Near-Surface Wind Simulation over Acrid Lakeshore Area and Sensitivity Studies using the WRF-LES

  • SUN Xuejin ,
  • LI Yan ,
  • ZHANG Yanhong ,
  • NING Hui ,
  • TANG Jing ,
  • WEN Yuanhong ,
  • MIAO Qingjian
Expand
  • College of Meteorology and Oceanography, People's Liberation Army of China University of Science and Technology, Nanjing 211101, China;Northwest Institute of Nuclear Technology, Xi'an 710024, China

Received date: 2015-12-18

  Online published: 2017-06-28

Abstract

Because of the relative larger mesh-grids, meso-scale atmospheric models cannot fully capture the spatial and temporal variability of near-surface wind fields over complex terrain, whereas the large turbulence-eddy resolving LES is a more promising model to account for this challenge. This paper performs a real-case near-surface wind simulation test over acrid lakeshore area close to Bosteng Lake in Xinjiang province utilizing the WRF-LES model with six nested domains. The simulation period is 28 hours and the model results were verified and analyzed against in-situ observations for one day. To assess the sensitivity of model results to local land-surface characteristics, three sensitivity tests were conducted by varying parameters such as the terrain resolution, soil-moist and surface roughness. For one sensitivity test, two digital elevation datasets were used, one is ASTER GDEM with 1 sec resolution and the other is MODIS with 30 sec resolution. For the other two sensitivity tests, disturbance factor with values 0. 4 through 2. 8 was used respectively to change the properties of land-surface. The test results demonstrate that the WRF-LES is more capable to regenerate the near-surface wind than meso-scale simulations in small-scale region with complex terrain owing to its explicit resolving of large atmospheric turbulence eddies. Thus the time series of wind speeds and wind directions more resemble the real atmosphere than those of meso-scale simulations. And the spectra of wind speeds is also more preferable. The sensitivity tests showed that the resolution of terrain data can affect the simulation results significantly so it should be treated with care. By increasing soil-moist the allocation of daytime land-surface heat fluxes is altered, thus the strength of large eddies is increased and so do the near-surface wind speeds, whereas the impact of surface roughness on model results is more complex. For one hand, increasing Z0 will enhance the transportation of momentum from upper air to near-surface flow, for another hand, larger value of Z0 is a negative factor when the wind speeds at 10 m height to be diagnosed by the land-surface model based on the Monin-Obukhov similarity theory and the atmospheric stability condition should be considered when analyze the impact of Z0 on near-surface wind speeds.

Cite this article

SUN Xuejin , LI Yan , ZHANG Yanhong , NING Hui , TANG Jing , WEN Yuanhong , MIAO Qingjian . Near-Surface Wind Simulation over Acrid Lakeshore Area and Sensitivity Studies using the WRF-LES[J]. Plateau Meteorology, 2017 , 36(3) : 835 -844 . DOI: 10.7522/j.issn.1000-0534.2016.00058

References

[1]Bou-Zeid E, Meneveau C, Parlange M B.2004.Large-eddy simulation of neutral atmospheric boundary layer flow over heterogeneous surfaces:Blending height and effective surface roughness[J].Water Resour Res, 40(2):W02505.
[2]Bou-Zeid E, Meneveau C, Parlange M B.2007.On the parameterization of surface roughness at regional scales[J].J Atmos Sci, 64(1):216-227.
[3]Courault D, Drobinski P, Brunet Y, et al.2007.Impact of surface heterogeneity on a buoyancy-driven convective boundary layer in light winds[J].Bound Layer Meteor, 124(4):383-403.
[4]Crosman E T, Horel J D.2012.Idealized large-eddy simulations of sea and lake breezes:Sensitivity to lake diameter, heat flux and stability[J].Bound Layer Meteor, 144(3):309-328.
[5]Hu X M, Nielsen J W, Zhang F Q.2010.Evaluation of three planetary boundary layer schemes in the WRF model[J].J Appl Meteorol Climatol, 49(9):1831-1844.
[6]Hu X M, Klein P M, Xue M.2013.Evaluation of the updated YSU planetary boundary layer scheme within WRF for wind resource and air quality assessments[J].J Geophysical Res:Atmospheres, 118(9):10490-10505.
[7]KangS L, Lenschow D H.2014.Temporal Evolution of Low-Level Winds Induced by Two-dimensional Mesoscale Surface Heat-Flux Heterogeneity[J].Bound Layer Meteor, 151(3):501-529.
[8]Liu Y, Warner T, Liu Y, et al.2011.Simultaneous nested modeling from the synoptic scale to the LES scale for wind energy applications[J].Journal of Wind Engineering and Industrial Aerodynamics, 99(4):308-319.
[9]Shin H, Hong S Y.2011.Intercomparison of planetary boundary-layer parameterizations in the WRF model for a single day from CASES-99[J].Bound Layer Meteor, 139(1):261-281.
[10]Skamarock W C, Klemp J B, Dudhia J, et al.2005.A description of the advanced research WRF version 2[R].National Center For Atmospheric Research Boulder Co Mesoscale and Microscale Meteorology Div.
[11]Talbot C, Bou-Zeid E, Smith J.2012.Nested mesoscale large-eddy simulations with WRF:performance in real test cases[J].J Hydrometeor, 13(5):1421-1441.
[12]WyngaardJ C.2004.Toward numerical modeling in the "terra incognita"[J].J Atmos Sci, 61(5):1816-1826.
[13]An Xingqin, Chen Yuhua, Lü Shihua.2002.Mesoscale simulations of winter low-level wind and temperature fields in Lanzhou city[J].Plateau Meteor, 21(2):186-192.<br/>安兴琴, 陈玉春, 吕世华.2002.中尺度模式对冬季兰州市低空风场和温度场的数值模拟[J].高原气象, 21(2):186-192.
[14]Chen Xinghong, Tao Shuwang, Wei Lei, et al.2012.Short-term wind power forecasting experiment based on WRF model and adapting partial least square regression method[J].Plateau Meteor, 31(5):1462-1469.<br/>程兴宏, 陶树旺, 魏磊, 等.2012.基于WRF模式和自适应偏最小二乘回归法的风能预报试验研究[J].高原气象, 31(5):1462-1469.
[15]Han Cunbo, Ma Yaoming, Liu Xin, et al.2014.Land surface characteristic variables estimated from ASTER images over Qomolangma area[J].Plateau Meteor, 33(3):596-606.DOI:10.7522/j.issn.1000-0534.2013.00081.<br/>韩存博, 马耀明, 刘新, 等.2014.利用ASTER数据反演珠峰地区地表特征参数[J].高原气象, 33(3):596-606.
[16]He Xiaofeng, Zhou Weirong, Sun Yihan.2014.Verification on surface wind speed of three global circulation models in China[J].Plateau Meteor, 33(5):1316-1322.DOI:10.7522/j.issn.1000-0534.2013.00093.<br/>何晓凤, 周荣卫, 孙逸涵.2014.3个全球模式对近地层风场预报能力的对比检验[J].高原气象, 33(5):1316-1322.
[17]Jiang Chuangye, Sun Xian, Xu Junchang.2011.A pplication of MM5/CALMET numerical simulation in wind energy resource assessment of northern Shanxi province[J].J Desert Res, 31(6):1606-1610.<br/>姜创业, 孙娴, 徐军昶.2011.MM5/CALMET数值模拟在陕北风能资源评估中的应用[J].中国沙漠, 31(6):1606-1610.
[18]Li Yan, Cheng Peipei, Lu Yixiong, et al.2015.Wind power forecasting over the typical complex terrains[J].Plateau Meteor, 34(2):414-425.DOI:10.7522/j.issn.1000-0534.2013.00181.<br/>李艳, 成培培, 路屹雄, 等.2015.典型复杂地形风能预报的精细化研究[J].高原气象, 34(2):414-425.
[19]Li Jianglin, Chen Yuchun, Lü Shihua.2009.Numerical simulation of local circulation in valley city in winter using RAMS model[J].Plateau Meteor, 28(6):1250-1259.<br/>李江林, 陈玉春, 吕世华.2009.利用RAMS模式对山谷城市冬季局地风场的数值模拟[J].高原气象, 28(6):1250-1259.
[20]Wang Chenghai, Hu Ju, Jin Shuanglong, et al.2011.Application and test of lower level wind field simulation with meso-scale model WRF in western region of northwest China[J].J Arid Meteor, 29(2):161-167.<br/>王澄海, 胡菊, 靳双龙, 等.2011.中尺度WRF模式在西北西部地区低层风场模拟中的应用和检验[J].干旱气象, 29(2):161-167.
[21]Xin Yu, Tang Jianping, Zhao Yizhou, et al.2010.Simulation of surface wind using MM5 model with different resolutions-a case study of Dabancheng and Xiaocaohu wind farms from April to September 2006[J].Plateau Meteor, 29(4):884-893.<br/>辛渝, 汤剑平, 赵逸舟, 等.2010.模式不同分辨率对新疆达坂城小草湖风区地面风场模拟结果的分析[J].高原气象, 29(4):884-893.
[22]Xin Yu, Chen Hongwu.2014.Influence of CALMET parameter adjustment in XJRUC coupling of CALMET over Dabancheng-Xiaocaohu wind area[J].Plateau Meteorology, 33(6):1675-1685.DOI:10.7522/j.issn.1000-0534.2013.00191.<br/>辛渝, 陈洪武.2014.XJRUCCALMET及CALMET不同参数调整对达坂城-小草湖区风场预报影响[J].高原气象, 33(6):1675-1685.
[23]Zhang Feimin, Wang Chenghai.2014.Experiment of surface-layer wind forecast improvement by assimilating conventional data with WRF-3DVAR[J].Plateau Meteor, 33(6):1675-1685.DOI:10.7522/j.issn.1000-0534.2012.00198.<br/>张飞民, 王澄海.2014.利用WRF-3DVAR同化常规观测资料对近地层风速预报的改进试验[J].高原气象, 33(3):676-685.
Outlines

/