标题： 美国各地未来气候下风速和风向的站点统计联合评估 显示英文标题

标题： Station-wise statistical joint assessment of wind speed and direction under future climates across the United States

摘要： 本研究开发了一种统计条件方法，用于评估气候模型在风速和风向方面的性能，并在代表性浓度路径8.5情景下，对美国大陆内陆和沿海地区的未来变化进行预测。 所提出的条件方法通过描述风速和风向联合分布的完整范围的变化，扩展了现有研究的范围。 使用两种统计方法估计方向风速分布：威布尔分布回归模型和分位数回归模型，这两种方法都对其结果的方向分布施加了循环约束。 研究了与不同气候模型和模型内部变异性相关的投影不确定性，并与气候变化信号进行比较，以量化未来投影的统计显著性。 特别是，这项工作将内部变异性概念扩展到标准差和高分位数，以评估其相对于投影变化的相对幅度。 评估结果表明，所研究的气候模型在内陆和沿海地区都能合理地捕捉历史风速、风向及其依赖关系。 在未来，大多数地区在冬季和夏季的平均风速均无显著变化，尽管某些地区在冬季的标准差和95百分位数的变化显示出一些稳健的变化。 所提出的条件方法能够表征方向风速分布，为速度和方向的联合评估提供了额外的见解。 显示英文摘要

摘要： This study develops a statistical conditional approach to evaluate climate model performance in wind speed and direction and to project their future changes under the representative concentration pathway 8.5 scenario over inland and offshore locations across the Continental United States. The proposed conditional approach extends the scope of existing studies by characterizing the changes of the full range of the joint wind speed and direction distribution. Directional wind speed distributions are estimated using two statistical methods: a Weibull distributional regression model and a quantile regression model, both of which enforce the circular constraint to their resulting estimates of directional distributions. Projected uncertainties associated with different climate models and model internal variability are investigated and compared with the climate change signal to quantify the statistical significance of the future projections. In particular this work extends the concept of internal variability to the standard deviation and high quantiles to assess the relative magnitudes to their projected changes. The evaluation results show that the studied climate model capture both historical wind speed, wind direction, and their dependencies reasonably well over both inland and offshore locations. In the future, most of the locations show no significant changes in mean wind speeds in both winter and summer, although the changes in standard deviation and 95th-quantile show some robust changes over certain locations in winter. The proposed conditional approach enables the characterization of the directional wind speed distributions, which offers additional insights for the joint assessment of speed and direction.