A Wind Field Reconstruction from Numerical Weather Prediction Data Based on a Meteo Particle Model

E. Bucchignani
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Abstract

In the present work, a methodology for wind field reconstruction based on the Meteo Particle model (MPM) from numerical weather prediction (NWP) data is presented. The development of specific wind forecast services is a challenging research topic, in particular for what concerns the availability of accurate local weather forecasts in highly populated areas. Currently, even if NWP limited area models (LAMs) are run at a spatial resolution of about 1 km, this level of information is not sufficient for many applications; for example, to support drone operation in urban contexts. The coupling of the MPM with the NWP limited area model COSMO has been implemented in such a way that the MPM reads the NWP output over a selected area and provides wind values for the generic point considered for the investigation. The numerical results obtained reveal the good behavior of the method in reproducing the general trend of the wind speed, as also confirmed by the power spectra analysis. The MPM is able to step over the intrinsic limitations of the NWP model in terms of the spatial and temporal resolution, even if the MPM inherits the bias that inevitably affects the COSMO output.
基于气象粒子模型的数值天气预报数据风场重建技术
本研究介绍了一种基于气象粒子模型(MPM)从数值天气预报(NWP)数据重建风场的方法。开发特定的风预报服务是一个具有挑战性的研究课题,尤其是在人口高度密集地区提供准确的本地天气预报。目前,即使 NWP 有限区域模型(LAM)的空间分辨率约为 1 公里,这一信息水平对于许多应用来说也是不够的,例如,在城市环境中支持无人机操作。MPM 与 NWP 有限区域模型 COSMO 的耦合是这样实现的:MPM 读取选定区域的 NWP 输出,并为调查考虑的通用点提供风值。数值结果表明,该方法能够很好地再现风速的总体趋势,功率谱分析也证实了这一点。尽管 MPM 继承了不可避免地影响 COSMO 输出的偏差,但 MPM 能够克服 NWP 模型在空间和时间分辨率方面的固有限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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