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Wind Forecasting Based on the HARMONIE Model and Adaptive Finite Elements

机译：基于HARMONIE模型和自适应有限元的风力预报

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摘要

In this paper, we introduce a new method for wind field forecasting over complex terrain. The main idea is to use the predictions of the HARMONIE meso-scale model as the input data for an adaptive finite element mass-consistent wind model. The HARMONIE results (obtained with a maximum resolution of about 1 km) are refined in a local scale (about a few metres). An interface between both models is implemented in such a way that the initial wind field is obtained by a suitable interpolation of the HARMONIE results. Genetic algorithms are used to calibrate some parameters of the local wind field model in accordance to the HARMONIE data. In addition, measured data are considered to improve the reliability of the simulations. An automatic tetrahedral mesh generator, based on the meccano method, is applied to adapt the discretization to complex terrains. The main characteristic of the framework is a minimal user intervention. The final goal is to validate our model in several realistic applications on Gran Canaria island, Spain, with some experimental data obtained by the AEMET in their meteorological stations. The source code of the mass-consistent wind model is available online at http://www.dca.iusiani.ulpgc.es/Wind3D/.
机译：本文介绍了一种在复杂地形上进行风场预测的新方法。主要思想是将HARMONIE中尺度模型的预测用作自适应有限元质量一致风模型的输入数据。 HARMONIE结果（以约1 km的最大分辨率获得）在局部范围（约几米）内得到改进。两个模型之间的接口以这样的方式实现：通过对HARMONIE结果进行适当的插值获得初始风场。遗传算法用于根据HARMONIE数据校准局部风场模型的某些参数。另外，考虑了测量数据以提高模拟的可靠性。基于meccano方法的自动四面体网格生成器用于使离散化适应复杂的地形。该框架的主要特征是最少的用户干预。最终目标是通过AEMET在其气象站获得的一些实验数据，在西班牙大加那利岛上的一些实际应用中验证我们的模型。可在http://www.dca.iusiani.ulpgc.es/Wind3D/在线获得质量一致风模型的源代码。

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