Probability distributions of land surface wind speeds over North America
Probability distributions of land surface wind speeds over North America
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DOI：
10.1029/2008jd010708
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发表时间：
2010-02
影响因子：
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通讯作者：
Yanping He;A. Monahan;Colin G. Jones;A. Dai;S. Biner;D. Caya;K. Winger
中科院分区：
文献类型：
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作者：
Yanping He;A. Monahan;Colin G. Jones;A. Dai;S. Biner;D. Caya;K. Winger
[1] 了解表面风速 (SWS) 的概率分布对于表面通量估计、风功率估计和风风险评估至关重要。二参数威布尔分布是 SWS 最广泛使用的经验分布。本研究考虑了 1979 年至 1999 年期间北美 720 个气象站每 3 小时观测的概率密度函数 (PDF)。 SWS 的 PDF 按季节、一天中的时间和地表类型进行分类。威布尔 PDF 的特征在于平均值、标准差和偏度之间的特定关系。虽然观察到的白天 SWS PDF 的矩被发现围绕此威布尔关系崩溃，但观察到的夜间 PDF 具有更广泛的值范围，并且在粗糙表面上比威布尔 PDF 更偏斜。理想化模型表明，在稳定层结条件下，SWS偏度随表面浮力通量均值和标准差的变化率远大于不稳定层结条件下的变化率。这一结果表明，表面浮力通量在 SWS PDF 的日变化中起着重要作用。两个全球再分析产品（ERA-40 和 NCEP-NCAR）和三个区域气候模型 (RCM)（罗斯比中心大气模型版本 3 (RCA3)、全球环境多尺度模型 (GEM-LAM) 的有限区域版本和加拿大区域气候模型版本 4 (CRCM4)）均具有较小偏差的夜间 PDF 和更窄的白天和夜间正常风速范围。其中，两个 RCM 捕获了不同土地覆盖类型之间观测到的 SWS 差异，并且只有一个 RCM 产生了观测到的 SWS PDF 季节性峰值。
[1] Knowledge of the probability distributions of surface wind speeds (SWS) is essential for surface flux estimation, wind power estimation, and wind risk assessments. The two-parameter Weibull distribution is the most widely used empirical distribution for SWS. This study considers the probability density function (PDF) of 3-hourly observations from 720 weather stations over North America for the period 1979–1999. The PDF of SWS is classified by season, time of day, and land surface type. The Weibull PDF is characterized by a particular relationship between the mean, standard deviation, and skewness. While the moments of the observed daytime SWS PDF are found to collapse around this Weibull relationship, the observed nighttime PDF has a broader range of values and is significantly more skewed than the Weibull PDF over rough surfaces. An idealized model shows that SWS skewness has a much greater rate of change with both the mean and standard deviation of surface buoyancy flux under conditions of stable stratification than that of unstable stratification. This result suggests that surface buoyancy flux plays an important role in generating diurnal variation of SWS PDF. Two global reanalyses products (ERA-40 and NCEP-NCAR) and three regional climate models (RCMs) (Rossby Centre Atmospheric Model version 3 (RCA3), limited area version of Global Environmental Multiscale Model (GEM-LAM), and Canadian Regional Climate Model, version 4 (CRCM4)) all have a less skewed nighttime PDF and a more narrow range of the normal wind speed during day and night. Among them, two of the RCMs capture the observed SWS differences across different land cover types, and only one of the RCMs produces the observed seasonal peak of SWS PDF.