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Multi-decadal variability in a centennial reconstruction of daily wind

机译:日风百年重建中的多年代际变化

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A wind clustering methodology capable of dynamically characterizing and long-term reconstructing daily surface wind series is introduced and tested for six meteorological towers at different wind farms in Spain, for the period 1871-2009. On this basis this paper provides for the first time a centennial surface wind reconstruction with a daily resolution without the need of numerical simulations. Thus, several soft-computing algorithms are developed, with public domain Sea Level Pressure (SLP) Reanalysis data as the only input. These algorithms are constructed by tackling an Euclidean distances' problem at the geostrophic speeds' space. Once the wind-independent classifications are obtained, the methodology is calibrated by linking the obtained classifications with observed wind data, thus allowing to estimate and characterize the daily surface wind speed and direction. A cross-validation is then performed in order to obtain several measures of goodness of the method, such as its wind speed estimation uncertainty in terms of Mean Absolute Error (MAE) and Pearson correlation (r) for both the wind module and vectorial values. Regarding previous approaches, this statistic downscaling shows an outstanding performance: Wind speed module estimates produce a MAE of 1.12 m/s(0.32 m/s) in some towers for a daily (monthly) scale, as r reaches values of 0.78 (daily scale) and 0.91 (monthly scale). The wind-independent classifications allowed to perform daily surface wind speed and rose reconstructions in time periods when no wind data are available, which constitutes the main goal of this work. Thus, a 140 year daily wind reconstruction is performed and analyzed for one tower located at central Iberia. There, significant low frequency variations are detected, as well as wind speed oscillations in the 20 y band. Remarkable changes are also identified over reconstructed decadal wind speed frequency distributions and wind rose. Since long-term wind measurements are rarely available at modern wind farm sites, such an analysis on centennial reconstructed wind series can represent an appropriate tool that places the last years of observed wind speed in a climatological perspective.
机译:引入了一种能够动态表征和长期重建日地面风序列的风聚方法,并在1871-2009年期间对西班牙不同风电场的六座气象塔进行了测试。在此基础上,本文首次提供了具有每日分辨率的百年地表风重建,而无需进行数值模拟。因此,开发了几种软计算算法,其中以公共领域海平面压力(SLP)重新分析数据为唯一输入。这些算法是通过在地转速度的空间上解决欧几里得距离的问题而构造的。一旦获得了与风无关的分类,就可以通过将获得的分类与观测到的风数据链接来对方法进行校准,从而可以估计和表征日地面风速和风向。然后执行交叉验证,以便获得该方法的几种良好度量,例如针对风模块和矢量值的根据平均绝对误差(MAE)和皮尔逊相关性(r)的风速估计不确定性。关于以前的方法,此统计数据的缩减显示了出色的性能:风速模块估计在某些塔中每日(每月)规模产生的MAE为1.12 m / s(0.32 m / s),因为r达到0.78(每日规模) )和0.91(月度规模)。与风力无关的分类允许在没有风力数据的时段内执行每日地表风速和玫瑰重建,这构成了这项工作的主要目标。因此,对位于伊比利亚中部的一座塔进行了140年的每日风能重建和分析。在那里,可以检测到明显的低频变化以及20 y波段的风速振荡。在重建的年代际风速频率分布和风向上升方面也发现了显着变化。由于在现代风电场现场很少进行长期风能测量,因此对百年重建风系列的分析可以代表一种合适的工具,可以将观测到的风速的最后几年置于气候学的角度。

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