Experiment and Verification of the Convective-Scale Ensemble Forecast Based on BGM

MA Shenjia; CHEN Chaohui; HE Hongrang; LI Xiang; LI Yi

doi:10.7522/j.issn.1000-0534.2017.00073

Plateau Meteorology >

2018 , Vol. 37 >Issue 2: 495 - 504

DOI: https://doi.org/10.7522/j.issn.1000-0534.2017.00073

Experiment and Verification of the Convective-Scale Ensemble Forecast Based on BGM

MA Shenjia ,
CHEN Chaohui ,
HE Hongrang ,
LI Xiang ,
LI Yi

Expand

College of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, Jiangsu, China

Received date: 2017-06-07

Online published: 2018-04-28

Fold

Abstract

Based on breeding of growing modes (BGM) method, an ensemble forecast experiment was tested for a strong squall line considering the highly non-linear feature and detailed forecast requirement in convective-scale weather systems. The probability matched mean (PMM) method was used to analysis contrastively the results of the ensemble forecast, and the effect of precipitation forecast was verified by the bias score and equitable threat score (ETS). The results indicate that BGM method applied to the convective-scale ensemble forecast could generate the rapid growth perturbations that represent atmospheric uncertainties. The results of the ensemble forecast were more accurate than the control forecast, the traditional ensemble mean (EM) method was more accurate on the smaller intensity forecast, and the PMM method was more skillful at forecasting the large intensity events. The results of the verification in precipitation forecast demonstrated that the EM method had the highest forecasting skill of the small magnitude precipitation. And the PMM method had obvious advantages in the forecasting techniques of extreme precipitation events. Convective-scale ensemble forecast can improve the forecasting skill of precipitation forecast, and provide a guidance for the high-impact convective weather events.

Key words： Convective-scale; ensemble forecast; BGM; Probability Matched; verification

Cite this article

MA Shenjia , CHEN Chaohui , HE Hongrang , LI Xiang , LI Yi . Experiment and Verification of the Convective-Scale Ensemble Forecast Based on BGM[J]. Plateau Meteorology, 2018 , 37(2) : 495 -504 . DOI: 10.7522/j.issn.1000-0534.2017.00073

References

[1]Berenguer M, Surcel M, Zawadzki I, et al, 2012. The diurnal cycle of precipitation from continental radar mosaics and numerical weather prediction models. Part Ⅱ:Intercomparison among numerical models and with nowcasting[J]. Mon Wea Rev, 140(8):2689-2705.
[2]Bishop C H, Toth Z, 1999. Ensemble transformation and adaptive observations[J]. J Atmos Sci, 56(11):1748-1765.
[3]Bishop C H, Etherton B J, Majumdar S J, 2001. Adaptive sampling with the ensemble transform Kalman filter. Part Ⅰ:Theoretical aspects[J]. Mon Wea Rev, 129(3):420-436.
[4]Clark A J, Gallus W, Xue M, et al, 2009. A comparison of precipitation forecast skill between small convection-allowing and large convection-parameterizing ensembles[J]. Wea Forecasting, 24(4):1121-1140.
[5]Clark A J, Weiss S J, Kain J S, et al, 2012. An overview of the 2010 hazardous weather testbed experimental forecast program spring experiment[J]. Bull Amer Meteor Soc, 93(1):55-74.
[6]Ebert E E, 2001. Ability of a poor man's ensemble to predict the probability and distribution of precipitation[J]. Mon Wea Rev, 129(10):2461-2480.
[7]Kong F, Xue M, Thomas K, et al, 2008. Real-time storm-scale ensemble forecast experiment -analysis of 2008 spring experiment data[C]//24th Conference on Several Local Storms, Amer Meteor Soc, Savannah.
[8]Kong F, Xue M, Thomas K W, et al, 2009. A realtime storm-scale ensemble forecast system: 2009 spring experiment[C]//23th Conference on Weather Analysis and Forecasting and 19th Conference on Numerical Weather Prediction, Amer Meteor Soc, Omaha, Nebraska.
[9]Lorenz E N, 1963. Deterministic nonperiodic flow[J]. J Atmos Sci, 20(2):130-141.
[10]Schwartz C S, Romine G S, Smith K R, et al, 2014. Characterizing and optimizing precipitation forecasts from a convection-permitting ensemble initialized by a mesoscale ensemble Kalman Filter[J]. Wea Forecasting, 29(6):1295-1318.
[11]Schwartz C S, Romine G S, Weisman M L, et al, 2015a. A real-time convection-allowing ensemble prediction system initialized by mesoscale ensemble Kalman Filter analyses[J]. Wea Forecasting, 30(5):1158-1181.
[12]Schwartz C S, Romine G S, Sobash R A, et al, 2015b. NCAR's experimental real-time convection-allowing ensemble prediction system[J]. Wea Forecasting, 30(5):1645-1654.
[13]Toth Z, Kalnay E, 1993. Ensemble forecasting at Nmc:the generation of perturbations[J]. Bull Amer Meteor Soc, 74(12):2317-2330.
[14]Toth Z, Kalnay E, 1997. Ensemble forecasting at NCEP and the breeding method[J]. Mon Wea Rev, 125(12):3297-3319.
[15]Xue M, Kong F, Weber D, et al, 2007. CAPS realtime storm-scale ensemble and high-resolution forecasts as part of the NOAA hazardous weather testbed 2007 spring experiment[C]//22th Conference on Weather Analysis and Forecasting and 18th Conference on Numerical Weather Prediction, Amer Meteor Soc, Park City, UT.
[16]Xue M, Kong F, Thomas K W, et al, 2010. CAPS realtime storm scale ensemble and high resolution forecasts for the NOAA hazardous weather testbed 2010 spring experiment[C]//25th Conference on Several Local Storms, Amer Metor Soc, Denver, Colorado.
[17]Du J, 2002. Present situation and prospects of ensemble numerical prediction[J]. J Appl Meteor Sci, 13(1):16-28. 杜钧, 2002.集合预报的现状和前景[J].应用气象学报, 13(1):16-28.
[18]Cai Y C, Min J Z, Zhuang X R, 2017. Comparison of different stochastic physics perturbation schemes on a stormscale ensemble forecast in a heavy rain event[J]. Plateau Meteor, 36(2):407-423. DOI:10.7522/j.issn. 1000-0534.2016.00024. 蔡沅辰, 闵锦忠, 庄潇然, 2017.不同随机物理扰动方案在一次暴雨集合预报中的对比研究[J].高原气象, 36(2):407-423.
[19]Gao F, Min J Z, Kong F Y, 2010. Experiment of the storm-scale ensemble forecast based on breeding of growing mode[J]. Plateau Meteor, 29(2):429-436. 高峰, 闵锦忠, 孔凡铀, 2010.基于增长模繁殖法的风暴尺度集合预报试验[J].高原气象, 29(2):429-436.
[20]Wang C X, Yao J Q, 2006. The establishment and experiment of Shanghai regional numerical ensemble forecast system[J]. Scientia Meteor Sinica, 26(2):127-134. 王晨稀, 姚建群, 2006.上海区域数值预报模式集合预报系统的建立与试验[J].气象科学, 26(2):127-134.
[21]Wang C X, Yao J Q, 2008. Ensemble forecasting of a local short-lived severe precipitation[J]. Plateau Meteor, 27(6):1299-1239. 王晨稀, 姚建群, 2008.对一次局地短时强降水过程的集合预报研究[J].高原气象, 27(6):1229-1239.
[22]Wang Y, Yan Z H, 2007. Effect of different verification schemes on precipitation verification and assessment conclusion[J]. Meteor Mon, 33(12):53-61. 王雨, 闫之辉, 2007.降水检验方案变化对降水检验评估效果的影响分析[J].气象, 33(12):53-61.
[23]Zhuang X R, Min J Z, Cai Y C, et al, 2016. Convective-scale ensemble prediction experiments under different large-scale forcing with consideration of uncertainties in initial and lateral boundary condition[J]. Acta Meteor Sinica, 74(2):244-258. 庄潇然, 闵锦忠, 蔡沅辰, 等, 2016.不同大尺度强迫条件下考虑初始场与侧边界条件不确定性的对流尺度集合预报试验[J].气象学报, 74(2):244-258.
[24]Zhuang X R, Min J Z, Wu T J, et al, 2017. Development mechanism of multi-scale perturbation based on different perturbation methods in convection-allowing ensemble prediction[J]. Plateau Meteor, 36(3):811-825. DOI:10.7522/j.issn. 1000-0534.2016.00049. 庄潇然, 闵锦忠, 武天杰, 等, 2017.风暴尺度集合预报中不同初始扰动的多尺度发展特征研究[J].高原气象, 36(3):811-825.

Options

Outlines

模态框（Modal）标题

Abstract

Cite this article

References