PREDICTION ON WIND SPEED AND WIND DIRECTION OF TRAFFIC LINE IN ALPINE REGION
-
摘要: 高寒地区交通线路风吹雪灾害严重，对交通线路全线天气状况的预测对于该类灾害的预测至关重要，目前该方面的研究仍然比较缺乏。该文采用WRF(天气研究预报模型)中尺度天气数值模拟，以新疆克塔铁路为研究对象，模拟该线路所在区域2018年−2019年冬季的天气状况。通过水平分辨率10 km~2 km的双重嵌套模拟，调整微物理方案及行星边界层方案，得到铁路沿线不同路段风速分布概率以及相应的主导风向。研究表明：WRF模拟结果能够较好的反映出道路沿线各路段不同的风速概率分布，结合主导风向与线路夹角，为预测不同路段发生风吹雪灾害的概率提供更加精确地依据，并为道路选线以及路段形式的设计提供参考。Abstract: The traffic line in the alpine region is deeply affected by drifting snow disasters. The weather along the entire traffic line is very important on predicting the snowdrift disaster, but there is still a lack of research in this area. In the present study, the mesoscale model WRF (the Weather Research and Forecasting Model) is used to predicate the weather in the winter of the Karamay-Tacheng Railway in Xinjiang from 2018 to 2019. This simulation is mainly two-level nested with a horizontal resolution of 10 km-2 km and adopts different microphysics and planetary boundary layer physics to obtain different distribution probability of wind velocity and dominant wind direction along the railway line. The results show that the WRF simulation results can reflect different probability distribution of wind speeds in different sections along the railway. Combined with the angle between the dominant wind direction and the traffic line, it can provide a more accurate basis for predicting the probability of drifting snow disasters in different sections and a reference for the design of traffic lines and sections form.
-
Key words:
- highway and railway engineering /
- weather prediction /
- WRF /
- drifting snow /
- probability distribution
-
图 2 逐时温度模拟结果与气象站观测数据对比图
Figure 2. The comparison of hourly temperature between the simulation results and station observation
图 3 逐时风速模拟结果与气象站观测数据对比图
Figure 3. The comparison of hourly wind velocity between the simulation results and station observation
5 克塔铁路K001~K007路段风速概率分布
5. Probability distribution of wind velocity in K001~K007 section of Karamay-Tacheng Railway
图 7 K004~K005路段局部地形高程图
Figure 7. The local topographic elevation map of K004 ~K005 section
表 1 组合方案设置
Table 1. The combination schemes setting
方案名称 方案1 方案2 方案3 方案4 微物理方案
(mp_physics)Purdue-Lin WSM6 Purdue-Lin Purdue-Lin 行星边界层方案
(bl_pbl_physics)YSU YSU MRF MYJ 
下载: 导出CSV
表 2 其余参数方案设置
Table 2. The other physical options
方案名称 方案类型 长波辐射(ra_lw_physics) RRTM 短波辐射(ra_sw_physics) Dudhia 近地面层 (sf_sfclay_physic) MM5 陆面层(sf_surface_physcs) Noah 积云参数化(cu_physics) Kain-Fritsch
下载: 导出CSV
表 3 K001~K007路段大于起动风速的概率
Table 3. Probability of wind speed greater than starting speed in K001~K007 section
路段 K001 K002 K003 K004 K005 K006 K007 概率/(%) 11.2 11.8 14.2 23.5 49.1 4 1.4
下载: 导出CSV
-
[1] 刘多特, 李永乐, 汪斌. 风雪绕流数值模拟的积雪预测模型研究[J]. 工程力学, 2016, 33(8): 122 − 131. doi: 10.6052/j.issn.1000-4750.2015.01.0019Liu Duote, Li Yongle, Wang Bin. A numerical prediction model for snow accumulation caused by ambient snowdrift [J]. Engineering Mechanics, 2016, 33(8): 122 − 131. (in Chinese) doi: 10.6052/j.issn.1000-4750.2015.01.0019 [2] 李飞强, 马文勇, 崔子晗, 等. 基于两方程模型的路堤风吹雪数值模拟[J]. 工程力学, 2021, 38(增刊): 189 − 194. doi: 10.6052/j.issn.1000-4750.2020.05.S034Li Feiqiang, Ma Wenyong, Cui Zihan, et al. Numerical simulation of snowdrift on embankment based on two equation model [J]. Engineering Mechanics, 2021, 38(Suppl): 189 − 194. (in Chinese) doi: 10.6052/j.issn.1000-4750.2020.05.S034 [3] 马文勇, 崔子晗, 柴晓兵. 风速和持续时间对立方体周边风致积雪演化影响研究[J]. 工程力学, 2022, 39(1): 108 − 117. doi: 10.6052/j.issn.1000-4750.2020.12.0884Ma Wenyong, Cui Zihan, Chai Xiaobing. Effects of wind speed and duration on process of snow distribution around a cube [J]. Engineering Mechanics, 2022, 39(1): 108 − 117. (in Chinese) doi: 10.6052/j.issn.1000-4750.2020.12.0884 [4] 李弘毅, 王建, 郝晓华. 祁连山区风吹雪对积雪质能过程的影响[J]. 冰川冻土, 2012, 34(5): 1084 − 1090.Li Hongyi, Wang Jian, Hao Xiaohua. Influence of blowing snow on snow mass and energy exchanges in the Qilian Mountainous [J]. Journal of Glaciology and Geocryology, 2012, 34(5): 1084 − 1090. (in Chinese) [5] Ma W, Li F, Sun Y, et al. Field measurement and numerical simulation of snow deposition on an embankment in snowdrift [J]. Wind Struct, 2021, 32(5): 453 − 469. [6] 张家平. 黑龙江省公路风吹雪灾害时空分布与防治技术研究[D]. 西安: 长安大学, 2012.Zhang Jiaping. Research on the temporal & spatial distribution rules and prevention technology of snowdrift disaster of Heilongjiang province [D]. Xi’an: Chang’an University, 2012. (in Chinese) [7] 郭丹奇, 柳春红, 吴春玉. 公路风吹雪的形成和影响因素分析[J]. 煤炭技术, 2003, 22(8): 112 − 113. doi: 10.3969/j.issn.1008-8725.2003.08.084Guo Danqi, Liu Chunhong, Wu Chunyu. Analysis on the formation and influential factors of snow on highway [J]. Coal technology, 2003, 22(8): 112 − 113. (in Chinese) doi: 10.3969/j.issn.1008-8725.2003.08.084 [8] 刘衡麟, 李小芳. 公路风吹雪雪害预警分析和防治技术[J]. 黑龙江交通科技, 2014, 37(11): 67. doi: 10.3969/j.issn.1008-3383.2014.11.047Liu Henglin, Li Xiaofang. Forewaning analysis and prevention technology of drifting snow disaster of highway [J]. Communications Science and Technology of Heilongjiang, 2014, 37(11): 67. (in Chinese) doi: 10.3969/j.issn.1008-3383.2014.11.047 [9] 施佳誉, 徐冬英, 夏才初, 等. 公路风吹雪雪阻分布规律及雪灾形成机理研究[J]. 公路, 2020, 65(1): 257 − 264.Shi Jiayu, Xu Dongying, Xia Caichu, et al. Research on the distribution law of snow blockage of snow drift on road and the formation mechanism of snow disaster [J]. Highway, 2020, 65(1): 257 − 264. (in Chinese) [10] 薛桁, 朱瑞兆, 杨振斌, 等. 中国风能资源贮量估算[J]. 太阳能学报, 2001(2): 167 − 170.Xue Heng, Zhu Ruizhao, Yang Zhenbin, et al. Assessment of wind energy reserves in China [J]. Acta Energiae Solaris Sinica, 2001(2): 167 − 170. (in Chinese) [11] 祁延录. 考虑风吹雪灾害的新疆克塔铁路选线研究[J]. 铁道科学与工程学报, 2018, 15(11): 2813 − 2824.Qi Yanlu. Strategies of railway alignment selection for Karamay-Tacheng railway in Xinjiang considering snow drifting disasters [J]. Journal of Railway Science and Engineering, 2018, 15(11): 2813 − 2824. (in Chinese) [12] Skamarock W C, Klemp J B. A time-split nonhydrostatic atmospheric model for research and NWP applications [J]. J Comput Phys: X, 2006, 227(7): 3465 − 3485. [13] Tse K T, Li S W, Fung J. A comparative study of typhoon wind profiles derived from field measurements, meso-scale numerical simulations, and wind tunnel physical modeling [J]. Journal of Wind Engineering & Industrial Aerodynamics, 2014, 131: 46 − 58. [14] 王澄海, 胡菊, 靳双龙, 等. 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, 2011, 29(2): 161 − 167.Wang Chenghai, Hu Ju, Jin Shuanglong, et al. Application and test of lower level wind field simulation with meso-scale model WRF in western region of northwest China [J]. Journal of Arid Meteorology, 2011, 29(2): 161 − 167. (in Chinese) [15] Marjanovic N, Wharton S, Chow F K. Investigation of model parameters for high-resolution wind energy forecasting: Case studies over simple and complex terrain [J]. J Wind Eng Ind Aerodyn, 2014, 134(134): 10 − 24. [16] Carvalho D, Rocha A, Gomez-Gesteira M, et al. Offshore wind energy resource simulation forced by different re-analyses: Comparison with observed data in the iberian peninsula [J]. Appl Energy, 2014, 134: 57 − 64. doi: 10.1016/j.apenergy.2014.08.018 [17] 杨旭. 玛依塔斯交通走廊风吹雪特点研究[J]. 铁道工程学报, 2018, 35(12): 1 − 6. doi: 10.3969/j.issn.1006-2106.2018.12.001Yang Xu. Research on the characteristics of drifting snow disaster in Xinjiagn Mayitas traffic corridor [J]. Journal of Railway Engineering Society, 2018, 35(12): 1 − 6. (in Chinese) doi: 10.3969/j.issn.1006-2106.2018.12.001 [18] Carvalho D, Rocha A, Gómez-Gesteira M, et al. A sensitivity study of the WRF model in wind simulation for an area of high wind energy [J]. Environmental Modelling & Software, 2012, 33(7): 23 − 34. [19] 于淼, 廉丽姝, 李宝富, 等. 基于WRF模式的青岛沿海地区近地面风的敏感性研究[J]. 热带气象学报, 2020, 36(2): 277 − 288.Yu Miao, Lian Lishu, Li baofu, et al. Sensitivity analysis of near-surface wind in Qingdao coastal area based on WRF model [J]. Journal of Tropical Meteorology, 2020, 36(2): 277 − 288. (in Chinese) [20] 宋倩, 毛健, 马振兴, 等. WRF模式气象要素模拟精度的验证及订正——以南疆区域为例[J]. 天津师范大学学报(自然科学版), 2020, 40(1): 53 − 59.Song Qian, Mao Jian, Ma Zhenxing, et al. Verification and correction of WRF model meteorological element simulation accuracy: A case study of southern margin of Xinjiang, China [J]. Journal of Tianjin Normal University (Natural Science Edition), 2020, 40(1): 53 − 59. (in Chinese) [21] 马惠群, 王远坤. 逐时风速概率分布研究[J]. 电网与清洁能源, 2018, 34(12): 53 − 58.Ma Huiqun, Wang Yuankun. Research on probability distribution of hourly wind speed [J]. Power System and Clean Energy, 2018, 34(12): 53 − 58. (in Chinese) [22] Aslam M. Testing average wind speed using sampling plan for Weibull distribution under indeterminacy [J]. Scientific Reports, 2021, 11: 7532. doi: 10.1038/s41598-021-87136-8 [23] 王中隆, 李长治. 艾肯达坂风雪流形成机制及其治理[J]. 中国沙漠, 1995, 15(2): 105 − 108.Wang Zhonglong, Li Changzhi. The formation mechanism of snow drift in Ainken Daban and its control [J]. Journal of Desert Research, 1995, 15(2): 105 − 108. (in Chinese) [24] 吕晓辉, 黄宁, 郭磊, 等. 风吹雪廓线的风洞实验研究[J]. 力学与实践, 2013, 35(1): 20 − 25.Lü Xiaohui, Huang Ning, Guo Lei, et al. Wind tunnel study of vertical profile of drifting snow [J]. Mechanics in Engineering, 2013, 35(1): 20 − 25. (in Chinese) [25] GB 50009−2019, 建筑结构荷载规范[S]. 北京: 中国建筑工业出版社, 2019.GB 50009−2019, Load code for the design of building structures [S]. Beijing: China Building Industry Press, 2019. (in Chinese) -
点击查看大图
图(9) / 表(3)
计量
- 文章访问数: 46
- HTML全文浏览量: 27
- PDF下载量: 12
- 被引次数: 0
