修正WRF次网格地形方案及其对风速模拟的影响
|
摘要
复杂地形区域风场模拟的准确率一直是风能研究领域的难点和重点。WRF模式是目前风能评估领域应用最广泛的天气数值模式之一,但该模式在复杂地形区域存在对平原、山谷风速高估且对山顶风速低估的系统性误差,并有研究建立次网格地形方案以订正误差。而次网格地形方案在不同水平分辨率下常出现错误的修正结果,该文基于高精度地形高程数据分析了方案失效的主要原因,发现其方程组中判断山体形态特征的阈值-20在过低和过高水平分辨率下均失去参考性。针对这一原因.将方案中影响关键参数C_t的地形高度算子与模式水平分辨率进行拟合,形成地形高度算子与水平分辨率相依赖的线性关系,获得不同分辨率下更适合的山体形态阈值。通过与自动气象站10 m风速对比分析了修正前后WRF对低层风速的模拟效果,结果显示:修正后的次网格地形方案能够分别在较低和较高分辨率下,部分矫正原方案错误的订正结果,使低层风速模拟更接近实况。修正后的次网格地形方案可为复杂地形区域开展高分辨率风场模拟提供参考。
Due to the limited representation of observation over complex terrain, high resolution model becomes a favorable tool. Fine numerical simulation of wind field is quite important for micro-siting wind farms and wind energy resources assessment, especially in the complex terrain area. The accuracy of low-layer wind simulation over mountain area is one of the difficulties and key points in the field of wind energy research.The state-of-the-art WRF(Weather Research and Forecasting) model is one of the most widely used mesoscale numerical weather models for wind energy assessment in recent years. However, effects of subgrid-scale topographic shape on surface wind field are not considered. With the new WRF version 3. 4. 1, a sub-grid-scale terrain parameterization scheme named Jimenez scheme is added into the YSU(Yonsei University) planet boundary layer parameterization scheme. The Jimenez scheme is designed aiming to reduce the systematic error of wind speed overestimation over valleys or plains and underestimation over hills conversely. However, correction effects of original WRF simulated 10 m wind speed by Jimenez scheme show great differences under different horizontal resolutions, particularly when over high hills. A series of sensitive numerical experiments are carried out under windy days for the Taihang Mountains in the west of Beijing-Tianjin-Hebei area. The main purpose of these experiments is to address some of issues regarding Jimenez scheme and try to solve the existing problems by establishing a relationship between the key topographic parameter C_t and the model grid spacing(dx/dy) to fit different numerical simulation for high resolution based on secondly SRTM topographic dataset. The simulated 10 m wind speed results of WRF without Jimenez scheme, with original Jimenez scheme and modified Jimenez scheme version are compared with observations of 3 automatic weather stations during the MOUNTAOM(MOUNtain Terrain Atmospheric Observations and Modeling) campaign which is prepared for 2022 winter Olympic Games. Results show that the modified Jimenez scheme can partially correct the error of the original Jimenez scheme at lower and higher resolutions. The simulated 10 m wind speed near the ground by modified version is closer to the actual condition. The correction method for Jimenez sub-grid-scale terrain scheme can provide reference for high resolution wind simulations over complex terrain and help users to obtain more detailed information on the surface wind field for wind energy related researches and applications.
Due to the limited representation of observation over complex terrain, high resolution model becomes a favorable tool. Fine numerical simulation of wind field is quite important for micro-siting wind farms and wind energy resources assessment, especially in the complex terrain area. The accuracy of low-layer wind simulation over mountain area is one of the difficulties and key points in the field of wind energy research.The state-of-the-art WRF(Weather Research and Forecasting) model is one of the most widely used mesoscale numerical weather models for wind energy assessment in recent years. However, effects of subgrid-scale topographic shape on surface wind field are not considered. With the new WRF version 3. 4. 1, a sub-grid-scale terrain parameterization scheme named Jimenez scheme is added into the YSU(Yonsei University) planet boundary layer parameterization scheme. The Jimenez scheme is designed aiming to reduce the systematic error of wind speed overestimation over valleys or plains and underestimation over hills conversely. However, correction effects of original WRF simulated 10 m wind speed by Jimenez scheme show great differences under different horizontal resolutions, particularly when over high hills. A series of sensitive numerical experiments are carried out under windy days for the Taihang Mountains in the west of Beijing-Tianjin-Hebei area. The main purpose of these experiments is to address some of issues regarding Jimenez scheme and try to solve the existing problems by establishing a relationship between the key topographic parameter C_t and the model grid spacing(dx/dy) to fit different numerical simulation for high resolution based on secondly SRTM topographic dataset. The simulated 10 m wind speed results of WRF without Jimenez scheme, with original Jimenez scheme and modified Jimenez scheme version are compared with observations of 3 automatic weather stations during the MOUNTAOM(MOUNtain Terrain Atmospheric Observations and Modeling) campaign which is prepared for 2022 winter Olympic Games. Results show that the modified Jimenez scheme can partially correct the error of the original Jimenez scheme at lower and higher resolutions. The simulated 10 m wind speed near the ground by modified version is closer to the actual condition. The correction method for Jimenez sub-grid-scale terrain scheme can provide reference for high resolution wind simulations over complex terrain and help users to obtain more detailed information on the surface wind field for wind energy related researches and applications.
引文
[1]朱蓉,何晓凤,周朱卫,等.风能资源评估技术进展及中国发展现状//全国工业空气动力学学术会议,2009:66-78.
[2]朱蓉,何晓凤,周荣卫,等.区域风能资源的数值模拟评估方法.风能,2010(4):52-56.
[3]刘郁珏,李军,胡非,等.一种考虑海拔高度的风速测量相关推测法.应用气象学报,2013,24(1):109-116.
[4] Whiteman C. Mountain meteorology:Fundamentals and applications. Mountain Research&Development, 2000,21(2):200-201.
[5]李磊,张立杰,张宁,等.FLUENT在复杂地形风场精细模拟中的应用研究.高原气象,2010.29(3):621-628.
[6]穆海振,徐家良,柯晓新,等.高分辨率数值模式在风能资源评估中的应用初探.应用气象学报,2006,17(2):152-159.
[7]许杨,陈正洪,杨宏青,等.风电场风电功率短期预报方法比较.应用气象学报,2013,24(5):625-630.
[8] Skamarock W,Klemp J. A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. Journal of Computational Physics, 2008, 227(7):3465-3485.
[9]徐晶晶,胡非,肖子牛,等.风能模式预报的相似误差订正.应用气象学报,2013,24(6):731-740.
[10]方艳莹,徐海明,朱蓉,等.基于WRF和CFD软件结合的风能资源数值模拟试验研究.气象,2012,38(11):1378-1389.
[11]苗世光,孙桂平,马艳,等.青岛奥帆赛高分辨率数值模式系统研制与应用.应用气象学报,2009,20(3):370-379.
[12]杨薇,苗崚峰,谈哲敏.太湖地区湖陆风对雷暴过程影响的数值模拟.应用气象学报,2014,25(1):59-70.
[13]王麟.WRF模式在云南省风能资源评估中的适用性研究.昆明:云南大学,2014.
[14]刘桂艳,高山红,王永明,等.台风外围下沉区大气波导成因的数值模拟.应用气象学报,2012,23(1):77-88.
[15]徐敬,马志强,赵秀娟,等.边界层方案对华北低层O_3垂直分布模拟的影响.应用气象学报,2015,26(5):567-577.
[16]马文通,朱蓉,李泽椿,等.基于CFD动力降尺度的复杂地形风电场风电功率短期预测方法研究.气象学报,2016,74(1):89-102.
[17] Wyngaard J C. Toward numerical modeling in the"terra incognita". J Atmos Sci,2004,61:1816-1826.
[18] llenckes P,Knaut A,Obermuller F, et al. The benefit of longterm high resolution wind data for electricity system analysis.Energy,2018,143:934-942.
[19] Cheng W,Steenburgh W. Evaluation of surface sensible weather forecasts by the WRF and the eta models over the Western United States. Wea Forecasting,2015,20(5):812-821.
[20] Roux G,Liu Y,Monache L,et al. Verification of IIigh-resolution WRF-RTFDDA Surface Forcasts over Mountains and Plains. 10th WRF Users'Workshop,2009:20-23.
[21] Mass C,Ovens D. WRF Model Physcis:Problems,Solutions,and a New Paradigm for Progress//Preprints,2010 WRF Users'Workshop,2010.
[22] Mass C. Improved Subgrid Drag of Hyper PBL Vertical Resolution? Dealing with the Stable PBL Problems in WRF. WRF Users'Workshop,2012.
[23] Mass C. Fixing WRF's IIigh Speed Wind Bias:A New Subgrid Scale Drag Parameterization and the Role of Detailed Verification//Preprints, 24th Conf on Weather and Forcasting/20th Conf on Numerical Weather Prediction. 2011.
[24] Shimada S,Ohsawa T. Accuracy and characteristics of offshore wind speeds simulated by WRF. Scientific Online Letters on the Atmosphere Sola,2011,7(1):21-24.
[25] Jimenez P,Dudhia J. Improving the representation of resolved and unresolved topographic effects on surface wind in the WRF model. Journal of Applied Meteorology&Climatology,2012,51(2):300-316.
[26] Jimenez P,Dudhia J. On the ability of the WRF model to reproduce the surface wind direction over complex terrain.Journal of Applied Meteorology&Climatology,2013,52(7):1610-1617.
[27]郑亦佳,刘树华,缪育聪,等.YSU边界层参数化方案中不同地形订正方法对地面风速及温度模拟的影响.地球物理学报,2016,59(3):803-815.
[28]杨鹏武,王学锋,王麟,等.WRF_TopoWind模式对中国低纬高原高山风速模拟的适用性研究.云南大学学报(自然科学版),2016,38(5):766-772.
[29]马晨晨,余晔,何建军,等,次网格地形参数化对WRF模式在复杂地形区风场模拟的影响.干旱气象,2016,34(1):96-105.
[30]张亦洲,苗世光,李青春,等.北京城市下垫面对雾影响的数值模拟研究.地球物理学报,2017.60(1):22-36.
[31] IIong S Y,Noh Y,Dudhia J. A new vertical diffusion packagewith an explicit treatment of entrainment processes. Mon Wea Rev,2006,134:2318-2341.
[2]朱蓉,何晓凤,周荣卫,等.区域风能资源的数值模拟评估方法.风能,2010(4):52-56.
[3]刘郁珏,李军,胡非,等.一种考虑海拔高度的风速测量相关推测法.应用气象学报,2013,24(1):109-116.
[4] Whiteman C. Mountain meteorology:Fundamentals and applications. Mountain Research&Development, 2000,21(2):200-201.
[5]李磊,张立杰,张宁,等.FLUENT在复杂地形风场精细模拟中的应用研究.高原气象,2010.29(3):621-628.
[6]穆海振,徐家良,柯晓新,等.高分辨率数值模式在风能资源评估中的应用初探.应用气象学报,2006,17(2):152-159.
[7]许杨,陈正洪,杨宏青,等.风电场风电功率短期预报方法比较.应用气象学报,2013,24(5):625-630.
[8] Skamarock W,Klemp J. A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. Journal of Computational Physics, 2008, 227(7):3465-3485.
[9]徐晶晶,胡非,肖子牛,等.风能模式预报的相似误差订正.应用气象学报,2013,24(6):731-740.
[10]方艳莹,徐海明,朱蓉,等.基于WRF和CFD软件结合的风能资源数值模拟试验研究.气象,2012,38(11):1378-1389.
[11]苗世光,孙桂平,马艳,等.青岛奥帆赛高分辨率数值模式系统研制与应用.应用气象学报,2009,20(3):370-379.
[12]杨薇,苗崚峰,谈哲敏.太湖地区湖陆风对雷暴过程影响的数值模拟.应用气象学报,2014,25(1):59-70.
[13]王麟.WRF模式在云南省风能资源评估中的适用性研究.昆明:云南大学,2014.
[14]刘桂艳,高山红,王永明,等.台风外围下沉区大气波导成因的数值模拟.应用气象学报,2012,23(1):77-88.
[15]徐敬,马志强,赵秀娟,等.边界层方案对华北低层O_3垂直分布模拟的影响.应用气象学报,2015,26(5):567-577.
[16]马文通,朱蓉,李泽椿,等.基于CFD动力降尺度的复杂地形风电场风电功率短期预测方法研究.气象学报,2016,74(1):89-102.
[17] Wyngaard J C. Toward numerical modeling in the"terra incognita". J Atmos Sci,2004,61:1816-1826.
[18] llenckes P,Knaut A,Obermuller F, et al. The benefit of longterm high resolution wind data for electricity system analysis.Energy,2018,143:934-942.
[19] Cheng W,Steenburgh W. Evaluation of surface sensible weather forecasts by the WRF and the eta models over the Western United States. Wea Forecasting,2015,20(5):812-821.
[20] Roux G,Liu Y,Monache L,et al. Verification of IIigh-resolution WRF-RTFDDA Surface Forcasts over Mountains and Plains. 10th WRF Users'Workshop,2009:20-23.
[21] Mass C,Ovens D. WRF Model Physcis:Problems,Solutions,and a New Paradigm for Progress//Preprints,2010 WRF Users'Workshop,2010.
[22] Mass C. Improved Subgrid Drag of Hyper PBL Vertical Resolution? Dealing with the Stable PBL Problems in WRF. WRF Users'Workshop,2012.
[23] Mass C. Fixing WRF's IIigh Speed Wind Bias:A New Subgrid Scale Drag Parameterization and the Role of Detailed Verification//Preprints, 24th Conf on Weather and Forcasting/20th Conf on Numerical Weather Prediction. 2011.
[24] Shimada S,Ohsawa T. Accuracy and characteristics of offshore wind speeds simulated by WRF. Scientific Online Letters on the Atmosphere Sola,2011,7(1):21-24.
[25] Jimenez P,Dudhia J. Improving the representation of resolved and unresolved topographic effects on surface wind in the WRF model. Journal of Applied Meteorology&Climatology,2012,51(2):300-316.
[26] Jimenez P,Dudhia J. On the ability of the WRF model to reproduce the surface wind direction over complex terrain.Journal of Applied Meteorology&Climatology,2013,52(7):1610-1617.
[27]郑亦佳,刘树华,缪育聪,等.YSU边界层参数化方案中不同地形订正方法对地面风速及温度模拟的影响.地球物理学报,2016,59(3):803-815.
[28]杨鹏武,王学锋,王麟,等.WRF_TopoWind模式对中国低纬高原高山风速模拟的适用性研究.云南大学学报(自然科学版),2016,38(5):766-772.
[29]马晨晨,余晔,何建军,等,次网格地形参数化对WRF模式在复杂地形区风场模拟的影响.干旱气象,2016,34(1):96-105.
[30]张亦洲,苗世光,李青春,等.北京城市下垫面对雾影响的数值模拟研究.地球物理学报,2017.60(1):22-36.
[31] IIong S Y,Noh Y,Dudhia J. A new vertical diffusion packagewith an explicit treatment of entrainment processes. Mon Wea Rev,2006,134:2318-2341.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |