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首页> 外文期刊>Climate dynamics >Characterization of the near surface wind speed distribution at global scale: ERA-Interim reanalysis and ECMWF seasonal forecasting system 4
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Characterization of the near surface wind speed distribution at global scale: ERA-Interim reanalysis and ECMWF seasonal forecasting system 4

机译:全球尺度近地表风速分布的特征:ERA中期再分析和ECMWF季节预报系统4

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The present developments in 10 m wind seasonal forecast products have lead to a growth in the number of studies analysing different aspects of both its predictability and applicability. However, there is still a lack of global studies analysing the statistical properties of the probability distribution of 10 m wind speed comparing the seasonal forecast systems with the widely used reanalysis products. To fill this gap we have studied the properties of the probability distributions of 10 m wind speed from the ERA-Interim reanalysis and the European Centre for Medium-Range Weather Forecasts System 4 seasonal forecast system. We have focused on two seasons, JJA and DJF, considering both their interannual and intraseasonal variability. The 10 m wind speed distribution has been characterized in terms of the four main moments of the probability distribution (mean, standard deviation, skewness and kurtosis). We have also computed the coefficient of variation to identify the regions with the higher wind variability and the Shapiro-Wilks goodness of fit test to assess their normality. This set of parameters is important to provide useful climate information in wind energy decision-making processes that use simple assumptions of the wind speed frequency distribution to properly estimate the wind energy potential. Besides, this study also illustrates where the discrepancies of the distributions of the seasonal predictions and the reference dataset are higher and, thus, which might need special attention from a bias adjustment perspective.
机译:10 m风季预报产品的最新发展导致分析其可预测性和适用性不同方面的研究数量不断增加。但是,仍然缺乏全球性的研究来分析10 m风速的概率分布的统计特性,并将季节预报系统与广泛使用的再分析产品进行比较。为了填补这一空白,我们通过ERA-Interim再分析和欧洲中距离天气预报系统4的季节性预报系统研究了10 m风速概率分布的特性。考虑到JJA和DJF的年际和季节内变异性,我们将重点放在两个季节。根据概率分布的四个主要矩(均值,标准差,偏度和峰度)对10 m风速分布进行了表征。我们还计算了变异系数,以识别风变率较高的区域,并通过Shapiro-Wilks拟合优度检验来评估其正态性。这组参数对于在风能决策过程中提供有用的气候信息非常重要,该过程使用对风速频率分布的简单假设来正确估算风能潜力。此外,本研究还说明了季节预测和参考数据集的分布差异较高的地方,因此,从偏差调整的角度可能需要特别注意。

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