6 resultados para Numerical weather forecasting.

em Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España


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[ES] La energía eólica es una de las fuentes de energía renovable más importante hoy día con un continuo crecimiento a nivel mundial. España también ha apostado por las renovables y más concretamente por la energía eólica, materializándose con importantes instalaciones en gran parte de las comunidades autónomas entre ellas, Canarias. Con la realización de este trabajo se pretende estudiar el potencial eólico disponible en la zona donde se pretenda instalar o mantener un parque eólico, empleando para ello la ayuda de un supercomputador, el cual se encargará, por medio de un software de predicción meteorológica, que ayudarán en la decisión de dónde ubicar un parque eólico y, posteriormente, en la fase de explotación, predecir la potencia que un parque eólico inyectará en la red eléctrica con la antelación suficiente para que permita planificar las centrales de reserva de generación de energía tradicional u otras acciones que se consideren de interés. Durante el desarrollo del trabajo emplearemos el software “WRF” de predicción meteorológica. Esto generará un alto coste computacional y es por lo que proponemos realizar los cálculos empleando la ayuda de un supercomputador. Para concluir el trabajo mostraremos las características del supercomputador Atlante, situado en Las Palmas de Gran Canaria, y analizaremos el coste que le supondría a una empresa, la compra o el alquiler de un supercomputador.

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[EN] On 8-10 April 2007, several episodes of intense sea-breeze fronts were registered at the island of Fuerteventura (Canary Islands). The sea-breeze circulation was primary driven by daytime heating contrasts between land and the Atlantic Ocean during a period of weak trade winds. Numerical simulations of these events were carried out using the 3.1.1 version of the Weather Research and Forecasting (WRF) Model. Two different domains with 6.6-km and 2.2-km horizontal grid spacing and two sets with 27 and 51 vertical sigma levels were defined. The simulation was performed using two-way interactive nesting between the first and the second domain, using different land surface model parameterizations (Thermal diffusion, Noah LSM and RUC) for comparison. Initial conditions were provided by the NCAR Dataset analysis from April 2007, which were improved using surface and upper-air observations. The poster is focused on the 9 April episode.

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[EN] On 8-10 April 2007, several episodes of intense sea-breeze fronts were registered at the islands of Fuerteventura and Lanzarote (Canary Islands). The sea-breeze circulation was primary driven by daytime heating contrasts between land and the Atlantic Ocean during a period of weak trade winds. Numerical simulations of these events were carried out using the 3.1.1 version of the Weather Research and Forecasting (WRF-ARW) Model. Three different domains with 6.6-km, 2.2-km and 0.7-km horizontal grid spacing and two sets with 51 and 70 vertical sigma levels were defined. The simulation was performed using two-way interactive nesting between the first and the second domain, using different land surface model parameterizations (Thermal diffusion, Noah LSM and RUC) for comparison. Initial conditions were provided by the NCAR Dataset analysis from April 2007, which were improved using surface and upper-air observations. The poster is focused on the 10 April episode.

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[EN] This poster shows the first attempt to modelize the Gran Canaria Island wake, an obstacle with almost a conical shape (60 km diameter and about 2000 m height). The leeside circulation was modelized for two well-defined street vortex cases during June 2010 and March 2011. Numerical simulations of these events were carried out using the 3.1.1 version of the Weather Research and Forecasting (WRF-ARW) Model. Three different domains with 4.5-km, 1.5-km and 0.5-km horizontal grid spacing and 70 vertical sigma levels were defined. The simulations were performed using two-way interactive nesting between the first and the second and third domains, using different land surface model parameterizations (Thermal diffusion, Noah LSM and RUC) for comparison. Initial conditions were provided by the NCAR Dataset analysis from April 2007. The poster is focused on both episodes using NoahLSM parameterizations.

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[EN]Ensemble forecasting [1] is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in [2]. The wind _eld forecasting is based on a mass-consistent model and a log-linear wind pro_le using as input data the resulting forecast wind from Harmonie [3], a Non-Hydrostatic Dynamic model. The mass-consistent model parameters are estimated by using genetic algorithms [4]. The mesh is generated using the meccano method [5] and adapted to the geometry. The main source of uncertainties in this model is the parameter estimation and the in- trinsic uncertainties of the Harmonie Model…

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[EN]Ensemble forecasting is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in. The wind field forecasting is based on a mass-consistent model and a log-linear wind profile using as input data the resulting forecast wind from Harmonie, a Non-Hydrostatic Dynamic model used experimentally at AEMET with promising results. The mass-consistent model parameters are estimated by using genetic algorithms. The mesh is generated using the meccano method and adapted to the geometry…