边界层参数化方案对文昌近地层风速模拟的影响
Influence of Boundary Layer Parameterization Scheme on Wind Speed Simulation near Surface in Wenchang
DOI: 10.12677/OJNS.2023.113036, PDF,   
作者: 赵子荟, 齐玉磊：成都信息工程大学大气科学学院，四川 成都
关键词: 风速；WRF模式；边界层参数化方案；模拟试验；Wind Velocity； WRF Model； Boundary Layer Parameterization Scheme； Simulated Test
摘要: 为了研究边界层参数化方案对文昌近地层风速模拟的影响，本文选用美国国家环境中心终分析资料FNL (Final Operational Global Analysis)作为模式的背景场资料，应用WRFV4.2.1模式10种边界层参数化方案(YSU, MYJ, QNSE, MYNN2, MYNN3, BouLac, UW, TEMF, Shin-Hong和GBM)，对文昌近地层2015年每月前三天的风速进行数值模拟，检验评估了它们对不同高度层风速的预报能力。结果表明：MYNN2方案和MYNN3方案在低层的风速模拟效果较好，UW方案、GBM方案和BouLac方案在高层风速模拟效果较好，TEMF方案风速模拟效果最差，且总体来看10个方案在70 m和90 m高度层的风速模拟效果更好。
Abstract: In order to study the influence of boundary layer parameterization scheme on the wind speed simulation of Wenchang near-surface layer, this paper selects the Final Operational Global Analysis (FNL) data of the National Environmental Center of the United States as the background field data of the model, and uses 10 boundary layer parameterization schemes of WRFV4.2.1 model (YSU, MYJ, QNSE, MYNN2, MYNN3, BouLac, UW, TEMF, Shin-Hong and GBM) to numerically simulate the wind speed of Wenchang near-surface layer in the first three days of each month in 2015. Their ability to forecast wind speeds at different altitudes was tested and evaluated. The results show that the MYNN2 scheme and MYNN3 scheme have better wind speed simulation effect at the low level, the UW scheme, GBM scheme and BouLac scheme have better wind speed simulation effect at the high level, and the TEMF scheme has the worst wind speed simulation effect. In general, the wind speed simulation effect of the 10 schemes at 70 m and 90 m levels is better.
文章引用：赵子荟, 齐玉磊. 边界层参数化方案对文昌近地层风速模拟的影响[J]. 自然科学, 2023, 11(3): 305-317. https://doi.org/10.12677/OJNS.2023.113036

参考文献

[1] 徐亚钦, 翟国庆, 李国平, 余贞寿, 严红梅. WRF模式对高影响浙江型台风微物理和边界层参数化方案的优化试验[J]. 热带气象学报, 2017, 33(2): 201-211. [Google Scholar] [CrossRef] 
[2] 王莹. 海南岛地形对局地海风降水强度和分布影响的数值模拟研究[D]: [硕士学位论文]. 南京: 南京信息工程大学, 2017.
[3] 仲鹏志, 冶磊, 李煜斌, 等. 不同边界层参数化方案对台风“利奇马”模拟的影响研究[J]. 热带气象学报, 2022, 38(2): 275-289.
[4] 屠妮妮, 何光碧, 张利红. 不同边界层和陆面过程参数化方案对比分析[J]. 高原山地气象研究, 2012, 32(3): 1-8. [Google Scholar] [CrossRef] 
[5] 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[J]. 地球物理学报, 2016, 59(3): 803-815.
[6] 王莹, 苗峻峰. 近地层参数化对海南岛海风降水模拟的影响[J]. 地球物理学报, 2019, 62(1): 32-48. [Google Scholar] [CrossRef] 
[7] 陈炯, 郑永光, 邓莲堂, 等. WRF模式中不同边界层参数化方案对2003年7月江淮暴雨的数值模拟及其比较[C]//新世纪气象科技创新与大气科学发展. 北京: 气象出版社, 2003: 2268-2271.
[8] 王成刚, 沈滢洁, 罗峰, 等. 晴天及阴天条件下WRF模式中几种边界层参数化方案的对比分析研究[J]. 地球物理学报, 2017, 60(3): 924-934.
[9] Draxl, C., Hahmann, A.N., Peña, A. and Giebel, G. (2014) Evaluating Winds and Vertical Wind Shear from Weather Research and Forecasting Model Forecasts Using Seven Planetary Boundary Layer Schemes. Wind Energy, 17, 39-55. [Google Scholar] [CrossRef] 
[10] 李玉鹏, 王东海, 尹金方. 蒙西地区不同边界层参数化方案的近地层风场预报效果评估[J]. 中山大学学报自然科学版, 2018, 57(4): 16-29.
[11] 李玉鹏. 模式背景场及边界层参数化方案对近地层风场预报的影响[D]: [硕士学位论文]. 北京: 中国气象科学研究院, 2017.
[12] Tyagi, B., Magliulo, V., Finardi, S., et al. (2018) Performance Analysis of Planetary Boundary Layer Parameterization Schemes in WRF Modeling Set Up over Southern Italy. Atmosphere, 9, 272. [Google Scholar] [CrossRef] 
[13] 王子谦, 段安民, 吴国雄. 边界层参数化方案及海气耦合对WRF模拟东亚夏季风的影响[J]. 中国科学: 地球科学, 2014, 44(3): 548-562.
[14] 吴哲珺, 包云轩, 朱霆, 等. 长江流域一次大暴雨过程的低空急流形成和影响机制分析[J]. 热带气象学报, 2019, 35(3): 409-422.
[15] 张龙. WRF不同PBL方案对SACOL冬季近地面气象要素模拟验证[D]: [硕士学位论文]. 兰州: 兰州大学, 2012.
[16] Janić, Z.I. (2001) Nonsingular Implementation of the Mel-lor-Yamada Level 2.5 Scheme in the NCEP Meso Model.
[17] Sukoriansky, S., Galperin, B. and Perov, V. (2005) Application of a New Spectral Theory of Stably Stratified Turbulence to the Atmospheric Boundary Layer over Sea Ice. Boundary-Layer Meteorology, 117, 231-257. [Google Scholar] [CrossRef] 
[18] Olson, J.B. and Brown, J.M. (2009) A Comparison of Two Mellor-Yamada-Based PBL Schemes in Simulating a Hybrid Barrier Jet. 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction, Omaha, Vol. 13. https://api.semanticscholar.org/CorpusID:43782503
[19] Bougeault, P. and Lacarrere, P. (1989) Parameterization of Orography-Induced Turbulence in a Mesobeta—Scale Model. Monthly Weather Review, 117, 1872-1890. [Google Scholar] [CrossRef] 
[20] 张玉, 王小伦, 刘雁. 不同边界层方案在短期天气模拟中的精度评估[J]. 通化师范学院学报, 2021, 42(12): 15-21.
[21] Mielikainen, J., Huang, B. and Huang, H.L.A. (2015) Optimizing Total Energy-Mass Flux (TEMF) Planetary Boundary Layer Scheme for Intel’s Many Integrated Core (MIC) Architecture. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 4106-4119. [Google Scholar] [CrossRef] 
[22] Shin, H. and Hong, S.Y. (2015) Representation of the Subgrid-Scale Turbulent Transport in Convective Boundary Layers at Gray-Zone Resolutions. Monthly Weather Review, 143, 250-271. [Google Scholar] [CrossRef]