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基于阵风系数模型的百米级阵风客观预报算法研究

杨璐 王晓丽 宋林烨 陈明轩 秦睿 曹伟华 吴剑坤

杨璐,王晓丽,宋林烨,陈明轩,秦睿,曹伟华,吴剑坤. 2023. 基于阵风系数模型的百米级阵风客观预报算法研究. 气象学报,81(1):1-16 doi: 10.11676/qxxb2023.20220052
引用本文: 杨璐,王晓丽,宋林烨,陈明轩,秦睿,曹伟华,吴剑坤. 2023. 基于阵风系数模型的百米级阵风客观预报算法研究. 气象学报,81(1):1-16 doi: 10.11676/qxxb2023.20220052
Yang Lu, Wang Xiaoli, Song Linye, Chen Mingxuan, Qin Rui, Cao Weihua, Wu Jiankun. 2023. A study on objective forecast algorithm of 100-meter gust based on gust coefficient model. Acta Meteorologica Sinica, 81(1):1-16 doi: 10.11676/qxxb2023.20220052
Citation: Yang Lu, Wang Xiaoli, Song Linye, Chen Mingxuan, Qin Rui, Cao Weihua, Wu Jiankun. 2023. A study on objective forecast algorithm of 100-meter gust based on gust coefficient model. Acta Meteorologica Sinica, 81(1):1-16 doi: 10.11676/qxxb2023.20220052

基于阵风系数模型的百米级阵风客观预报算法研究

doi: 10.11676/qxxb2023.20220052
基金项目: 北京自然科学基金(8222051)、灾害天气国家重点实验室开放课题(2022LASW-B11)、中国气象局重点创新团队(CMA2022ZD07)
详细信息
    作者简介:

    杨璐,主要从事多源资料融合分析与应用研究。E-mail:lyang@ium.cn

    通讯作者:

    陈明轩,主要从事短时临近预报研究。E-mail: mxchen@ium.cn

  • 中图分类号: P456

A study on objective forecast algorithm of 100-meter gust based on gust coefficient model

  • 摘要: 京津冀地区经济和文化的快速发展对冬季地面瞬时强风预报要求越来越高。正确估计和预测冬季地面瞬时强风,尤其是复杂地形条件下的阵风高分辨率格点精准预报,对于提升重大活动服务保障、首都及周边地区城市安全运行及防灾减灾能力等方面都具有重要意义。本研究基于京津冀长时间序列的实况观测资料,建立了阵风系数与稳定风速、风向、地形高度各要素之间的关系模型,并结合客观统计分析方法、阵风观测数据融合技术、格点偏差订正技术,发展了一种既保留模式物理参数特征和阵风局地气候特征,又发挥格点偏差订正技术的阵风客观预报方法。冬奥赛事期间批量检验和个例分析结果表明,基于阵风系数格点模型和模式后处理订正技术得到的百米级分辨率、分钟级更新的阵风客观预报产品,24 h预报时效内张家口赛区和延庆赛区考核站平均绝对误差分别在2.3 m/s和3.0 m/s以下,延庆赛区8级以上大风,阵风风速预报评分超过0.5,解决了复杂山地数值模式阵风预报误差大、几乎无法业务应用的瓶颈问题,满足冬奥重大活动保障现场服务要求。

     

  • 图 1  2018—2021年京津冀地区不同风速区间 全风向条件下阵风系数的空间分布 ( a. 3级以下,b. 3—5级,c. 6级,d. 7级及以上)

    Figure 1.  Spatial distributions of gust coefficients at four different wind speed intervals in Beijing-Tianjin-Hebei under all wind directions for the period of 2018—2021 (a. below level 3,b. levels 3—5,c. level 6,d. level 7 and above level 7 )

    图 2  京津冀地区地形高度 (a) 及下垫面类型(b)分布 (下垫面类型中,0代表水体,1—5代表森林,6—9代表森林覆盖的草地和灌木丛,10代表草地,11代表农田耕地,12代表裸地,13代表城市)

    Figure 2.  Terrain height (a) and surface land use types (b) in Beijing-Tianjin-Hebei (in Fig. 2b,0 represents water,1—5 denote forest,6—9 are for wooded grassland and shrubland,10 indicates grassland,11 is cropland,12 is bare land,13 represents urban)

    图 3  2018—2021年北京地区全风向条件下阵风系数空间分布 (a. 3级以下,b. 3—5级)

    Figure 3.  Spatial distributions of gust coefficient in all wind directions in Beijing for the period of 2018—2021 (a. below level 3 ,b. levels 3—5)

    图 4  2018—2021年京津冀8个不同风向区间全风速条件下阵风系数空间分布 (a. 西北风,b. 北风,c. 东北风,d. 东风,e. 东南风,f. 南风,g. 西南风,h. 西风)

    Figure 4.  Spatial distributions of gust coefficient at 8 different wind direction intervals in Beijing-Tianjin-Hebei under full wind speed for the period of 2018—2021 (a. northwesterly wind,b. northerly wind,c. northeasterly wind,d. easterly wind,e. southeasterly wind,f. southerly wind,g. southwesterly wind,h. westerly wind)

    图 5  2018—2021年北京市延庆赛区竞速1 (a)、竞速5 (b)、竞速8 (c) 及北京国家站观象台 (d) 不同风速区间、不同风向阵风系数玫瑰图 (阵风系数等值线每圈间隔为0.5)

    Figure 5.  Wind rose diagrams of gust coefficient at Jingsu 1 (a), Jingsu 5 (b), Jingsu 8 (c) in the Yanqing competition area and Beijing National Station Observatory (d) from 2018 to 2021 at different wind speed intervals and different wind direction intervals (the interval of each circle is 0.5)

    图 6  2022年2月4—20日冬奥赛事期间睿图-睿思系统冬奥赛区 (a)、张家口赛区 (b) 及延庆赛区 (c) 阵风偏差、平均绝对误差、均方根误差 (曲线) 及延庆赛区8级以上 (风速>17.1 m/s) 阵风风速评分 (柱状)(Contour2和Contour3分别表示等值线2和3)

    Figure 6.  Gust deviations, mean absolute errors, root mean square errors (colored curves) in the Winter Olympic competition area (a), Zhangjiakou competition area (b) and BIAS,MAE,RMSE (colored curves) and gust wind speed scores above level 8 (wind speed >17.1 m/s)(bar in Yanqing competition area (c) during the period of 4—20 Feburary 2022 contour 2 and contour 3 represent isoline 2 and 3 respectively)

    图 7  2022年2月4—20日竞速赛道高山代表站点竞速1 (Jingsu1) 及延庆国家站 (Yanqing) 阵风偏差、平均绝对误差、均方根误差对比

    Figure 7.  Comparison of BIAS,MAE and RMSE at representative high-mountain sites of Jingsu 1 (Jingsu1) and Yanqing National Station (Yanqing) during the period of 4—20 Feburary 2022

    图 8  2022年2月4—6日竞速1 (JS1) 号站1 h极大风速

    Figure 8.  1 h maximum wind speed at Jingsu1 (JS1) from 4 to 6 February,2022

    图 9  2022年2月5(a)、6(b)和7(c)日11时延庆赛区阵风分析场 (第1条色阶表示风矢大小,第2条色阶表示地形高度; JS1、JS3、JS5、JS8分别表示竞速1、3、5和8)

    Figure 9.  Gust analysis field in Yanqing competition area at 11:00 BT 5 (a),6(b) and 7 (c) February 2022 (the first color scale indicates the wind vector size,and the secend color scale indicates the terrain height;the labels JS1,JS3,JS5,and JS8 represent Jingsu 1,3,5,and 8)

    图 10  延庆赛区竞速1站点2月5日16时 (a) 和6日16时 (b) 起报的0—24 h分析和预报阵风风场 (黑色) 与实况观测风场 (红色) 的时间序列

    Figure 10.  Time series of 0—24 h analysis and forecast wind field (black) and observed wind field (red) at Jingsu1 station in Yanqing competition area at 16:00 BT 5 (a) and 16:00 BT 6 (b) Feburary

    图 12  2022年2月13日11时 (a) 和14日11时 (b) 延庆赛区阵风分析场 (第1条色阶表示风矢大小,第2条色阶表示地形高度; JS1、JS3、JS5、JS8分别表示竞速1、3、5和8)

    Figure 12.  Gust analysis field in Yanqing competition area at 11:00 BT 13 (a) and 14:00 (b) February 2022 (the first color scale indicates the wind vector size,and the secend color scale indicates the terrain height;the labels JS1,JS3,JS5,and JS8 represent Jingsu 1,3,5,and 8)

    图 11  2022年2月12—14日竞速1站点1 h极大风速

    Figure 11.  1 h maximum wind speed at Jingsu1 (JS1) from 12 to 14 February,2022

    图 13  延庆赛区竞速1站点2月12日23时 (a) 和13日23时 (b) 睿图-睿思0—24 h分析和预报阵风风场 (黑色) 与观测风场 (红色) 的时间序列

    Figure 13.  Time series of 0—24 h analysis and forecast wind field (black) and observed wind field (red) at Jingsu1 station in Yanqing competition area at 23:00 BT 12 (a) and 23:00 BT 13 (b) Feburary

    Continued

    表  1  阵风风速预报评分对照

    Table  1.   Comparison table of gust wind speed forecast scores

    实况预报
    0.0−
    0.2
    0.3−
    1.5
    1.6−
    3.3
    3.4−
    5.4
    5.5−
    7.9
    8.0−
    10.7
    10.8−13.813.9−17.117.2−20.720.8−24.424.5−28.428.5−32.632.7−36.9≥37.0
    0.0—0.210.60.400000000000
    0.3—1.50.610.60.40000000000
    1.6—3.30.40.610.60.4000000000
    3.4—5.400.40.610.60.400000000
    5.5—7.9000.40.610.60.40000000
    8.0—10.70000.40.610.60.4000000
    10.8—13.800000.40.610.60.400000
    13.9—17.1000000.40.610.60.40000
    17.2—20.70000000.40.610.60.4000
    20.8—24.400000000.40.610.60.400
    24.5—28.4000000000.40.610.60.40
    28.5—32.60000000000.40.610.60.4
    32.7—36.900000000000.40.610.6
    ≥37.0000000000000.40.61
    下载: 导出CSV
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  • 收稿日期:  2022-03-31
  • 修回日期:  2022-06-29
  • 网络出版日期:  2022-07-01

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