13 resultados para climate field reconstruction

em Universidad Politécnica de Madrid


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La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

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Developing countries are experiencing unprecedented levels of economic growth. As a result, they will be responsible for most of the future growth in energy demand and greenhouse gas (GHG) emissions. Curbing GHG emissions in developing countries has become one of the cornerstones of a future international agreement under the United Nations Framework Convention for Climate Change (UNFCCC). However, setting caps for developing countries’ GHG emissions has encountered strong resistance in the current round of negotiations. Continued economic growth that allows poverty eradication is still the main priority for most developing countries, and caps are perceived as a constraint to future growth prospects. The development, transfer and use of low-carbon technologies have more positive connotations, and are seen as the potential path towards low-carbon development. So far, the success of the UNFCCC process in improving the levels of technology transfer (TT) to developing countries has been limited. This thesis analyses the causes for such limited success and seeks to improve on the understanding about what constitutes TT in the field of climate change, establish the factors that enable them in developing countries and determine which policies could be implemented to reinforce these factors. Despite the wide recognition of the importance of technology and knowledge transfer to developing countries in the climate change mitigation policy agenda, this issue has not received sufficient attention in academic research. Current definitions of climate change TT barely take into account the perspective of actors involved in actual climate change TT activities, while respective measurements do not bear in mind the diversity of channels through which these happen and the outputs and effects that they convey. Furthermore, the enabling factors for TT in non-BRIC (Brazil, Russia, India, China) developing countries have been seldom investigated, and policy recommendations to improve the level and quality of TTs to developing countries have not been adapted to the specific needs of highly heterogeneous countries, commonly denominated as “developing countries”. This thesis contributes to enriching the climate change TT debate from the perspective of a smaller emerging economy (Chile) and by undertaking a quantitative analysis of enabling factors for TT in a large sample of developing countries. Two methodological approaches are used to study climate change TT: comparative case study analysis and quantitative analysis. Comparative case studies analyse TT processes in ten cases based in Chile, all of which share the same economic, technological and policy frameworks, thus enabling us to draw conclusions on the enabling factors and obstacles operating in TT processes. The quantitative analysis uses three methodologies – principal component analysis, multiple regression analysis and cluster analysis – to assess the performance of developing countries in a number of enabling factors and the relationship between these factors and indicators of TT, as well as to create groups of developing countries with similar performances. The findings of this thesis are structured to provide responses to four main research questions: What constitutes technology transfer and how does it happen? Is it possible to measure technology transfer, and what are the main challenges in doing so? Which factors enable climate change technology transfer to developing countries? And how do different developing countries perform in these enabling factors, and how can differentiated policy priorities be defined accordingly? vi Resumen Los paises en desarrollo estan experimentando niveles de crecimiento economico sin precedentes. Como consecuencia, se espera que sean responsables de la mayor parte del futuro crecimiento global en demanda energetica y emisiones de Gases de Efecto de Invernadero (GEI). Reducir las emisiones de GEI en los paises en desarrollo es por tanto uno de los pilares de un futuro acuerdo internacional en el marco de la Convencion Marco de las Naciones Unidas para el Cambio Climatico (UNFCCC). La posibilidad de compromisos vinculantes de reduccion de emisiones de GEI ha sido rechazada por los paises en desarrollo, que perciben estos limites como frenos a su desarrollo economico y a su prioridad principal de erradicacion de la pobreza. El desarrollo, transferencia y uso de tecnologias bajas en carbono tiene connotaciones mas positivas y se percibe como la via hacia un crecimiento bajo en carbono. Hasta el momento, la UNFCCC ha tenido un exito limitado en la promocion de transferencias de tecnologia (TT) a paises en desarrollo. Esta tesis analiza las causas de este resultado y busca mejorar la comprension sobre que constituye transferencia de tecnologia en el area de cambio climatico, cuales son los factores que la facilitan en paises en desarrollo y que politicas podrian implementarse para reforzar dichos factores. A pesar del extendido reconocimiento sobre la importancia de la transferencia de tecnologia a paises en desarrollo en la agenda politica de cambio climatico, esta cuestion no ha sido suficientemente atendida por la investigacion existente. Las definiciones actuales de transferencia de tecnologia relacionada con la mitigacion del cambio climatico no tienen en cuenta la diversidad de canales por las que se manifiestan o los efectos que consiguen. Los factores facilitadores de TT en paises en desarrollo no BRIC (Brasil, Rusia, India y China) apenas han sido investigados, y las recomendaciones politicas para aumentar el nivel y la calidad de la TT no se han adaptado a las necesidades especificas de paises muy heterogeneos aglutinados bajo el denominado grupo de "paises en desarrollo". Esta tesis contribuye a enriquecer el debate sobre la TT de cambio climatico con la perspectiva de una economia emergente de pequeno tamano (Chile) y el analisis cuantitativo de factores que facilitan la TT en una amplia muestra de paises en desarrollo. Se utilizan dos metodologias para el estudio de la TT a paises en desarrollo: analisis comparativo de casos de estudio y analisis cuantitativo basado en metodos multivariantes. Los casos de estudio analizan procesos de TT en diez casos basados en Chile, para derivar conclusiones sobre los factores que facilitan u obstaculizan el proceso de transferencia. El analisis cuantitativo multivariante utiliza tres metodologias: regresion multiple, analisis de componentes principales y analisis cluster. Con dichas metodologias se busca analizar el posicionamiento de diversos paises en cuanto a factores que facilitan la TT; las relaciones entre dichos factores e indicadores de transferencia tecnologica; y crear grupos de paises con caracteristicas similares que podrian beneficiarse de politicas similares para la promocion de la transferencia de tecnologia. Los resultados de la tesis se estructuran en torno a cuatro preguntas de investigacion: .Que es la transferencia de tecnologia y como ocurre?; .Es posible medir la transferencia de tecnologias de bajo carbono?; .Que factores facilitan la transferencia de tecnologias de bajo carbono a paises en desarrollo? y .Como se puede agrupar a los paises en desarrollo en funcion de sus necesidades politicas para la promocion de la transferencia de tecnologias de bajo carbono?

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This paper describes two methods to cancel the effect of two kinds of leakage signals which may be presented when an antenna is measured in a planar near-field range. One method tries to reduce leakage bias errors from the receiver¿s quadrature detector and it is based on estimating the bias constant added to every near-field data sample. Then, that constant is subtracted from the data, removing its undesired effect on the far-field pattern. The estimation is performed by back-propagating the field from the scan plane to the antenna under test plane (AUT) and averaging all the data located outside the AUT aperture. The second method is able to cancel the effect of the leakage from faulty transmission lines, connectors or rotary joints. The basis of this method is also a reconstruction process to determine the field distribution on the AUT plane. Once this distribution is known, a spatial filtering is applied to cancel the contribution due to those faulty elements. After that, a near-field-to-far-field transformation is applied, obtaining a new radiation pattern where the leakage effects have disappeared. To verify the effectiveness of both methods, several examples are presented.

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The rotation maize and dry bean provides the main food supply of smallholder farmers in Honduras. Crop model assessment of climate change impacts (2070?2099 compared to a 1961?1990 baseline) on a maize?dry bean rotation for several sites across a range of climatic zones and elevations in Honduras. Low productivity systems, together with an uncertain future climate, pose a high level of risk for food security. The cropping systems simulation dynamic model CropSyst was calibrated and validated upon field trail site at Zamorano, then run with baseline and future climate scenarios based upon general circulation models (GCM) and the ClimGen synthetic daily weather generator. Results indicate large uncertainty in crop production from various GCM simulations and future emissions scenarios, but generally reduced yields at low elevations by 0 % to 22 % in suitable areas for crop production and increased yield at the cooler, on the hillsides, where farming needs to reduce soil erosion with conservation techniques. Further studies are needed to investigate strategies to reduce impacts and to explore adaptation tactics.

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The 12 January 2010, an earthquake hit the city of Port-au-Prince, capital of Haiti. The earthquake reached a magnitude Mw 7.0 and the epicenter was located near the town of Léogâne, approximately 25 km west of the capital. The earthquake occurred in the boundary region separating the Caribbean plate and the North American plate. This plate boundary is dominated by left-lateral strike slip motion and compression, and accommodates about 20 mm/y slip, with the Caribbean plate moving eastward with respect to the North American plate (DeMets et al., 2000). Initially the location and focal mechanism of the earthquake seemed to involve straightforward accommodation of oblique relative motion between the Caribbean and North American plates along the Enriquillo-Plantain Garden fault system (EPGFZ), however Hayes et al., (2010) combined seismological observations, geologic field data and space geodetic measurements to show that, instead, the rupture process involved slip on multiple faults. Besides, the authors showed that remaining shallow shear strain will be released in future surface-rupturing earthquakes on the EPGFZ. In December 2010, a Spanish cooperation project financed by the Politechnical University of Madrid started with a clear objective: Evaluation of seismic hazard and risk in Haiti and its application to the seismic design, urban planning, emergency and resource management. One of the tasks of the project was devoted to vulnerability assessment of the current building stock and the estimation of seismic risk scenarios. The study was carried out by following the capacity spectrum method as implemented in the software SELENA (Molina et al., 2010). The method requires a detailed classification of the building stock in predominant building typologies (according to the materials in the structure and walls, number of stories and age of construction) and the use of the building (residential, commercial, etc.). Later, the knowledge of the soil characteristics of the city and the simulation of a scenario earthquake will provide the seismic risk scenarios (damaged buildings). The initial results of the study show that one of the highest sources of uncertainties comes from the difficulty of achieving a precise building typologies classification due to the craft construction without any regulations. Also it is observed that although the occurrence of big earthquakes usually helps to decrease the vulnerability of the cities due to the collapse of low quality buildings and the reconstruction of seismically designed buildings, in the case of Port-au-Prince the seismic risk in most of the districts remains high, showing very vulnerable areas. Therefore the local authorities have to drive their efforts towards the quality control of the new buildings, the reinforcement of the existing building stock, the establishment of seismic normatives and the development of emergency planning also through the education of the population.

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In this paper, we investigate the real demand for climate protection when the purely individual perspective of existing revealed preference studies is relaxed. This is achieved in two treatments; first, we determine the information subjects receive about the demand revealed by other subjects in a similar decision making situation, second, collective action is implemented whereby all subjects are required to purchase the group?s median quantity at a given price. Participants in the experiment were offered the opportunity to contribute to climate protection by purchasing European Union Allowances. Allowances purchased were withdrawn from the European Emissions Trading Scheme. In our experiment, information about other subjects? behaviour has no treatment effect on the demand for climate protection. Under collective action however, the probability of purchasing allowances is higher compared to the reference treatment situation, an individual contribution mechanism. Furthermore, we observe a strong correlation between subjects? demand and their expectations about other participants? behaviour. When collective action is not available, subjects? e xpectations are consistent with free rider behaviour.

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This paper presents a reflection suppression technique for far field antenna measurements. The technique is based on a source reconstruction over a surface greater than the antenna itself. To be able to perform the reflection construction the next steps are required: the complete far field antenna pattern is obtained through interpolation of the acquired cuts, the currents are obtained through a holographic technique, the field out of the antenna area is filtered, and the pattern is reconstructed. The algorithm is used with measurements in the LEHA-UPM antenna measurement facilities and in the outdoor far field facility of LIT INPE in Brazil.

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Purpose: A fully three-dimensional (3D) massively parallelizable list-mode ordered-subsets expectation-maximization (LM-OSEM) reconstruction algorithm has been developed for high-resolution PET cameras. System response probabilities are calculated online from a set of parameters derived from Monte Carlo simulations. The shape of a system response for a given line of response (LOR) has been shown to be asymmetrical around the LOR. This work has been focused on the development of efficient region-search techniques to sample the system response probabilities, which are suitable for asymmetric kernel models, including elliptical Gaussian models that allow for high accuracy and high parallelization efficiency. The novel region-search scheme using variable kernel models is applied in the proposed PET reconstruction algorithm. Methods: A novel region-search technique has been used to sample the probability density function in correspondence with a small dynamic subset of the field of view that constitutes the region of response (ROR). The ROR is identified around the LOR by searching for any voxel within a dynamically calculated contour. The contour condition is currently defined as a fixed threshold over the posterior probability, and arbitrary kernel models can be applied using a numerical approach. The processing of the LORs is distributed in batches among the available computing devices, then, individual LORs are processed within different processing units. In this way, both multicore and multiple many-core processing units can be efficiently exploited. Tests have been conducted with probability models that take into account the noncolinearity, positron range, and crystal penetration effects, that produced tubes of response with varying elliptical sections whose axes were a function of the crystal's thickness and angle of incidence of the given LOR. The algorithm treats the probability model as a 3D scalar field defined within a reference system aligned with the ideal LOR. Results: This new technique provides superior image quality in terms of signal-to-noise ratio as compared with the histogram-mode method based on precomputed system matrices available for a commercial small animal scanner. Reconstruction times can be kept low with the use of multicore, many-core architectures, including multiple graphic processing units. Conclusions: A highly parallelizable LM reconstruction method has been proposed based on Monte Carlo simulations and new parallelization techniques aimed at improving the reconstruction speed and the image signal-to-noise of a given OSEM algorithm. The method has been validated using simulated and real phantoms. A special advantage of the new method is the possibility of defining dynamically the cut-off threshold over the calculated probabilities thus allowing for a direct control on the trade-off between speed and quality during the reconstruction.

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Water balance simulation in cropping systems is a very useful tool to study how water can be used efficiently. However this requires that models simulate an accurate water balance. Comparing model results with field observations will provide information on the performance of the models. The objective of this study was to test the performance of DSSAT model in simulating the water balance by comparing the simulations with observed measurements. The soil water balance in DSSAT uses a one dimensional ?tipping bucket? soil water balance approach where available soil water is determined by the drained upper limit (DUL), lower limit (LL) and saturated water content (SAT). A continuous weighing lysimeter was used to get the observed values of drainage and evapotranspiration (ET). An automated agrometeorological weather station close to the lisymeter was also used to record the climatic data. The model simulated accurately the soil water content after the optimization of the soil parameters. However it was found the inability of the model to capture small changes in daily drainage and ET. For that reason simulated cumulative values had larger errors as the time passed by. These results suggested the need to compare outputs of DSSAT and some hydrological model that simulates soil water movement with a more mechanistic approach. The comparison of the two models will allow us to find which mechanism can be modified or incorporated in DSSAT model to improve the simulations.

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We have analysed the geochemical (element analysis), mineralogical and sedimentary facies to characterize the sedimentary record in Fuentillejo maar-lake in the central Spanish volcanic field of Campo de Calatrava and thus be able to reconstruct the cyclicity of the sedimentary and paleoclimatic processes involved. The upper 20 m of core FUENT-1 show variations in clastic input and water chemistry in the lake throughout the last 50 ka cal BP. Being a closed system, the water level in this maar-lake depends primarily on the balance between precipitation and evaporation

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Pig’s slurry is a key source of greenhouse gases (GHG). In Spain, GHG emissions (CH4+ N2O) from pig slurry (storage and land application) accounted in 2011 for 18.4% of total GHG emissions (in CO2- equivalent) of the agriculture sector according to the National Inventory Report (NIR). Slurry composition can be modified through diet manipulation. The aim of this work was to evaluate the effect of different fibre types in fattening pigs’ diets on GHG emissions from pig slurry storage and field application.

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La familia Cupressaceae incluye un total de 133 especies agrupadas en 30 géneros, 17 de los cuales son monospecíficos. Esta familia se encuentra representada en todos los continentes salvo en la Antártida. Sus especies se distribuyen en distintas regiones climáticas, y en altitudes que varían desde el nivel del mar hasta los 5.000 m. La falta de descripción anatómica de muchos de los géneros y especies de Cupressaceae es notable, así como la contradicción que aparece entre distintas investigaciones sobre las características anatómicas de la madera descritas para cada especie. Este estudio describe la anatomía de la madera de Cupressaceae y analiza las características que podrían representar sinapomorfías de los clados delimitados en los estudios filogenéticos. Siguiendo los métodos tradicionales de preparación y descripción de la madera a nivel microscópico, se ha estudiado la madera de 113 especies de los 30 géneros de Cupressaceae. Para ello se han empleado muestras de madera de origen trazable, procedentes de colecciones de madera de distintas instituciones internacionales. Se ha empleado una robusta filogenia molecular para la reconstrucción de los caracteres ancestrales. La anatomía de la madera de los 30 géneros de Cupressaceae, pone de manifiesto la gran homogeneidad de la familia, caracterizada por la presencia de traqueidas axiales sin engrosamientos helicoidales, parénquima radial con paredes horizontales lisas, punteaduras del campo de cruce de tipo cupresoide y la carencia de canales resiníferos fisiológicos. Además, todos presentan parénquima axial (salvo Neocallitropsis, Thuja y Xanthocyparis), punteaduras radiales areoladas con toro definido (salvo Thuja y Thujopsis), siendo habitual la presencia de punteaduras areoladas en las paredes tangenciales de la madera tardía, y verrugosidades en la cara interna de las traqueidas (salvo Ca. macleayana, Libocedrus, Papuacedrus y Neocallitropsis). Los radios leñosos son homogéneos y están compuestos de parénquima radial (con la presencia de traqueidas radiales en algunas especies de Cupressus, Sequoia, Thujopsis y X. nootkatensis) con paredes finales lisas o lisas y noduladas (exclusivamente noduladas en Cal. macrolepis, C. bakeri y en la mayoría de especies de Juniperus), y el rango de altura de los radios leñosos se encuentra entre 5 y 15 células. Se consideran posibles sinapomorfismos de Cupressaceae la presencia de verrugosidades en la cara interna de las traqueidas, la presencia de traqueidas axiales sin engrosamientos helicoidales, la presencia de parénquima axial, la presencia de radios leñosos homogéneos (compuestos únicamente de parénquima radial), la tipología de las paredes horizontales del parénquima radial, las punteaduras del campo de cruce de tipo cupresoide y la ausencia de canales resiníferos fisiológicos, pero lo que realmente diferencia a este grupo de coníferas es la simultaneidad de todos estos caracteres en sus maderas. Como sinapomorfías específicas por clados se proponen: la ausencia de toro definido y muescas en el borde de las punteaduras en Thuja-Thujopsis, la existencia de extensiones de toro en Diselma-Fitzroya-Widdringtonia; la presencia de engrosamientos callitroides en Callitris-Actinostrobus; la presencia de espacios intercelulares y las muescas en el borde de las punteaduras en el clado formado por el género Juniperus y las especies de Cupressus en la región oriental; la presencia de paredes finales del parénquima radial tanto lisas como noduladas en los clados formados por el género Xanthocyparis y las especies de Cupressus en la región occidental y en Fitzroya-Diselma; y por último, la presencia de punteaduras del campo de cruce de tipo taxodioide en los clados taxodioid y sequoioid. ABSTRACT The Cupressaceae family comprises 133 species grouped into 30 genera, 17 of which are monotypic. The family is represented in all continents except Antarctica. Its species are distributed in various climate zones and at altitudes from sea level to 5,000 m. There is a considerable lack of anatomical descriptions for many genera and species of Cupressaceae and much contradiction between studies about the wood anatomical features described for each species. This study describes the wood anatomy of Cupressaceae and analyses the features that could represent synapomorphies of the clades recovered in phylogenetic studies. Following the traditional methods of preparation and description of wood at microscopic level, a study was made of the wood of 113 species of the 30 Cupressaceae genera. The study samples had traceable origins and came from wood collections held at various international institutions. A robust molecular phylogeny was used for ancestral state reconstruction. The wood anatomy of the 30 genera of the Cupressaceae shows the high homogeneity of the family, which is characterised by the presence of axial tracheids without helical thickenings, smooth horizontal walls of ray parenchyma cells, cupressoid cross-field pits, and the absence of physiological resin canals. In addition, they all have axial parenchyma (except Neocallitropsis, Thuja and Xanthocyparis), a warty layer on the inner wall of the tracheids (except Ca. macleayana, Libocedrus, Papuacedrus and Neocallitropsis) and tracheid pitting in radial walls with a well defined torus (except Thuja and Thujopsis); tracheid pitting in the tangential walls of the latewood is common. Rays are homogeneous and are composed of ray parenchyma (with the presence of ray tracheids in some species of Cupressus, Sequoia, Thujopsis and X. nootkatensis), with smooth end walls or both smooth and nodular end walls (exclusively nodular in Cal. macrolepis, C. bakeri and most Juniperus species), and ray height range is 5 to 15 cells. Possible synapomorphies of Cupressaceae are the presence of a warty layer on the inner layer of the tracheids, axial tracheids without helical thickenings, the presence of axial parenchyma, homogeneous rays (composed exclusively of ray parenchyma), the typology of the horizontal walls of ray parenchyma cells, cupressoid cross-field pits and the absence of physiological resin canals, but what truly differentiates this group of softwoods is the co-occurrence of all these features in their wood. The following are proposed as clade-specific synapomorphies: absence of a well-defined torus and presence of pits with notched borders in Thuja-Thujopsis, torus extensions in Diselma-Fitzroya-Widdringtonia; callitroid thickenings in Callitris-Actinostrobus; intercellular spaces and pits with notched borders in the clade formed by the genus Juniperus and the species of Cupressus in the eastern region; smooth and nodular ray parenchyma end walls in the clades formed by the genus Xanthocyparis and the species of Cupressus in the western region and in Fitzroya-Diselma, and taxodioid cross-field pits in the taxodioid and sequoioid clades.

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A method to reconstruct the excitation coefficients of wide-slot arrays from near-field data is presented. The plane wave spectrum (PWS) is used for reconstruction, and the shape of the field distribution on a wide slot is considered in the calculation of the PWS. The proposed algorithm is validated through the reconstruction of the excitation coefficients of a wide-slot array with element failures from the simulated nearfield data. The element failures are clearly located by the proposed algorithm