MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Distance-based kriging relying on proxy simulations for inverse conditioning

Let us consider a large set of candidate parameter fields, such as hydraulic conductivity maps, on which we can run an accurate forward flow and transport simulation. We address the issue of rapidly identifying a subset of candidates whose response best match a reference response curve. In order to keep the number of calls to the accurate flow simulator computationally tractable, a recent distance-based approach relying on fast proxy simulations is revisited, and turned into a non-stationary kriging method where the covariance kernel is obtained by combining a classical kernel with the proxy. Once the accurate simulator has been run for an initial subset of parameter fields and a kriging metamodel has been inferred, the predictive distributions of misfits for the remaining parameter fields can be used as a guide to select candidate parameter fields in a sequential way. The proposed algorithm, Proxy-based Kriging for Sequential Inversion (ProKSI), relies on a variant of the Expected Improvement, a popular criterion for kriging-based global optimization. A statistical benchmark of ProKSI’s performances illustrates the efficiency and the robustness of the approach when using different kinds of proxies.

Radium concentration in water samples from the Northeast Atlantic

We present field measurements of air-sea gas exchange by the radon deficit method that were carried out during JASIN 1978 (NE Atlantic) and FGGE 1979 (Equatorial Atlantic). Both experiments comprised repeated deficit measurements at fixed position over periods of days or longer, using a previously descibed precise and fast-acquiaition, automatic radon measuring system. The deficit time series exhibit variations that only partly reflect the expected changes in gas transfer. By evaluating averages over each time series we deduce the following gas transfer velocities (average wind velocity and water temperature in parentheses): JASIN phase 1: 1.6 ± 0.8 m/d (at ~6 m/s, 13°C) JASIN phase 2: 4.3 ± 1.2 m/d (at ~8 m/s, 13°C) FGGE: 1.2 ± 0.4 m/d (at ~5 m/s, 28°C) 0.9 ± 0.4 m/d (at ~7 m/s, 28°C) 1.5 ± 0.4 m/d (at ~7 m/s, 28°C) The large difference betwen the JASIN phase 2 and FGGE values despite quite similare average wind velocity becomes even larger when the values are, however, fully compatible with the range of gas transfer velocities observed in laboratory experiments and the conclusion is suggested that their difference is caused by the highly different wind variability in JASIN and FGGE. We conclude that in gas exchange parameterization it is not sufficinent to consider wind velocity only. A comparison of our observations with laboratory results outlines the range of variations of air-sea gas transfer velocities with wind velocity and sea state. We also reformulate the radon deficit method, in the light of our observed deficit variations, to account explicitely for non-stationary and horizontal inhomogeneity in previous radon work introduces considerable uncertainty in deduced gas transfere velocity. We furthermore discuss the observational rewuirements that have to be met for an adequate exploitation of the radon deficit method, of which an observation area of minimum horizontal inhomogeneity and monitoring of the remaining inhomogeneities are thought to be the most stringent ones.

Nd concentrations and isotopic composition in the western Mediterranean Sea

The concentration and isotopic composition of Nd in water and particles collected in the western Mediterranean Sea are studied by two complementary approaches. The first examines local vertical profiles and time series; the second considers the global Nd budget of the whole western Mediterranean Sea. These two approaches are used to quantify the Nd inputs and the dissolved/particulate exchange processes in the water column. Two profiles of Nd in seawater in the Ligurian Sea taken in May and October 1992 show an average epsilon-Nd(0) = -9.6 ± 0.5. Seawater from the Strait of Sicily, representative of the eastern waters flowing into the western basin, is more radiogenic [epsilon-Nd(0) = -7.7 ± 0.6]. Profiles of particulate matter collected in sediment traps in coastal (Gulf of Lions) and offshore (Ligurian Sea) environments are also shown. Particles are enriched in Nd and are more radiogenic near the coast than offshore. Measurements of Nd concentration and epsilon-Nd(0) of external sources to the western Mediterranean Sea compared with the literature data demonstrate that particulate flux of atmospheric Saharan origin are more rich ([Nd] = 38 ± 10 µg/g) and less radiogenic [epsilon-Nd(0) = -13.0 ± 1.0] than riverine particulate discharge ([Nd] = 21.5 ± 4.4 µg/g; epsilon-Nd(0) = -10.1 ± 0.5), allowing to trace Nd particulate inputs in the water column. Nd atmospheric flux appears to be the major source into the whole western basin, although lateral advection of riverine material is the prevailing process in the coastal environment. Offshore, the vertical propagation of an important Saharan dust event has been recorded for two months in sediment traps at 80, 200 and 1000 m. The evolution of the resulting negative epsilon-Nd(0) peak along depth and time shows that the particles reach 200 m on a time scale of one week. For the first time, the Nd budget in the western Mediterranean basin is constrained by both concentrations and isotopic compositions measured in particles and seawater. Surface budget requires a remobilization of 30 ± 20% of particulate Nd input. In deep water, dissolved Nd concentrations are balanced by a scavenging of 10 ± 20% of the sinking particulate flux. On the other hand, the deep isotopic compositions suggest an exchange between 30 ± 20% of the sinking particles and the deep waters. The hypothesis of a non-stationary regime for the surface waters in the Ligurian Sea is also considered.

Sedimentology and geochemistry of core GIK23258-2 in the Barents Sea

At the western continental margin of the Barents Sea, 75°N, hemipelagic sediments provide a record of Holocene climate change with a time resolution of 10-70 years. Planktic foraminifera counts reveal a very early Holocene thermal optimum 10.7-7.7 kyr BP, with summer sea surface temperatures (SST) of 8°C and a much enhanced West Spitsbergen Current. There was a short cooling between 8.8 and 8.2 kyr BP. In the middle and late Holocene summer, SST dropped to 2.5°-5.0°C, indicative of reduced Atlantic heat advection, except for two short warmings near 2.2 and 1.6 kyr BP. Distinct quasi-periodic spikes of coarse sediment fraction (with large portions of lithic grains, benthic and planktic foraminifera) record cascades of cold, dense winter water down the continental slope as a result of enhanced seasonal sea ice formation and storminess on the Barents shelf over the entire Holocene. The spikes primarily cluster near recurrence intervals of 400-650 and 1000-1350 years, when traced over the entire Holocene, but follow significant 885-/840- and 505-/605-year periodicities in the early Holocene. These non-stationary periodicities mimic the Greenland-[Formula: See Text]Be variability, which is a tracer of solar forcing. Further significant Holocene periodicities of 230, (145) and 93 years come close to the deVries and Gleissberg solar cycles.

Homography-based ground plane detection using a single on-board camera

This study presents a robust method for ground plane detection in vision-based systems with a non-stationary camera. The proposed method is based on the reliable estimation of the homography between ground planes in successive images. This homography is computed using a feature matching approach, which in contrast to classical approaches to on-board motion estimation does not require explicit ego-motion calculation. As opposed to it, a novel homography calculation method based on a linear estimation framework is presented. This framework provides predictions of the ground plane transformation matrix that are dynamically updated with new measurements. The method is specially suited for challenging environments, in particular traffic scenarios, in which the information is scarce and the homography computed from the images is usually inaccurate or erroneous. The proposed estimation framework is able to remove erroneous measurements and to correct those that are inaccurate, hence producing a reliable homography estimate at each instant. It is based on the evaluation of the difference between the predicted and the observed transformations, measured according to the spectral norm of the associated matrix of differences. Moreover, an example is provided on how to use the information extracted from ground plane estimation to achieve object detection and tracking. The method has been successfully demonstrated for the detection of moving vehicles in traffic environments.

Two Different Approaches of Feature Extraction for Classifying the EEG Signals

The electroencephalograph (EEG) signal is one of the most widely used signals in the biomedicine field due to its rich information about human tasks. This research study describes a new approach based on i) build reference models from a set of time series, based on the analysis of the events that they contain, is suitable for domains where the relevant information is concentrated in specific regions of the time series, known as events. In order to deal with events, each event is characterized by a set of attributes. ii) Discrete wavelet transform to the EEG data in order to extract temporal information in the form of changes in the frequency domain over time- that is they are able to extract non-stationary signals embedded in the noisy background of the human brain. The performance of the model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed scheme has potential in classifying the EEG signals.

Large aperture antenna arrays with subband delay compensation for reception of wideband satellite signals

Con esta disertación se pretenden resolver algunos de los problemas encontrados actualmente en la recepción de señales de satélites bajo dos escenarios particularmente exigentes: comunicaciones de Espacio Profundo y en banda Ka. Las comunicaciones con sondas de Espacio Profundo necesitan grandes aperturas en tierra para poder incrementar la velocidad de datos. La opción de usar antennas con diámetro mayor de 35 metros tiene serios problemas, pues antenas tan grandes son caras de mantener, difíciles de apuntar, pueden tener largos tiempo de reparación y además tienen una efeciencia decreciente a medida que se utilizan bandas más altas. Soluciones basadas en agrupaciones de antenas de menor tamaño (12 ó 35 metros) son mas ecónomicas y factibles técnicamente. Las comunicaciones en banda Ka tambien pueden beneficiarse de la combinación de múltiples antennas. Las antenas de menor tamaño son más fáciles de apuntar y además tienen un campo de visión mayor. Además, las técnicas de diversidad espacial pueden ser reemplazadas por una combinación de antenas para así incrementar el margen del enlace. La combinación de antenas muy alejadas sobre grandes anchos de banda, bien por recibir una señal de banda ancha o múltiples de banda estrecha, es complicada técnicamente. En esta disertación se demostrará que el uso de conformador de haz en el dominio de la frecuencia puede ayudar a relajar los requisitos de calibración y, al mismo tiempo, proporcionar un mayor campo de visión y mayores capacidades de ecualización. Para llevar esto a cabo, el trabajo ha girado en torno a tres aspectos fundamentales. El primero es la investigación bibliográfica del trabajo existente en este campo. El segundo es el modelado matemático del proceso de combinación y el desarrollo de nuevos algoritmos de estimación de fase y retardo. Y el tercero es la propuesta de nuevas aplicaciones en las que usar estas técnicas. La investigación bibliográfica se centra principalmente en los capítulos 1, 2, 4 y 5. El capítulo 1 da una breve introducción a la teoría de combinación de antenas de gran apertura. En este capítulo, los principales campos de aplicación son descritos y además se establece la necesidad de compensar retardos en subbandas. La teoría de bancos de filtros se expone en el capítulo 2; se selecciona y simula un banco de filtros modulado uniformemente con fase lineal. Las propiedades de convergencia de varios filtros adaptativos se muestran en el capítulo 4. Y finalmente, las técnicas de estimación de retardo son estudiadas y resumidas en el capítulo 5. Desde el punto de vista matemático, las principales contribución de esta disertación han sido: • Sección 3.1.4. Cálculo de la desviación de haz de un conformador de haz con compensación de retardo en pasos discretos en frecuencia intermedia. • Sección 3.2. Modelo matemático de un conformador de haz en subbandas. • Sección 3.2.2. Cálculo de la desviación de haz de un conformador de haz en subbandas con un buffer de retardo grueso. • Sección 3.2.4. Análisis de la influencia de los alias internos en la compensación en subbandas de retardo y fase. • Sección 3.2.4.2. Cálculo de la desviación de haz de un conformador de haz con compensación de retardo en subbandas. • Sección 3.2.6. Cálculo de la ganancia de relación señal a ruido de la agrupación de antenas en cada una de las subbandas. • Sección 3.3.2. Modelado de la función de transferencia de la agrupación de antenas bajo errores de estimación de retardo. • Sección 3.3.3. Modelado de los efectos de derivas de fase y retardo entre actualizaciones de las estimaciones. • Sección 3.4. Cálculo de la directividad de la agrupación de antenas con y sin compensación de retardos en subbandas. • Sección 5.2.6. Desarrollo de un algorimo para estimar la fase y el retardo entre dos señales a partir de su descomposición de subbandas bajo entornos estacionarios. • Sección 5.5.1. Desarrollo de un algorimo para estimar la fase, el retardo y la deriva de retardo entre dos señales a partir de su descomposición de subbandas bajo entornos no estacionarios. Las aplicaciones que se pueden beneficiar de estas técnicas son descritas en el capítulo 7: • Sección 6.2. Agrupaciones de antenas para comunicaciones de Espacio Profundo con capacidad multihaz y sin requisitos de calibración geométrica o de retardo de grupo. • Sección 6.2.6. Combinación en banda ancha de antenas con separaciones de miles de kilómetros, para recepción de sondas de espacio profundo. • Secciones 6.4 and 6.3. Combinación de estaciones remotas en banda Ka en escenarios de diversidad espacial, para recepción de satélites LEO o GEO. • Sección 6.3. Recepción de satélites GEO colocados con arrays de antenas multihaz. Las publicaciones a las que ha dado lugar esta tesis son las siguientes • A. Torre. Wideband antenna arraying over long distances. Interplanetary Progress Report, 42-194:1–18, 2013. En esta pulicación se resumen los resultados de las secciones 3.2, 3.2.2, 3.3.2, los algoritmos en las secciones 5.2.6, 5.5.1 y la aplicación destacada en 6.2.6. • A. Torre. Reception of wideband signals from geostationary collocated satellites with antenna arrays. IET Communications, Vol. 8, Issue 13:2229–2237, September, 2014. En esta segunda se muestran los resultados de la sección 3.2.4, el algoritmo en la sección 5.2.6.1 , y la aplicación mostrada en 6.3. ABSTRACT This dissertation is an attempt to solve some of the problems found nowadays in the reception of satellite signals under two particular challenging scenarios: Deep Space and Ka-band communications. Deep Space communications require from larger apertures on ground in order to increase the data rate. The option of using single dishes with diameters larger than 35 meters has severe drawbacks. Such antennas are expensive to maintain, prone to long downtimes, difficult to point and have a degraded performance in high frequency bands. The array solution, either with 12 meter or 35 meter antennas is deemed to be the most economically and technically feasible solution. Ka-band communications can also benefit from antenna arraying technology. The smaller aperture antennas that make up the array are easier to point and have a wider field of view allowing multiple simultaneous beams. Besides, site diversity techniques can be replaced by pure combination in order to increase link margin. Combination of far away antennas over a large bandwidth, either because a wideband signal or multiple narrowband signals are received, is a demanding task. This dissertation will show that the use of frequency domain beamformers with subband delay compensation can help to ease calibration requirements and, at the same time, provide with a wider field of view and enhanced equalization capabilities. In order to do so, the work has been focused on three main aspects. The first one is the bibliographic research of previous work on this subject. The second one is the mathematical modeling of the array combination process and the development of new phase/delay estimation algorithms. And the third one is the proposal of new applications in which these techniques can be used. Bibliographic research is mainly done in chapters 1, 2, 4 and 5. Chapter 1 gives a brief introduction to previous work in the field of large aperture antenna arraying. In this chapter, the main fields of application are described and the need for subband delay compensation is established. Filter bank theory is shown in chapter 2; a linear phase uniform modulated filter bank is selected and simulated under diverse conditions. The convergence properties of several adaptive filters are shown in chapter 4. Finally, delay estimation techniques are studied and summarized in chapter 5. From a mathematical point of view, the main contributions of this dissertation have been: • Section 3.1.4. Calculation of beam squint of an IF beamformer with delay compensation at discrete time steps. • Section 3.2. Establishment of a mathematical model of a subband beamformer. • Section 3.2.2. Calculation of beam squint in a subband beamformer with a coarse delay buffer. • Section 3.2.4. Analysis of the influence of internal aliasing on phase and delay subband compensation. • Section 3.2.4.2. Calculation of beam squint of a beamformer with subband delay compensation. • Section 3.2.6. Calculation of the array SNR gain at each of the subbands. • Section 3.3.2. Modeling of the transfer function of an array subject to delay estimation errors. • Section 3.3.3. Modeling of the effects of phase and delay drifts between estimation updates. • Section 3.4. Calculation of array directivity with and without subband delay compensation. • Section 5.2.6. Development of an algorithm to estimate relative delay and phase between two signals from their subband decomposition in stationary environments. • Section 5.5.1. Development of an algorithm to estimate relative delay rate, delay and phase between two signals from their subband decomposition in non stationary environments. The applications that can benefit from these techniques are described in chapter 7: • Section 6.2. Arrays of antennas for Deep Space communications with multibeam capacity and without geometric or group delay calibration requirement. • Section 6.2.6. Wideband antenna arraying over long distances, in the range of thousands of kilometers, for reception of Deep Space probes. • Sections 6.4 y 6.3. Combination of remote stations in Ka-band site diversity scenarios for reception of LEO or GEO satellites. • Section 6.3. Reception of GEO collocated satellites with multibeam antenna arrays. The publications that have been made from the work in this dissertation are • A. Torre. Wideband antenna arraying over long distances. Interplanetary Progress Report, 42-194:1–18, 2013. This article shows the results in sections 3.2, 3.2.2, 3.3.2, the algorithms in sections 5.2.6, 5.5.1 and the application in section 6.2.6. • A. Torre. Reception of wideband signals from geostationary collocated satellites with antenna arrays. IET Communications, Vol. 8, Issue 13:2229–2237, September, 2014. This second article shows among others the results in section 3.2.4, the algorithm in section 5.2.6.1 , and the application in section 6.3.

Direct Vlasov simulations of electron-attracting cylindrical Langmuir probes in flowing plasmas

Current collection by positively polarized cylindrical Langmuir probes immersed in flowing plasmas is analyzed using a non-stationary direct Vlasov-Poisson code. A detailed description of plasma density spatial structure as a function of the probe-to-plasma relative velocity U is presented. Within the considered parametric domain, the well-known electron density maximum close to the probe is weakly affected by U. However, in the probe wake side, the electron density minimum becomes deeper as U increases and a rarified plasma region appears. Sheath radius is larger at the wake than at the front side. Electron and ion distribution functions show specific features that are the signature of probe motion. In particular, the ion distribution function at the probe front side exhibits a filament with positive radial velocity. It corresponds to a population of rammed ions that were reflected by the electric field close to the positively biased probe. Numerical simulations reveal that two populations of trapped electrons exist: one orbiting around the probe and the other with trajectories confined at the probe front side. The latter helps to neutralize the reflected ions, thus explaining a paradox in past probe theory.

Climate variability effects on field crops in Iberian Peninsula. Predictability

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.

El Niño influence on potential maize yield in Iberian Peninsula

El Niño phenomenon is the leading mode of sea surface temperature interannual variability. It can affect weather patterns worldwide and therefore crop production. Crop models are useful tools for impact and predictability applications, allowing to obtain long time series of potential and attainable crop yield, unlike to available time series of observed crop yield for many countries. Using this tool, crop yield variability in a location of Iberia Peninsula (IP) has been previously studied, finding predictability from Pacific El Niño conditions. Nevertheless, the work has not been done for an extended area. The present work carries out 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 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 potential usefulness of this study is to apply the relationships found to improving crop forecasting in IP.

Conceptual modelling to assess how the interplay of hydrological connectivity, catchment storage and tracer dynamics controls nonstationary water age estimates

Acknowledgements We would like to gratefully acknowledge the data provided by SEPA, Iain Malcolm. Mark Speed, Susan Waldron and many MSS staff helped with sample collection and lab analysis. We thank the European Research Council (project GA 335910 VEWA) for funding and are grateful for the constructive comments provided by three anonymous reviewers.

Método multigrid algébrico: reutilização das estruturas multigrid no transporte de contaminantes

A necessidade de obter solução de grandes sistemas lineares resultantes de processos de discretização de equações diferenciais parciais provenientes da modelagem de diferentes fenômenos físicos conduz à busca de técnicas numéricas escaláveis. Métodos multigrid são classificados como algoritmos escaláveis.Um estimador de erros deve estar associado à solução numérica do problema discreto de modo a propiciar a adequada avaliação da solução obtida pelo processo de aproximação. Nesse contexto, a presente tese caracteriza-se pela proposta de reutilização das estruturas matriciais hierárquicas de operadores de transferência e restrição dos métodos multigrid algébricos para acelerar o tempo de solução dos sistemas lineares associados à equação do transporte de contaminantes em meio poroso saturado. Adicionalmente, caracteriza-se pela implementação das estimativas residuais para os problemas que envolvem dados constantes ou não constantes, os regimes de pequena ou grande advecção e pela proposta de utilização das estimativas residuais associadas ao termo de fonte e à condição inicial para construir procedimentos adaptativos para os dados do problema. O desenvolvimento dos códigos do método de elementos finitos, do estimador residual e dos procedimentos adaptativos foram baseados no projeto FEniCS, utilizando a linguagem de programação PYTHONR e desenvolvidos na plataforma Eclipse. A implementação dos métodos multigrid algébricos com reutilização considera a biblioteca PyAMG. Baseado na reutilização das estruturas hierárquicas, os métodos multigrid com reutilização com parâmetro fixo e automática são propostos, e esses conceitos são estendidos para os métodos iterativos não-estacionários tais como GMRES e BICGSTAB. Os resultados numéricos mostraram que o estimador residual captura o comportamento do erro real da solução numérica, e fornece algoritmos adaptativos para os dados cuja malha retornada produz uma solução numérica similar à uma malha uniforme com mais elementos. Adicionalmente, os métodos com reutilização são mais rápidos que os métodos que não empregam o processo de reutilização de estruturas. Além disso, a eficiência dos métodos com reutilização também pode ser observada na solução do problema auxiliar, o qual é necessário para obtenção das estimativas residuais para o regime de grande advecção. Esses resultados englobam tanto os métodos multigrid algébricos do tipo SA quanto os métodos pré-condicionados por métodos multigrid algébrico SA, e envolvem o transporte de contaminantes em regime de pequena e grande advecção, malhas estruturadas e não estruturadas, problemas bidimensionais, problemas tridimensionais e domínios com diferentes escalas.

Investment behaviour of EU arable crop farms in selected EU countries and the impact of policy reforms. Factor Markets Working Document No. 42, May 2013

This deliverable provides a comparative analysis, among selected EU member states, of the investment demand of a sample of specialised field crop farms for farm buildings, machinery and equipment as determined by different types and levels of Common Agricultural Policy support. It allows for the existence of uncertainty in the price of output farmers receive and for both long- and short-run determinants of investment levels, as well as for the presence of irregularities in the cost adjustment function due to the existence of threshold-type behaviours. The empirical estimation reveals that three investment regimes are consistently identified in Germany and Hungary, across asset and support types, and in France for machinery and equipment. More traditional disinvestment-investment type behaviours characterise investment in farm building in France and the UK, across support types, and Italy for both asset classes under coupled payments. The long-run dynamic adjustment of capital stocks is consistently and significantly estimated to be towards a – mostly non-stationary – lower level of capitalisation of the farm analysed. By contrast, the expected largely positive short-run effects of an increase in output prices are often not significant. The effect of CAP support on both types of investment is positive, although seldom significant, while the proxy for uncertainty employed fails to be significant yet, in most cases, has the expected effect of reducing the investment levels.

Composition of basalts from the north part of the Bougault anomaly, Mid-Atlantic Ridge 15°N

A quantitative model of development of magmatic and ore-magmatic systems under crests of mid-ocean ridges is constructed. Correct physical models of melting zone formation in approximation to active spreading, non-stationary dynamics of magma intrusion from a center of generation, filling of magma chambers of various shapes, feeding of fissure-type volcanoes, and retrograde boiling of melts during solidification of intrusive bodies beneath axial zones of spreading in crests of ridges are proposed. Physicochemical and mathematical theories of disintegration of multi-component solutions, growth of liquational drops of ore melts, and sublimation of components from magmatic gases are elaborated. Methods for constructing physically correct models of heat and mass transfer in heterophase media are devised. Modeling of development of magmatic and ore-magmatic systems on the basis of the Usov-Kuznetsov facies method and the Pospelov system approach are advanced. For quantitative models numerical circuits are developed and numerical experiments are carried out.