morning of September 27th were positioned into the Trending Topics 8 hashtags related to Venezuela and the elections results.Etereos Esta investigación tuvo como objetivo describir las rutinas que establecen los usuarios de la plataforma Twitter durante el día 26 de Septiembre de 2010, día de las elecciones de diputados a la Asamblea Nacional en Venezuela. Se basa en los aportes de boyd (2005), Masten y Plowman (2003) y la FAO (2011) relacionados a con la etnografía digital y observación pasiva como métodos y técnicas de estudio más apropiados para los trabajos que buscan modelar y caracterizar a los participantes de una comunidad digital. La recolección de datos se realizó con la herramienta The Archivist y para el procesamiento de los mismos se desarrolló el software CAVAnaTuit versión v0.9. Entre los primeros resultados se puede destacar que los venezolanos han desarrollado una serie de rutinas, prácticas y juegos que ejecutan durante el día del evento electoral de forma sistemática; asimismo se detectó que los usuarios se convierten en reporteros digitales durante el día cubriendo desde el establecimiento de los centros electorales hasta el ejercicio y conteo de los votos. La hora que registró la mayor cantidad de tuits fueron las 6 de la tarde mientras que el valor mínimo se tuvo a las 4pm (hay que tomar como punto de referencia que estas son las horas en las cuales comienza el cierre de mesas). La descarga de datos se estableció con la etiqueta #26S pero las más comunes, según su frecuencia de uso, fueron: #Venezuela, #Cuba, #ElNacional, #cosasquepasaranantesdelboletín y #fuerafocas. En la madrugada del 27S se posicionaron en las Tendencias del Momento Mundial de Twitter 8 de 10 etiquetas

Caracterizando las elecciones venezolanas a través de Twitter. Caso: #26s

This paper is aimed to discover the characteristic routines established by Twitter users along September 26th 2010, an Asamblea Nacional election day in Venezuela. It is based on previous studies by Boyd (2005), Masten and Plowman (2003) and FAO (2011) on digital ethnography and passive observation as the appropriate methods and techniques for modeling and characterizing the behavior of a digital community. The data acquisition was achieved using The Archivist, while the software CAVAnaTuit was developed by the authors for the corresponding analysis. Among the results, it is clear that Venezuelans have developed a series of practices, behaviors and games that they execute systematically along the Election Day; the users behave as digital journalists for covering the vote’s instauration, execution and counting. The whole process being started at 9am and finished on September 27th, the analysis revealed that the maximum amounts of tweets were written at 6 pm, while the minimum was detected to occur at 4 pm. Even when the data acquisition was designed to include the hashtag #26S, among the other most frequent hashtags were: #Venezuela, #Cuba, #ElNacional, cosasquepasaranantesdelboletín y #fuerafocas. During the early morning of September 27th were positioned into the Trending Topics 8 hashtags related to Venezuela and the elections results.Esta investigación tuvo como objetivo describir las rutinas que establecen los usuarios de la plataforma Twitter durante el día 26 de Septiembre de 2010, día de las elecciones de diputados a la Asamblea Nacional en Venezuela. Se basa en los aportes de boyd (2005), Masten y Plowman (2003) y la FAO (2011) relacionados a con la etnografía digital y observación pasiva como métodos y técnicas de estudio más apropiados para los trabajos que buscan modelar y caracterizar a los participantes de una comunidad digital. La recolección de datos se realizó con la herramienta The Archivist y para el procesamiento de los mismos se desarrolló el software CAVAnaTuit versión v0.9. Entre los primeros resultados se puede destacar que los venezolanos han desarrollado una serie de rutinas, prácticas y juegos que ejecutan durante el día del evento electoral de forma sistemática; asimismo se detectó que los usuarios se convierten en reporteros digitales durante el día cubriendo desde el establecimiento de los centros electorales hasta el ejercicio y conteo de los votos. La hora que registró la mayor cantidad de tuits fueron las 6 de la tarde mientras que el valor mínimo se tuvo a las 4pm (hay que tomar como punto de referencia que estas son las horas en las cuales comienza el cierre de mesas). La descarga de datos se estableció con la etiqueta #26S pero las más comunes, según su frecuencia de uso, fueron: #Venezuela, #Cuba, #ElNacional, #cosasquepasaranantesdelboletín y #fuerafocas. En la madrugada del 27S se posicionaron en las Tendencias del Momento Mundial de Twitter 8 de 10 etiquetas.

Variabilidad estacional a interanual de las temperaturas de la superficie del mar en los mares interamericanos: sesgos dependientes del patrón en el sistema regional de modelos oceánicos

The Inter-Americas Seas (IAS), involving the Gulf of Mexico, the Caribbean and a section of the eastern tropical Pacific Ocean bordering Central America, Colombia and Ecuador, exhibits very active ocean-land-atmosphere interactions that impact socio-economic activities within and beyond the region, and that are still not well understood or represented in state-of-the-art models. On seasonal-to-interannual timescales, the main source of variability of this geographical area is related to interactions between the Pacific and the Atlantic oceans, involving to anomalous sea-surface temperature (SST) patterns like El Niño-Southern Oscillation (ENSO), and regional features in the Caribbean linked to the bi-modal seasonality of the Caribbean Low-Level Jet. This study investigates seasonal-to-interannual IAS surface-temperature anomalies in observations, and their representation in am eddy-permitting, 1/9o-resolution simulation using the Regional Ocean Modeling System (ROMS), interannually-forced by the Climate Forecast System Reanalysis. Here, rather than analyzing model biases locally (i.e., gridbox-by-gridbox), a non-local SST pattern-based diagnostic was conducted via a principal component analysis. The approach allowed to identify magnitude, variance and spatial systematic errors in SST patterns related to the Western Hemisphere Warm Pool, ENSO, the Inter-American Seas Dipole, and several other variability modes. These biases are mainly related to errors in surface heat fluxes, misrepresentation of air-sea interactions impacting surface latent cooling in the Caribbean, and too strong sub-surface thermal stratification, mostly off the coast of Ecuador and northern Peru.Los mares interamericanos (IAS), que se extienden desde el Golfo de México, el Caribe y la parte trópico-oriental del Océano Pacífico que limita con América Central, Colombia y Ecuador; presentan interacciones muy activas entre el océano, el suelo y la atmósfera, que influyen en las actividades socioeconómicas dentro y fuera de la región. Estas interacciones aún no se comprenden en su totalidad y no se representan adecuadamente, inclusive en modelos de última generación. En escalas de tiempo estacionales e interanuales, la principal fuente de variabilidad en esta zona geográfica, se relaciona con las interacciones entre los océanos Pacífico y Atlántico, incluyendo patrones anómalos de la temperatura en la superficie del mar (SST), como El Niño-Oscilación del Sur (ENSO), y otras características regionales relacionadas con la estacionalidad bimodal del chorro de bajo nivel del Caribe. Este estudio investiga las anomalías estacionales e interanuales de los registros de la temperatura en superficie en los mares interamericanos, y de los resultados simulados con una resolución a una escala de remolino, de 1/9⁰ (0.11°, aproximadamente 10 km), generados por el Sistema Regional de Modelado del Océano (ROMS), y en base del Reanálisis del Sistema de Pronóstico del Clima para el período 1999-2008. En lugar de analizar los sesgos de los resultados del modelo de manera local (cuadrícula por cuadrícula), se realizó un diagnóstico no local, en base de la identificación de patrones de la SST, mediante un análisis de componentes principales. Los resultados indican que incluso con resoluciones a escala de remolino, y a diferencia del consenso de la literatura, persisten varios sesgos. El enfoque permitió cuantificar la magnitud, la varianza y los errores sistemáticos de los patrones espaciales de la SST, relacionados con la piscina cálida del hemisferio occidental, ENSO, el Dipolo de los mares interamericanos y otros componentes de variabilidad. Estos sesgos se relacionan principalmente con errores la cuantificación de los flujos de calor en la superficie, una inadecuada representación de las interacciones entre el mar y la atmósfera, componentes que afectan el enfriamiento latente en superficie en la zona del Caribe y genera una estratificación térmica subterránea excesiva, principalmente frente a la costa de Ecuador y el norte de Perú

Could the Recent Zika Epidemic Have Been Predicted?

Given knowledge at the time, the recent 2015–2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME), finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower—but still of potential use to decision-makers—for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics