高原气象

高原气象 >

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

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

论文

基于BGM的对流尺度集合预报试验及其检验

  • 马申佳 ,
  • 陈超辉 ,
  • 何宏让 ,
  • 李湘 ,
  • 李毅
展开
  • 国防科技大学气象海洋学院, 江苏 南京 211101

收稿日期: 2017-06-07

  网络出版日期: 2018-04-28

基金资助

北极阁开放研究基金项目（NJCAR2016MS02）；国家重点基础研究发展计划（973计划）项目（2017YFC1501800）；国家自然科学基金项目（41205073，41675007）

收起

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

摘要

基于增长模繁殖法，考虑对流尺度高度非线性特征和精细化预报要求，对一次强飑线天气过程进行了集合预报试验，引入概率匹配平均法对集合预报结果进行对比分析，并通过偏差和公平技巧评分对降水进行了预报效果检验。试验结果表明，BGM法应用到对流尺度集合预报中能够生成代表大气不确定性的快速增长扰动。集合预报结果相比控制预报更加准确，传统集合平均对较小降水强度的预报更加准确，概率匹配平均法对大量级降水的预报能力明显占优。降水评分检验表明，集合平均对小量级降水的预报技巧最高，概率匹配平均法对极端降水事件的预报技巧有明显优势。对流尺度集合预报能够提高降水预报技巧，并对高影响对流天气事件的预报有指导意义。

关键词： 对流尺度; 集合预报; BGM; 概率匹配平均法; 检验

本文引用格式

马申佳 , 陈超辉 , 何宏让 , 李湘 , 李毅 . 基于BGM的对流尺度集合预报试验及其检验[J]. 高原气象, 2018 , 37(2) : 495 -504 . DOI: 10.7522/j.issn.1000-0534.2017.00073

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

参考文献

[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]//24<sup>th</sup> 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]//23<sup>th</sup> Conference on Weather Analysis and Forecasting and 19<sup>th</sup> 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]//22<sup>th</sup> Conference on Weather Analysis and Forecasting and 18<sup>th</sup> 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]//25<sup>th</sup> 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.<br/>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.<br/>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.<br/>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.<br/>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.<br/>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.<br/>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.<br/>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.<br/>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
文章导航

/

〈 〉

本系统由北京玛格泰克科技发展有限公司设计开发 技术支持：support@magtech.com.cn