Climate Change Impacts on Maize and Dry Bean Yields of smallholder farmers in Honduras

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.

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Efectos del cambio climático y usos del suelo sobre los recursos hídricos de la cuenca del río Tordera (Barcelona, España)

Se presentan los efectos del cambio global en la cuenca del río Tordera (España) para el periodo 2000-2050, escenarios climáticos A2 (medio-alto) definidos por el Panel Intergubernamental del Cambio Climático (IPCC, 200) y escenarios socioeconómicos (cambios previstos en la cuenca) denominados estable y tendencial. Los efectos sobre los recursos hídricos se han analizado de forma conjunta superficial-subterránea mediante una metodológica de tipo acoplado. Para establecer los impactos futuros sobre los recursos hídricos se ha seleccionado el Modelo de Circulación Global ECHAM5 (Max Planck Institute). Los resultados obtenidos indican una disminución de la precipitación del 11.3% y un aumento de la temperatura de 1ºC, respecto a los valores históricos de la zona. De acuerdo a la proyección futura (2050) sobre cambios en los recursos hídricos, la escorrentía superficial obtenida mediante simulación con el código HEC-HMS 3.4 experimenta una reducción del 31.8% respecto al valor histórico y la recarga natural, estimada mediante VISUAL-Balan, se reduce en un 11.7%. El balance en el acuífero deltaico simulado mediante MODFLOW 2009.1 Pro muestra igualmente una disminución de los parámetros del balance. Los cambios del uso del suelo previstos de acuerdo a la legislación vigente (escenarios socioeconómicos) no conducen a la generación de un impacto apreciable en los recursos hídricos; según los escenarios definidos la variación de precipitación y temperatura son los parámetros fundamentales del cambio previsto.

Identifying student and teacher difficulties in interpreting atomic spectra using a quantum model of emission and absorption of radiation

Our study sets out to identify the difficulties that high school students, teachers, and university students encounter when trying to explain atomic spectra. To do so, we identify the key concepts that any quantum model for the emission and absorption of electromagnetic radiation must include to account for the gas spectra and we then design two questionnaires, one for teachers and the other for students. By analyzing the responses, we conclude that (i) teachers lack a quantum model for the emission and absorption of electromagnetic radiation capable of explaining the spectra, (ii) teachers and students share the same difficulties, and (iii) these difficulties concern the model of the atom, the model of radiation, and the model of the interaction between them.

Analysis of Lead-Acid batteries with a third-order dynamical model

Electrical energy storage is a really important issue nowadays. As electricity is not easy to be directly stored, it can be stored in other forms and converted back to electricity when needed. As a consequence, storage technologies for electricity can be classified by the form of storage, and in particular we focus on electrochemical energy storage systems, better known as electrochemical batteries. Largely the more widespread batteries are the Lead-Acid ones, in the two main types known as flooded and valve-regulated. Batteries need to be present in many important applications such as in renewable energy systems and in motor vehicles. Consequently, in order to simulate these complex electrical systems, reliable battery models are needed. Although there exist some models developed by experts of chemistry, they are too complex and not expressed in terms of electrical networks. Thus, they are not convenient for a practical use by electrical engineers, who need to interface these models with other electrical systems models, usually described by means of electrical circuits. There are many techniques available in literature by which a battery can be modeled. Starting from the Thevenin based electrical model, it can be adapted to be more reliable for Lead-Acid battery type, with the addition of a parasitic reaction branch and a parallel network. The third-order formulation of this model can be chosen, being a trustworthy general-purpose model, characterized by a good ratio between accuracy and complexity. Considering the equivalent circuit network, all the useful equations describing the battery model are discussed, and then implemented one by one in Matlab/Simulink. The model has been finally validated, and then used to simulate the battery behaviour in different typical conditions.

Mineralogy of ODP Hole 117-722B (Appendix)

Bulk mineralogy of the terrigenous fraction of 99 samples from ODP Site 722 on the Owen Ridge, western Arabian Sea, has been determined by x-ray diffraction, using an internal standard method. The sampling interval, approximately 4.3 k.y., provides a detailed mineralogic record for the past 500 k.y. Previous studies have identified important modern continental sediment sources and the mineral assemblages presently derived from each. These studies have also demonstrated that most of this material is supplied by southwest and northwest winds during the summer monsoon. A variety of marine and terrestrial records and general circulation model (GCM) simulations have indicated the importance of monsoonal circulation during the Pleistocene and Holocene and have demonstrated increased aridity during glacial times and increased humidity during inter glacials. The mineralogic data generated here were used to investigate variations in source area weathering conditions during these environmental changes. Terrigenous minerals present include smectite, illite, palygorskite, kaolinite, chlorite, quartz, plagioclase feldspar, and dolomite. This mineralogy is consistent with the compositions of source areas presently supplying sediment to the Arabian Sea. An R-mode factor analysis has identified four mineral assemblages present throughout the past 500 k.y.: quartz/chlorite/dolomite (Factor 1), kaolinite/plagioclase/illite (Factor 2), smectite (Factor 3), and palygorskite/dolomite (Factor 4). Chlorite, illite, and palygorskite are extremely susceptible to chemical weathering, and a spectral comparison of these factors with the eolian mass accumulation rate (MAR) record from Hole 722B (an index of dust source area aridity) indicates that Factors 1, 2, and 4 are directly related to changes in aridity. Because of these characteristics, Factors 1,2, and 4 are interpreted to originate from arid source regions. Factor 3 is interpreted to record more humid source conditions. Time-series of scores for the four factors are dominated by short-term (10-100 k.y.) variability, and do not correlate well to glacial/interglacial fluctuations in the time domain. These characteristics suggest that local climatic shifts were complex, and that equilibrium weathering assemblages did not develop immediately after climatic change. Spectral analysis of factor scores identifies peaks at or near the primary Milankovitch frequencies for all factors. Factor 1 (quartz/chlorite/dolomite), Factor 2 (kaolinite/plagioclase/illite), and Factor 4 (illite/palygorskite) are coherent and in phase with the MAR record over the 23, 41, and 100 k.y. bands, respectively. The reasons for coherency at single Milankovitch frequencies are not known, but may include differences in the susceptibilities of minerals to varying time scales of weathering and/or preferential development of suitable continental source environments by climatic changes at the various Milankovitch frequencies.

Results of Heinrich event 1 simulation from the University of Victoria Earth System-Climate Model (UVic ESCM) and the Community Climate System Model (CCSM3)

We investigated changes in tropical climate and vegetation cover associated with abrupt climate change during Heinrich Event 1 (HE1, ca. 17.5 ka BP) using two different global climate models: the University of Victoria Earth System-Climate Model (UVic ESCM) and the Community Climate System Model version 3 (CCSM3). Tropical South American and African pollen records suggest that the cooling of the North Atlantic Ocean during HE1 influenced the tropics through a southward shift of the rain belt. In this study, we simulated the HE1 by applying a freshwater perturbation to the North Atlantic Ocean. The resulting slowdown of the Atlantic Meridional Overturning Circulation was followed by a temperature seesaw between the Northern and Southern Hemispheres, as well as a southward shift of the tropical rain belt. The shift and the response pattern of the tropical vegetation around the Atlantic Ocean were more pronounced in the CCSM3 than in the UVic ESCM simulation. For tropical South America, opposite changes in tree and grass cover were modeled around 10° S in the CCSM3 but not in the UVic ESCM. In tropical Africa, the grass cover increased and the tree cover decreased around 15° N in the UVic ESCM and around 10° N in the CCSM3. In the CCSM3 model, the tree and grass cover in tropical Southeast Asia responded to the abrupt climate change during the HE1, which could not be found in the UVic ESCM. The biome distributions derived from both models corroborate findings from pollen records in southwestern and equatorial western Africa as well as northeastern Brazil.

Gray's model of personality and aggregate level factor analysis

Previous research shows that correlations tend to increase in magnitude when individuals are aggregated across groups. This suggests that uncorrelated constellations of personality variables (such as the primary scales of Extraversion and Neuroticism) may display much higher correlations in aggregate factor analysis. We hypothesize and report that individual level factor analysis can be explained in terms of Giant Three (or Big Five) descriptions of personality, whereas aggregate level factor analysis can be explained in terms of Gray's physiological based model. Although alternative interpretations exist, aggregate level factor analysis may correctly identify the basis of an individual's personality as a result of better reliability of measures due to aggregation. We discuss the implications of this form of analysis in terms of construct validity, personality theory, and its applicability in general. Copyright (C) 2003 John Wiley Sons, Ltd.

Global assessment of coral bleaching and required rates of adaptation under climate change

Elevated ocean temperatures can cause coral bleaching, the loss of colour from reef-building corals because of a breakdown of the symbiosis with the dinoflagellate Symbiodinium. Recent studies have warned that global climate change could increase the frequency of coral bleaching and threaten the long-term viability of coral reefs. These assertions are based on projecting the coarse output from atmosphere-ocean general circulation models (GCMs) to the local conditions around representative coral reefs. Here, we conduct the first comprehensive global assessment of coral bleaching under climate change by adapting the NOAA Coral Reef Watch bleaching prediction method to the output of a low- and high-climate sensitivity GCM. First, we develop and test algorithms for predicting mass coral bleaching with GCM-resolution sea surface temperatures for thousands of coral reefs, using a global coral reef map and 1985-2002 bleaching prediction data. We then use the algorithms to determine the frequency of coral bleaching and required thermal adaptation by corals and their endosymbionts under two different emissions scenarios. The results indicate that bleaching could become an annual or biannual event for the vast majority of the world's coral reefs in the next 30-50 years without an increase in thermal tolerance of 0.2-1.0 degrees C per decade. The geographic variability in required thermal adaptation found in each model and emissions scenario suggests that coral reefs in some regions, like Micronesia and western Polynesia, may be particularly vulnerable to climate change. Advances in modelling and monitoring will refine the forecast for individual reefs, but this assessment concludes that the global prognosis is unlikely to change without an accelerated effort to stabilize atmospheric greenhouse gas concentrations.

A New Formulation of the Spectral Energy Budget of the Atmosphere, with Application to Two High-Resolution General Circulation Models

International audience

A model for assessing and correcting construction project health

Abstract Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

A collaborative model for learning and assessment of legal placements

This paper will report on the evaluation of a new undergraduate legal workplace unit, LWB421 Learning in Professional Practice. LWB421 was developed in response to the QUT’s strategic planning and a growing view that work experience is essential to developing the skills that law graduates need in order to be effective legal practitioners (Stuckey, 2007). Work integrated learning provides a context for students to develop their skills, to see the link between theory and practice and support students in making the transition from university to practice (Shirley, 2006). The literature in Australian legal education has given little consideration to the design of legal internship subjects (as distinct from legal clinic programs). Accordingly the design of placement subjects needs to be carefully considered to ensure alignment of learning objectives, learning tasks and assessment. Legal placements offer students the opportunity to develop their professional skills in practice, reflect on their own learning and job performance and take responsibility for their career development and planning. This paper will examine the literature relating to the design of placement subjects, particularly in a legal context. It will propose a collaborative model to facilitate learning and assessment of legal work placement subjects. The basis of the model is a negotiated learning contract between the student, workplace supervisor and academic supervisor. Finally the paper will evaluate the model in the context of LWB421. The evaluation will be based on data from surveys of students and supervisors and focus group sessions.

A model for assessing and correcting project Health

Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

Establishment of a mouse model of colitis and its use to evaluate the anti-inflammatory effects of two ghrelin peptides

Ghrelin is a gut-brain peptide hormone that induces appetite, stimulates the release of growth hormone, and has recently been shown to ameliorate inflammation. Recent studies have suggested that ghrelin may play a potential role in inflammation-related diseases such as inflammatory bowel diseases (IBD). A previous study with ghrelin in the TNBS mouse model of colitis demonstrated that ghrelin treatment decreased the clinical severity of colitis and inflammation and prevented the recurrence of disease. Ghrelin may be acting at the immunological and epithelial level as the ghrelin receptor (GHSR) is expressed by immune cells and intestinal epithelial cells. The current project investigated the effect of ghrelin in a different mouse model of colitis using dextran sodium sulphate (DSS) – a luminal toxin. Two molecular weight forms of DSS were used as they give differing effects (5kDa and 40kDa). Ghrelin treatment significantly improved clinical colitis scores (p=0.012) in the C57BL/6 mouse strain with colitis induced by 2% DSS (5kDa). Treatment with ghrelin suppressed colitis in the proximal colon as indicated by reduced accumulative histopathology scores (p=0.03). Whilst there was a trend toward reduced scores in the mid and distal colon in these mice this did not reach significance. Ghrelin did not affect histopathology scores in the 40kDa model. There was no significant effect on the number of regulatory T cells or TNF-α secretion from cultured lymph node cells from these mice. The discovery of C-terminal ghrelin peptides, for example, obestatin and the peptide derived from exon 4 deleted proghrelin (Δ4 preproghrelin peptide) have raised questions regarding their potential role in biological functions. The current project investigated the effect of Δ4 peptide in the DSS model of colitis however no significant suppression of colitis was observed. In vitro epithelial wound healing assays were also undertaken to determine the effect of ghrelin on intestinal epithelial cell migration. Ghrelin did not significantly improve wound healing in these assays. In conclusion, ghrelin treatment displays a mild anti-inflammatory effect in the 5kDa DSS model. The potential mechanisms behind this effect and the disparity between these results and those published previously will be discussed.