The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(Ca...The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.展开更多
复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流...复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流体动力学(computational fluid dynamics,CFD)技术,构建一套WRF-CFD模式耦合的复杂地形风电场非定常仿真方法。以国际经典案例Askervein山和Bolund岛为验证对象,研究复杂地形流场中平均风速和湍流强度的分布特征,并简要分析复杂地形中风力机布置策略。结果表明,基于WRF-CFD模式的数值模拟结果与实验观测值有较好的一致性,且优于中尺度数值模拟结果,在选取的特征点位置,风速绝对误差均在2 m/s以内。结果可为风力机的设计、布局、载荷评估及风电场运行控制提供一定参考。展开更多
作为天气系统的主要组成部分,三维云仿真在军事、航空等领域都起着重要作用.目前主流的边界体积层次结构(Bounding Volume Hierarchy,BVH)在处理形状不均匀且体积较大的云时存在渲染效率低下的问题,为此提出一种基于优化BVH算法的云产...作为天气系统的主要组成部分,三维云仿真在军事、航空等领域都起着重要作用.目前主流的边界体积层次结构(Bounding Volume Hierarchy,BVH)在处理形状不均匀且体积较大的云时存在渲染效率低下的问题,为此提出一种基于优化BVH算法的云产品渲染方法.将WRF(Weather Research and Forecasting,天气研究与预报)模型网格点中的数据作为云基元,利用Z-order Hilbert曲线对其进行空间排序,结合云基元密度优化BVH算法,提高计算效率.提出ONS(Overlapping Node Sets,重叠节点结构)降低数据存取耗时.优化BVH算法能够减少不必要的光线和三角形面之间的相交测试次数,并解决边界体无效重叠问题.仿真实验显示,SAH(Surface Area Heuristic,表面积启发式)成本较同类最优算法可提升15.6%,EPO(Effective Partial Overlap,有效重叠部分)可提升10%,构建时间减少100%以上,在任意云场景中优化BVH算法的计算效率较同类算法都有显著提高,表明其能实现WRF云产品的快速渲染.展开更多
为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Envi...为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)的FNL全球再分析资料(Final Operational Global Analysis)、先进星载热发射和反射辐射仪全球数字高程模型以及兰州中川机场的实况观测资料,采用中尺度数值天气预报模式(Weather Research and Forecasting Model,WRF)、WRF结合计算流体动力学(Computational Fluid Dynamics,CFD)方法、长短期神经网络(Long Short-Term Memory,LSTM)方法,对2021年4月15-16日兰州中川机场的两次风切变过程进行模拟分析。结果表明:(1)在小于1 km的网格中使用大涡模拟,WRF模式在单个站点风速模拟任务中表现更好,但在近地面水平风场风速模拟效果上,不如WRF模式结合计算流体力学模型方案;(2)对于飞机降落过程中遭遇的两次低空风切变的模拟,WRF-LES和WRF-CFD两种模式都可以模拟出第一次低空风切变,而第二次受传入模式的WRF风速数据值较小的影响,两种模式风速差都没有达到阈值,需要在后续工作中进一步验证;(3)低风速条件(6 m·s^(-1))下,基于LSTM的单变量风速预测模型平均绝对误差基本维持在0.59 m·s^(-1),能较好地把握不同地形与环流背景条件下风速变化的非线性关系,虽然受到WRF误差和观测要素不全的限制,多变量风速预测能在保证平均绝对百分比误差小于6.60%的情况下,以更高的计算效率和泛化能力实现风速预测。本文不仅验证了WRF-CFD和WRF-LES耦合方案在风场和低空风切变预报中的差异,还探讨了基于LSTM的风速预测的可行性和准确性,期望为提高风场模拟精度,缩短精细风场模拟时间提供新的视角和方法。展开更多
基金National Public Benefit Research Foundation of China (2008416048GYHY201006035)
文摘The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.
文摘复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流体动力学(computational fluid dynamics,CFD)技术,构建一套WRF-CFD模式耦合的复杂地形风电场非定常仿真方法。以国际经典案例Askervein山和Bolund岛为验证对象,研究复杂地形流场中平均风速和湍流强度的分布特征,并简要分析复杂地形中风力机布置策略。结果表明,基于WRF-CFD模式的数值模拟结果与实验观测值有较好的一致性,且优于中尺度数值模拟结果,在选取的特征点位置,风速绝对误差均在2 m/s以内。结果可为风力机的设计、布局、载荷评估及风电场运行控制提供一定参考。
文摘作为天气系统的主要组成部分,三维云仿真在军事、航空等领域都起着重要作用.目前主流的边界体积层次结构(Bounding Volume Hierarchy,BVH)在处理形状不均匀且体积较大的云时存在渲染效率低下的问题,为此提出一种基于优化BVH算法的云产品渲染方法.将WRF(Weather Research and Forecasting,天气研究与预报)模型网格点中的数据作为云基元,利用Z-order Hilbert曲线对其进行空间排序,结合云基元密度优化BVH算法,提高计算效率.提出ONS(Overlapping Node Sets,重叠节点结构)降低数据存取耗时.优化BVH算法能够减少不必要的光线和三角形面之间的相交测试次数,并解决边界体无效重叠问题.仿真实验显示,SAH(Surface Area Heuristic,表面积启发式)成本较同类最优算法可提升15.6%,EPO(Effective Partial Overlap,有效重叠部分)可提升10%,构建时间减少100%以上,在任意云场景中优化BVH算法的计算效率较同类算法都有显著提高,表明其能实现WRF云产品的快速渲染.
文摘为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)的FNL全球再分析资料(Final Operational Global Analysis)、先进星载热发射和反射辐射仪全球数字高程模型以及兰州中川机场的实况观测资料,采用中尺度数值天气预报模式(Weather Research and Forecasting Model,WRF)、WRF结合计算流体动力学(Computational Fluid Dynamics,CFD)方法、长短期神经网络(Long Short-Term Memory,LSTM)方法,对2021年4月15-16日兰州中川机场的两次风切变过程进行模拟分析。结果表明:(1)在小于1 km的网格中使用大涡模拟,WRF模式在单个站点风速模拟任务中表现更好,但在近地面水平风场风速模拟效果上,不如WRF模式结合计算流体力学模型方案;(2)对于飞机降落过程中遭遇的两次低空风切变的模拟,WRF-LES和WRF-CFD两种模式都可以模拟出第一次低空风切变,而第二次受传入模式的WRF风速数据值较小的影响,两种模式风速差都没有达到阈值,需要在后续工作中进一步验证;(3)低风速条件(6 m·s^(-1))下,基于LSTM的单变量风速预测模型平均绝对误差基本维持在0.59 m·s^(-1),能较好地把握不同地形与环流背景条件下风速变化的非线性关系,虽然受到WRF误差和观测要素不全的限制,多变量风速预测能在保证平均绝对百分比误差小于6.60%的情况下,以更高的计算效率和泛化能力实现风速预测。本文不仅验证了WRF-CFD和WRF-LES耦合方案在风场和低空风切变预报中的差异,还探讨了基于LSTM的风速预测的可行性和准确性,期望为提高风场模拟精度,缩短精细风场模拟时间提供新的视角和方法。
