Evaluation of three different gust diagnostic schemes in the CMA-BJ for gale forecasting over Beijing
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摘要: 数值模式预报是阵风预报的重要途径之一,对“中国气象局北京快速更新循环数值预报系统(简称CMA北京模式)”中AFWA、UPP、IUM三种阵风诊断方案在北京地区大风预报中的性能进行了分析评估。两次大风过程的分析以及各季节大风预报的批量试验检验结果显示:三种方案的阵风预报存在明显差异,IUM方案的阵风预报能力优势明显。IUM方案对冷空气大风和雷暴大风预警都有较好的指示意义。其对2020年3月18日冷空气大风过程中大风起始时间、大风区位置和演变以及过程极大风速均有较好的预报效果,对2020年8月2日雷暴大风过程中大风区范围预报偏大且位置存在偏差,但对大风预警的指示意义最强。IUM方案的阵风风速预报整体偏强,但对各个季节达到或超过5级阵风的等级预报较为准确。总体而言,IUM方案对北京地区大风预报性能较好,基于该方案制作的阵风预报产品可为大风预报提供有力支撑。Abstract: Numerical prediction is one of the important ways to forecast gust. This study analyzed and evaluated the performance of the three gust diagnostic schemes (AFWA, UPP and IUM) in the CMA-BJ for gale forecasting over Beijing. Subjective analysis on two extreme gale processes as well as objective validation on batch experiments of each season indicated that there are significant differences in the gust forecasting using the three schemes, and the forecasting with the IUM scheme shows significant advantages. The IUM scheme performs relatively well on forecasting gales associated with both cold air and thunderstorms. For the gale on 18 March 2020, which was induced by cold air invasion, the scheme shows good performance on the forecast of starting and ending time, the location and evolution, and the maximum value during the entire period of the gale. For the gale on 2 August 2020, which was generated by a thunderstorm, the scheme overestimates the gale area and shows certain biases in the location of the gale. However, the scheme issues warning for gale, which is the most significant. Moreover, the gust speed predicted by the IUM scheme has positive biases at all seasons, but the forecasts of gales equal to or greater than level 5 are more consistent with observations. In general, the IUM scheme performs better than the other two schemes for the gale forecasting over Beijing, and can provide strong support for the gale forecasting.
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Key words:
- CMA-BJ /
- Gust diagnosis /
- Gale with cold air /
- Gale with thunderstorms /
- Batch experiments
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图 2 2020年3月18日08时至19日08时北京地区20个国家级气象站逐时 (a) 2 min平均风速和 (b) 阵风 (蓝色点实线代表平均值,对应黑色箱线图分别显示了最小值、下四分位数、中位数、上四分位数和最大值)
Figure 2. Hourly (a) 2 min mean surface wind speed and (b) gust at 20 national weather stations in Beijing from 08:00 BT 18 March to 08:00 BT 19 March 2020 (the blue dotted-lines indicate the average values;the black boxes indicate the minimum,lower quartile,median,upper quartile,and maximum values)
图 4 2020年3月18日08时至19日08时北京地区20个国家级气象站的过程阵风 (单位:级) (a. 观测,b. CMA-BJ_IUM,c. CMA-BJ_UPP,d. CMA-BJ_AFWA)
Figure 4. Gusts at 20 national weather stations in Beijing from 08:00 BT 18 to 08:00 BT 19 March 2020 (unit:level)(a. observations,b. CMA-BJ_IUM forecasts,c. CMA-BJ_UPP forecasts,d. CMA-BJ_AFWA forecasts)
图 5 观测和预报的2020年3月18日08时至19日08时汤河口 (54412)、朝阳 (54433) 和大兴 (54594) 站逐时阵风 (a. 观测,b. CMA-BJ_IUM,c. CMA-BJ_UPP,d. CMA-BJ_AFWA;实线为阵风数值,虚线为阵风峰值出现时刻)
Figure 5. Observations and forecasts of hourly gust at Tanghekou (54412),Chaoyang (54433),and Daxing (54594) stations from 08:00 BT 18 to 08:00 BT 19 March 2020 (a. observations,b. CMA-BJ_IUM,c. CMA-BJ_UPP,d. CMA-BJ_AFWA;Solid lines indicate the gust speed,dashed lines indicate the times when the maximum gust appeared)
图 6 观测和预报的大风开始阶段逐时阵风 (单位:级) (a—c. 2020年3月18日14、15和16时观测,d—f. 2020年3月18日11、12和13时CMA-BJ_IUM预报)
Figure 6. Observations and forecasts of hourly gust at the beginning of the gale (unit:level)(a─c. observations at 14:00 to 16:00 BT 18 March 2020,d─f. forecasts at 11:00 to 13:00 BT 18 March 2020 by CMA-BJ_IUM)
图 11 2020年5、8、11月和2021年2月北京地区20个国家级气象站逐时阵风预报 (a) 平均偏差和 (b) 平均绝对偏差 (红色、蓝色和绿色分别代表IUM、UPP和AFWA阵风诊断方案,对应箱线图显示了最小值、下四分位数、中位数、上四分位数和最大值;对应黑点代表平均值)
Figure 11. (a) Mean biases and (b) mean absolute biases of hourly gust forecasts at 20 national weather stations in Beijing in May,August and November of 2020 and February of 2021 (The red,blue and green colors indicate the results for the IUM,the UPP and the AFWA schemes,respectively;the boxes indicate the minimum,lower quartile,median,upper quartile,and maximum values;the black dots indicate the mean values)
图 12 不同季节北京地区20个国家级气象站逐时阵风预报的TS评分和BIAS评分 (a. 2020年5月,b. 2020年8月,c. 2020年11月,d. 2021年2月;实曲线对应TS评分,虚斜线和对角斜线对应BIAS评分,数值对应上、右坐标数字;圆点、三角和菱形分别对应不同阈值;红色、蓝色和绿色分别对应IUM、UPP和AFWA方案)
Figure 12. TS and BIAS scores of hourly gust forecasts at 20 national weather stations in Beijing (a. May 2020,b. August 2020, c. November 2020, d. February 2021; the solid curves correspond to TS score and the dashed slashes correspond to BIAS score; the dots,triangles and diamonds correspond to different thresholds;the red,blue and green colors correspond to the IUM,the UPP and the AFWA schemes,respectively)
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[1] 陈敏,陈明轩,范水勇. 2014. 雷达径向风观测在华北区域数值预报系统中的实时三维变分同化应用试验. 气象学报,72(4):658-677 doi: 10.11676/qxxb2014.070Chen M,Chen M X,Fan S Y. 2014. The real-time radar radial velocity 3DVar assimilation experiments for application to an operational forecast model in North China. Acta Meteor Sinica,72(4):658-677 (in Chinese) doi: 10.11676/qxxb2014.070 [2] 李永平,郑云霞,方平治. 2012. 2009年“莫拉克”台风登陆过程阵风特征分析. 气象学报,70(6):1188-1199 doi: 10.11676/qxxb2012.100Li Y P,Zheng Y X,Fang P Z. 2012. Analysis of the characteristics of gusts during the landing of Typhoon Morakot (2009). Acta Meteor Sinica,70(6):1188-1199 (in Chinese) doi: 10.11676/qxxb2012.100 [3] 卢冰,孙继松,仲跻芹等. 2017. 区域数值预报系统在北京地区的降水日变化预报偏差特征及成因分析. 气象学报,75(2):248-259 doi: 10.11676/qxxb2017.021Lu B,Sun J S,Zhong J Q,et al. 2017. Analysis of characteristic bias in diurnal precipitation variation forecasts and possible reasons in a regional forecast system over Beijing area. Acta Meteor Sinica,75(2):248-259 (in Chinese) doi: 10.11676/qxxb2017.021 [4] 徐海,邹捍,李鹏等. 2014. 林芝机场地面强风的统计特征及其对飞行安全的影响. 高原气象,33(4):907-915 doi: 10.7522/j.issn.1000-0534.2013.00055Xu H,Zou H,Li P,et al. 2014. Statistical analysis on strong surface wind and its impacts on flight safety at Nyingchi airport. Plateau Meteor,33(4):907-915 (in Chinese) doi: 10.7522/j.issn.1000-0534.2013.00055 [5] 杨扬,卢冰,王薇等. 2021. 基于WRF的积云对流参数化方案对中国夏季降水预报的影响研究. 气象学报,79(4):612-625 doi: 10.11676/qxxb2021.045Yang Y,Lu B,Wang W,et al. 2021. Impacts of cumulus parameterization schemes on the summertime precipitation forecast in China based on the WRF model. Acta Meteor Sinica,79(4):612-625 (in Chinese) doi: 10.11676/qxxb2021.045 [6] 尹尽勇,刘涛,张增海等. 2009. 冬季黄渤海大风天气与渔船风损统计分析. 气象,35(6):90-95 doi: 10.7519/j.issn.1000-0526.2009.06.012Yin J Y,Liu T,Zhang Z H,et al. 2009. Statistical analysis of the weather system types causing strong winds and fishery boat windage loss accidents in Bohai sea and Yellow sea in winter. Meteor Mon,35(6):90-95 (in Chinese) doi: 10.7519/j.issn.1000-0526.2009.06.012 [7] 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 [8] Adams N. 2004. A numerical modeling study of the weather in East Antarctica and the surrounding southern Ocean. Wea Forecast,19(4):653-672 doi: 10.1175/1520-0434(2004)019<0653:ANMSOT>2.0.CO;2 [9] Ágústsson H,Ólafsson H. 2009. Forecasting wind gusts in complex terrain. Meteor Atmos Phys,103(1):173-185 [10] Bartha I. 1994. Development of a decision procedure for forecasting maximum wind gusts associated with thunderstorms. Meteor Appl,1(2):103-107 [11] Bechtold P,Bidlot J R. 2009. Parametrization of convective gusts. ECMWF newsletter-meteorology section of ECMWF Newsletter no. 119. Shinfield Park,Reading:ECMWF,15-18 [12] 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 [13] 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 [14] Bukharov M V,Losev V M,Peskov B E. 2008. Automated estimation of the maximum speed of surface wind gusts by taking into account information obtained from the geostationary satellite. Russ Meteor Hydrol,33(12):753-759 doi: 10.3103/S1068373908120017 [15] Chan P W,Lam C C,Cheung P. 2011. Numerical simulation of wind gusts in intense convective weather and terrain-disrupted airflow. Atmósfera,24(3):287-309 [16] Chen F,Dudhia J. 2001. Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part Ⅰ:Model im- plementation and sensitivity. Mon Wea Rev,129(4):569-585 doi: 10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2 [17] Creighton G, Kuchera E, Adams-Selin R, et al. 2014. AFWA diagnostics in WRF. Offutt AFB, NE, USA: Air Force Weather Agency, 6-7 [18] ECMWF. 2018. IFS Documentation─Cy45r1- Part Ⅳ:Physical Processes. Reading,England:ECMWF,52pp [19] Ek M B,Mitchell K E,Lin Y,et al. 2003. Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res,108(D22):8851 [20] Geerts B. 2001. Estimating downburst-related maximum surface wind speeds by means of proximity soundings in New South Wales,Australia. Wea Forecast,16(2):261-269 doi: 10.1175/1520-0434(2001)016<0261:EDRMSW>2.0.CO;2 [21] Goyette S,Brasseur O,Beniston M. 2003. Application of a new wind gust parameterization:Multiscale case studies performed with the Canadian regional climate model. J Geophys Res,108(D13):4374 [22] Hong S Y,Noh Y,Dudhia J. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Wea Rev,134(9):2318-2341 doi: 10.1175/MWR3199.1 [23] Iacono M J,Delamere J S,Mlawer E J,et al. 2008. Radiative forcing by long-lived greenhouse gases:Calculations with the AER radiative transfer models. J Geophys Res,113(D13):D13103 doi: 10.1029/2008JD009944 [24] Jiménez P A,Dudhia J,González-Rouco J F,et al. 2012. A revised scheme for the WRF surface layer formulation. Mon Wea Rev,140(3):898-918 doi: 10.1175/MWR-D-11-00056.1 [25] Kuchera E L,Parker M D. 2006. Severe convective wind environments. Wea Forecast,21(4):595-612 doi: 10.1175/WAF931.1 [26] Kuhlman C J. 2006. Evaluation of convective wind forecasting methods during high wind events. Monterey:Naval Postgraduate School,13-16 [27] Kurbatova M,Rubinstein K,Gubenko I,et al. 2018. Comparison of seven wind gust parameterizations over the European part of Russia. Adv Sci Res,15:251-255 doi: 10.5194/asr-15-251-2018 [28] LaCroix K W. 2002. Application of the wind gust estimate and comparison to the AFWA MM5 wind gust algorithm. Wright-Patterson Air Force Base:Air Force Institute of Technology,1-102 [29] Lee Y H,Lee G,Joo S,et al. 2018. Observational study of surface wind along a sloping surface over mountainous terrain during winter. Adv Atmos Sci,35(3):276-284 doi: 10.1007/s00376-017-7075-5 [30] McCann D W. 1994. WINDEX—A new index for forecasting microburst potential. Wea Forecast,9(4):532-541 doi: 10.1175/1520-0434(1994)009<0532:WNIFFM>2.0.CO;2 [31] Nakamura K,Kershaw R,Gait N. 1996. Prediction of near-surface gusts generated by deep convection. Meteor Appl,3(2):157-167 [32] 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 [33] Pinto J G,Neuhaus C P,Krüger A,et al. 2009. Assessment of the wind gust estimate method in mesoscale modelling of storm events over West Germany. Meteor Z,18(5):495-506 doi: 10.1127/0941-2948/2009/0402 [34] Schreur B W,Geertsema G. 2008. Theory for a TKE based parameterization of wind gusts. HIRLAM Newsl,(54):177-188 [35] Schulz J P,Heise E. 2003. A new scheme for diagnosing near-surface convective gusts. COSMO Newsl,(3):221-225 [36] Schulz J P. 2008. Revision of the turbulent gust diagnostics in the COSMO model. COSMO Newsl,(8):17-22 [37] Sheridan P. 2011. Review of techniques and research for gust forecasting and parameterization. Forecasting Research Technical Report 570. Exeter, UK: UK Met Office [38] Sheridan P. 2018. Current gust forecasting techniques,developments and challenges. Adv Sci Res,15:159-172 doi: 10.5194/asr-15-159-2018 [39] Thompson G,Field P R,Rasmussen R M,et al. 2008. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part Ⅱ:Implementation of a new snow parameterization. Mon Wea Rev,136(12):5095-5115 doi: 10.1175/2008MWR2387.1 [40] Vogelezang D H P,Holtslag A A M. 1996. Evaluation and model impacts of alternative boundary-layer height formulations. Bound Layer Meteor,81(3):245-269 [41] Walser A,Arpagaus M,Appenzeller C,et al. 2006. The impact of moist singular vectors and horizontal resolution on short-range limited-area ensemble forecasts for two European winter storms. Mon Wea Rev,134(10):2877-2887 doi: 10.1175/MWR3210.1 [42] Wilt B A,Wang W. 2020. IBM GRAF─scale-aware convective forecast evaluation and improvements∥Proceedings of the 30th Conference on Weather Analysis and Forecasting/26th Conference on Numerical Weather Prediction. Boston,MA:AMS,2020 -