Vol.33, NO.2, 2022
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Article Navigation >  Journal of Applied Meteorological Science  > 2022  >  33(2): 129-141
Liu Yujue, Huang Qianqian, Zhang Hanbin, et al. Refined assessment of wind environment over Winter Olympic competition zone based on large eddy simulation. J Appl Meteor Sci, 2022, 33(2): 129-141. DOI:  10.11898/1001-7313.20220201.
Citation: Liu Yujue, Huang Qianqian, Zhang Hanbin, et al. Refined assessment of wind environment over Winter Olympic competition zone based on large eddy simulation. J Appl Meteor Sci, 2022, 33(2): 129-141. DOI:  10.11898/1001-7313.20220201.
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Refined Assessment of Wind Environment over Winter Olympic Competition Zone Based on Large Eddy Simulation

DOI: 10.11898/1001-7313.20220201

  • Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089

  • Received Date: 2021-12-03
  • Rev Recd Date: 2022-02-14
  • Publish Date: 2022-03-31
    Abstract
  • The near-surface wind field over complex terrain is highly non-uniform due to the influence of topographical fluctuations. Therefore, it is extremely difficult to carry out high-density observational experiments and refined assessment of wind environment in these areas. In this case, high-resolution wind field data from numerical simulations is essential for the evaluation and analysis of near-surface wind environment. A refined wind environment assessment is carried out for Xiaohaituo alpine skiing field, Yanqing competition zone of Beijing Winter Olympic Games. Firstly, the weather patterns over the alpine skiing field during the winter competition periods from 2009 to 2021 (every February and March) are divided into 5 main types according to the Lamb-Jenkinson (L-J) atmospheric circulation classification scheme, and further classified into 93 secondary circulation types according to the wind directions and speed at 700 hPa. Secondly, the coupled model system of mesoscale meteorology and large eddy simulation (RMAPS-LES) developed by Beijing Institute of Urban Meteorology is used to simulate the wind field at a horizontal resolution of 37 m for typical cases under 93 weather patterns. The comparison between the simulation results and observations at 11 automatic weather stations shows that the model simulation performs reasonably well. The results show that the average deviation of 2 m temperature is less than 2℃, which perfectly meets the accuracy requirements of weather forecast service demand. Although 10 m wind speed is slightly overestimated for the whole typical cases of different weather patterns, the average deviation is within 3 m·s-1, and the average deviation of 10 m wind direction simulation is 10.43°-12.36°, which shows a good prediction skill. Finally, based on the wind field simulation results of different weather patterns, a ten-year winter wind environment assessment is carried out to provide detailed spatial distribution characteristics of the wind field, risk ranges, locations of gale, and the risk probability of exceeding the wind speed thresholds of the sport events, so as to provide technical supports for the organization, time arrangement, track design and wind hazard protection of 2022 Beijing Winter Olympic Games. The method provides an effective way for wind energy assessment and forecast over complex terrain, as well as meteorological services for wind-sensitive activities, such as outdoor mega-events over complex terrain, small-scale environmental design for large-scale architectural complex over mountain terrain, mountain fire disaster prevention and mitigation, mountain pollution forecasting and nuclear proliferation assessment.
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    References(36)

  • Fig. 1  Computational domain for RMAPS-LES of Yanqing competition zone with the terrain elevation and state boundaries

    (a)d01-d04, (b)d04 (⊙ and ☆ denote automatic weather stations)

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    Fig. 2  Domain and 16 grid points (black dots) for L-J circulation type classification

    (the red dot denotes the center of competition zone)

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    Fig. 3  Main circulation types from Feb to Mar during 2009-2021 of Yanqing competition zone

    (the percentage denotes the proportion)

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    Fig. 4  Wind rose of 700 hPa at the center of Yanqing competition zone from Feb to Mar during 2009-2021

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    Fig. 5  Errors of 2 m temperature and 10 m wind speed, direction at automatic weather stations

    (the marker denotes the median error, the whisker denotes the standard deviation of error)
    (a)2 m temperature of 31 secondary circulation types, (b)2 m temperature of three wind speed groups, (c)10 m wind speed of 31 secondary circulation types, (d)10 m wind speed of three wind speed groups, (e)10 m wind direction of 31 secondary circulation types, (f)10 m wind direction of three wind speed groups

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    Fig. 6  Average wind speed distribution of alpine skiing field

    (the upper part of plot is a three-dimensional map in the region alpine skiing field, the bottom part shows the top view in planar, white dots denote automatic weather stations)

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    Fig. 7  Maximum wind speed distribution of alpine skiing field

    (the others same as in Fig. 6)

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    Fig. 8  Probability of wind speed exceeding the threshold of alpine skiing of all wind speed groups

    (the others same as in Fig. 6)
    (a)critical decision point 11 m·s-1, (b)significant decision point 14 m·s-1, (c)factor to consider 17 m·s-1

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    Fig. 9  Probability of wind speed exceeding the threshold of alpine skiing of small wind speed group

    (the others same as in Fig. 6)
    (a)critical decision point 11 m·s-1, (b)significant decision point 14 m·s-1, (c)factor to consider 17 m·s-1

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    Table  1  L-J circulation classification scheme

    条件 大类环流型 小类环流型
    |ξ| < V 平直气流型D DE(1)，DS(4)，DSW(6)，DWSW(11)，
    DWNW(16)，DNW(21)，DNWN(26)，DN(29)
    V≤|ξ|≤2V且ξ≥0 气旋-平直气流混合型C-h C-hE，C-hS，C-hSW(7)，C-hWSW(12)，
    C-hWNW(17)，C-hNW(22)，C-hNWN，C-hN
    V≤|ξ|≤2V且ξ < 0 反气旋-平直气流混合型A-h A-hE(2)，A-hS，A-hSW(8)，A-hWSW(13)，
    A-hWNW(18)，A-hNW(23)，A-hNWN(27)，A-hN(30)
    |ξ|>2V且ξ≥0 气旋型C CE，CS(5)，CSW(9)，CWSW(14)，
    CWNW(19)，CNW(24)，CNWN，CN
    |ξ|>2V且ξ < 0 反气旋型A AE(3)，AS，ASW(10)，AWSW(15)，
    AWNW(20)，ANW(25)，ANWN(28)，AN(31)
    注：括号内数字表示小类环流型序号。
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    Table  2  Secondary circulation types from Feb to Mar during 2009-2021 of Yanqing competition zone

    风向 大类环流型
    D C-h A-h C A
    E 13 0 6 0 6
    S 42 2 5 7 2
    SW 80 13 6 19 9
    WSW 197 45 23 54 42
    WNW 430 89 139 71 145
    NW 331 43 247 37 187
    NWN 189 5 180 5 152
    N 71 0 85 0 84
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    Table  3  Schemes used in RMAPS-LES simulations

    参数化方案 d01 d02 d03 d04
    边界层方案 YSU LES LES LES
    微物理方案 New Thompson New Thompson New Thompson New Thompson
    长、短波辐射方案 RRTMG RRTMG RRTMG RRTMG
    近地层方案 Revised MM5 Revised MM5 Revised MM5 Revised MM5
    陆面过程方案 Noah Noah Noah Noah
    积云方案 Kain-Fritsch 无 无 无
    DownLoad: Download CSV
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    • Received : 2021-12-03
    • Accepted : 2022-02-14
    • Published : 2022-03-31
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