Response of the West African Monsoon to the Madden–Julian Oscillation

Observations show that rainfall over West Africa is influenced by the Madden-Julian Oscillation (MJO). A number of mechanisms have been suggested: 1) forcing by equatorial waves; 2) enhanced monsoon moisture supply; and 3) increased African easterly wave (AEW) activity. However, previous observational studies are not able to unambiguously distinguish between cause and effect. Carefully designed model experiments are used to assess these mechanisms. Intraseasonal convective anomalies over West Africa during the summer monsoon season are simulated in an atmosphere-only global circulation model as a response to imposed sea surface temperature (SST) anomalies associated with the MJO over the equatorial warm pool region. 1) Negative SST anomalies stabilize the atmosphere leading to locally reduced convection. The reduced convection leads to negative midtropospheric latent heating anomalies that force dry equatorial waves. These waves propagate eastward (Kelvin wave) and westward (Rossby wave), reaching Africa approximately 10 days later. The associated negative temperature anomalies act to destabilize the atmosphere, resulting in enhanced monsoon convection over West and central Africa. The Rossby waves are found to be the most important component, with associated westward-propagating convective anomalies over West Africa. The eastward-propagating equatorial Kelvin wave also efficiently triggers convection over the eastern Pacific and Central America, consistent with observations. 2) An increase in boundary layer moisture is found to occur as a result of the forced convective anomalies over West Africa rather than a cause. 3) Increased shear on the African easterly jet, leading to increased AEW activity, is also found to occur as a result of the forced convective anomalies in the model

Adjustment of model parameters to estimate distribution transformers remaining lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.Fil: Jimenez, Victor Adrian. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Will, Adrian L. E.. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Gotay Sardiñas, Jorge. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Rodriguez, Sebastian Alberto. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentin

UNDERGRADUATE EDUCATION IN DEPARTMENTS OF AGRICULTURAL ECONOMICS IN THE SOUTH: STATUS, CHALLENGES, AND OPPORTUNITIES

Teaching/Communication/Extension/Profession,