A study on objective forecast algorithm of 100-meter gust based on gust coefficient model
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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。Abstract: The rapid development of economy and culture in Beijing-Tianjin-Hebei region has a higher requirement for instantaneous strong wind forecasts. Correctly estimating and predicting instantaneous strong winds on the ground level in winter, especially accurate high-resolution grid-point forecasting of gusts under complex terrain condition, is of great significance for improving the service for major Winter Olympics events, the safe operation in the capital and surrounding cities, and disaster prevention and mitigation capabilities. This study establishes a relationship between the gust coefficient and wind speed, wind direction and terrain height based on long-term series of observation data in Beijing-Tianjin-Hebei. Combined with objective statistical analysis method, gust observation data fusion technology and grid point deviation correction technology, an objective gust forecast method is developed, which not only retains the model physical parameters and local climate characteristics, but also utilizes the grid point deviation correction technology. The results of batch verification and case analysis during the Winter Olympics show that the average absolute errors in the Zhangjiakou competition area and the Yanqing competition area are below 2.3 m/s and 3.0 m/s, respectively. The forecast score of gust wind speed above level 8 in the Yanqing competition area is above 0.5. It solves the bottleneck problem of large gust prediction errors and meets the on-site service requirements of major Winter Olympic activities.
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Key words:
- Gust forecast /
- Gust coefficient grid model /
- Grid deviation correction /
- Data fusion
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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
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−
0.20.3−
1.51.6−
3.33.4−
5.45.5−
7.98.0−
10.710.8−13.8 13.9−17.1 17.2−20.7 20.8−24.4 24.5−28.4 28.5−32.6 32.7−36.9 ≥37.0 0.0—0.2 1 0.6 0.4 0 0 0 0 0 0 0 0 0 0 0 0.3—1.5 0.6 1 0.6 0.4 0 0 0 0 0 0 0 0 0 0 1.6—3.3 0.4 0.6 1 0.6 0.4 0 0 0 0 0 0 0 0 0 3.4—5.4 0 0.4 0.6 1 0.6 0.4 0 0 0 0 0 0 0 0 5.5—7.9 0 0 0.4 0.6 1 0.6 0.4 0 0 0 0 0 0 0 8.0—10.7 0 0 0 0.4 0.6 1 0.6 0.4 0 0 0 0 0 0 10.8—13.8 0 0 0 0 0.4 0.6 1 0.6 0.4 0 0 0 0 0 13.9—17.1 0 0 0 0 0 0.4 0.6 1 0.6 0.4 0 0 0 0 17.2—20.7 0 0 0 0 0 0 0.4 0.6 1 0.6 0.4 0 0 0 20.8—24.4 0 0 0 0 0 0 0 0.4 0.6 1 0.6 0.4 0 0 24.5—28.4 0 0 0 0 0 0 0 0 0.4 0.6 1 0.6 0.4 0 28.5—32.6 0 0 0 0 0 0 0 0 0 0.4 0.6 1 0.6 0.4 32.7—36.9 0 0 0 0 0 0 0 0 0 0 0.4 0.6 1 0.6 ≥37.0 0 0 0 0 0 0 0 0 0 0 0 0.4 0.6 1 
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陈康凯,宋林烨,杨璐等. 2020. 一种基于高斯模糊的复杂地形下高分辨率三维插值方法的研究与试验应用. 高原气象,39(2):367-377Chen K K,Song L Y,Yang L,et al. 2020. Research and application of a three-dimensional interpolation method for high-resolution temperature in complex terrain based on gaussian fuzzy. Plateau Meteor,39(2):367-377 (in Chinese) 程丛兰,陈敏,陈明轩等. 2019. 临近预报的两种高时空分辨率定量降水预报融合算法的对比试验. 气象学报,77(4):701-714Cheng C L,Chen M,Chen M X,et al. 2019. Comparative experiments on two high spatiotemporal resolution blending algorithms for quantitative precipitation nowcasting. Acta Meteor Sinica,77(4):701-714 (in Chinese) 窦以文,屈玉贵,陶士伟等. 2008. 北京自动气象站实时数据质量控制应用. 气象,34(8):77-81Dou Y W,Qu Y G,Tao S W,et al. 2008. The application of quality control procedures for real-time data from automatic weather stations. Meteor Mon,34(8):77-81 (in Chinese) 胡波. 2017. 浙江沿海台风阵风系数的影响因子分析. 热带气象学报,33(6):841-849Hu B. 2017. Analysis of gust factor associated with typhoons on Zhejiang coast. J Trop Meteor,33(6):841-849 (in Chinese) 胡波,俞燎霓,滕代高. 2019. 浙江海岛台风和冬季大风阵风特征的对比分析. 热带气象学报,35(1):25-36Hu B,Yu L N,Teng D G. 2019. Comparative analysis of factors of typhoon gust and winter gale at coastal islands in Zhejiang. J Trop Meteor,35(1):25-36 (in Chinese) 马淑红,马韫娟,李建群等. 2009. 京津城际CRH3动车组大风天气条件下安全行车技术标准参数研究. 铁道技术监督,37(2):7-9,12Ma S H,Ma Y J,Li J Q,et al. 2009. Research on technical standard parameters for safe running of CRH3 EMU on Beijing-Tianjin inter-city high-speed railway under strong windy weather. Railw Qual Control,37(2):7-9,12 (in Chinese) 宋林烨,陈明轩,程丛兰等. 2019. 京津冀夏季雷达定量降水估测的误差统计及定量气候校准. 气象学报,77(3):497-515Song L Y,Chen M X,Cheng C L,et al. 2019. Characteristics of summer QPE error and a climatological correction method over Beijing-Tianjin-Hebei region. Acta Meteor Sinica,77(3):497-515 (in Chinese) 杨璐,韩丰,陈明轩等. 2018a. 基于支持向量机的雷暴大风识别方法. 应用气象学报,29(6):680-689Yang L,Han F,Chen M X,et al. 2018a. Thunderstorm gale identification method based on support vector machine. J Appl Meteor Sci,29(6):680-689 (in Chinese) 杨璐,陈明轩,孟金平等. 2018b. 北京地区雷暴大风不同生命期内的雷达统计特征及预警提前量分析. 气象,44(6):802-813Yang L,Chen M X,Meng J P,et al. 2018b. Radar statistical characteristics and warning lead analysis of thunderstorm gales in different life periods in Beijing. Meteor Mon,44(6):802-813 (in Chinese) 杨璐,陈敏,陈明轩等. 2019. 高时空分辨率三维风场在强对流天气临近预报中的融合应用研究. 气象学报,77(2):243-255Yang L,Chen M,Chen M X,et al. 2019. Fusion of 3D high temporal and spatial resolution wind field and its application in nowcasting of severe convective weather. Acta Meteor Sinica,77(2):243-255 (in Chinese) 杨璐,宋林烨,荆浩等. 2022. 复杂地形下高精度风场融合预报订正技术在冬奥会赛区风速预报中的应用研究. 气象,48(2):162-176Yang L,Song L Y,Jing H,et al. 2022. Fusion prediction and correction technique for high-resolution wind field in Winter Olympic Games area under complex terrain. Meteor Mon,48(2):162-176 (in Chinese) 周福,蒋璐璐,涂小萍等. 2017. 浙江省几种灾害性大风近地面阵风系数特征. 应用气象学报,28(1):119-128 doi: 10.11898/1001-7313.20170111Zhou F,Jiang L L,Tu X P,et al. 2017. Near-surface gust factor characteristics in several disastrous winds over Zhejiang province. J Appl Meteor Sci,28(1):119-128 (in Chinese) doi: 10.11898/1001-7313.20170111 Ágústsson H,Ólafsson H. 2004. Mean gust factors in complex terrain. Meteor Z,13(2):149-155 doi: 10.1127/0941-2948/2004/0013-0149 Beljaars A C M. 1987. The influence of sampling and filtering on measured wind gusts. J Atmos Ocean Technol,4(4):613-626 doi: 10.1175/1520-0426(1987)004<0613:TIOSAF>2.0.CO;2 Brasseur O. 2001. Development and application of a physical approach to estimating wind gusts. Mon Wea Rev,129(1):5-25 doi: 10.1175/1520-0493(2001)129<0005:DAAOAP>2.0.CO;2 Friederichs P,Göber M,Bentzien S,et al. 2009. A probabilistic analysis of wind gusts using extreme value statistics. Meteor Z,18(6):615-629 doi: 10.1127/0941-2948/2009/0413 Harris A R,Kahl J D W. 2017. Gust factors:Meteorologically stratified climatology,data artifacts,and utility in forecasting peak gusts. J Appl Meteor Climatol,56(12):3151-3166 doi: 10.1175/JAMC-D-17-0133.1 Hofherr T,Kunz M. 2010. Extreme wind climatology of winter storms in Germany. Climate Res,41(2):105-123 Holmes J D,Allsop A C,Ginger J D. 2014. Gust durations,gust factors and gust response factors in wind codes and standards. Wind Struct,19(3):339-352 doi: 10.12989/was.2014.19.3.339 Jungo P,Goyette S,Beniston M. 2002. Daily wind gust speed probabilities over Switzerland according to three types of synoptic circulation. Int J Climatol,22(4):485-499 doi: 10.1002/joc.741 Kahl J D W. 2020. Forecasting peak wind gusts using meteorologically stratified gust factors and MOS guidance. Wea Forecasting,35(3):1129-1143 doi: 10.1175/WAF-D-20-0045.1 Letson F,Pryor S C,Barthelmie R J,et al. 2018. Observed gust wind speeds in the coterminous United States,and their relationship to local and regional drivers. J Wind Eng Ind Aerodyn,173:199-209 doi: 10.1016/j.jweia.2017.12.008 Panofsky H A,Tennekes H,Lenschow D H,et al. 1977. The characteristics of turbulent velocity components in the surface layer under convective conditions. Bound Layer Meteor,11(3):355-361 doi: 10.1007/BF02186086 Panofsky H A,Dutton J A. 1984. Atmospheric Turbulence:Models and Methods for Engineering Applications. New York:Wiley,397pp Rudack D E. 2006. GFS-based mos wind gust guidance for the United States, Puerto Rico, and the U. S. Virgin Islands: NOAA Schreur B W,Geertsema G. 2008. Theory for a TKE based parameterization of wind gusts. HIRLAM Newslett,(54):177-188 Schulz J P. 2008. Revision of the turbulent gust diagnostics in the COSMO model. COSMO Newsl,(8):17-22 Sinden G. 2007. Characteristics of the UK wind resource:Long-term patterns and relationship to electricity demand. Energy Policy,35(1):112-127 doi: 10.1016/j.enpol.2005.10.003 Stucki P,Dierer S,Welker C,et al. 2016. Evaluation of downscaled wind speeds and parameterised gusts for recent and historical windstorms in Switzerland. Tellus A,68(1):31820 doi: 10.3402/tellusa.v68.31820 van den Bossche N,Lacasse M A,Janssens A. 2013. A uniform methodology to establish test parameters for watertightness testing:Part Ⅰ:A critical review. Build Environ,63:145-156 doi: 10.1016/j.buildenv.2012.12.003 Wieringa J. 1973. Gust factors over open water and built-up country. Bound Layer Meteor,3(4):424-441 doi: 10.1007/BF01034986 Wood N. 2000. Wind flow over complex terrain:A historical perspective and the prospect for large-eddy modelling. Bound Layer Meteor,96(1):11-32 Yang L,Chen M X,Wang X L,et al. 2021. Classification of precipitation type in North China using model-based explicit fields of hydrometeors with modified thermodynamic conditions. Wea Forecasting,36(1):91-107 doi: 10.1175/WAF-D-20-0005.1 -
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