南京大学学报(自然科学版) ›› 2012, Vol. 48 ›› Issue (6): 677–688.

• • 上一篇    下一篇

WRF模式对中国东南地区的多参数化短期集合预报试验*

李嘉鹏,汤剑平**

  

  • 出版日期:2015-07-09 发布日期:2015-07-09
  • 作者简介:(南京大学大气科学学院,南京,210093)
  • 基金资助:
    国家重点基础研究发展计划项日(2011CB95204),中国气象局公益性行业专项(GYHY200706033)

Experiment of WRF multrphysics short range ensemble forecasts
in southeastern China

Li Jia-Peng,Tang Jian-Ping
  

  • Online:2015-07-09 Published:2015-07-09
  • About author:(School of Atmospheric Sciences,Nanjing University,Naniing,210093,China)

摘要: 木文采用物理过程扰动方法,针对中国东南地区建立了基于Weather Research and Forecas- ting( WRF)模式的短期集合预报系统.利用美国国家环境预报中心全球数据同化系统的高空资料和预报区域内1000多个站点(包括基准站、基木站和一般站)的地面观测资料对短期集合预报系统2010年5,6月份的预报结果进行了检验,分析了物理过程参数化方案和集合平均方法对气象要素预报效果的影响.结果表明:基于WRF模式的短期集合预报系统对我国东南地区高空及地面要素有一定的预报能
力.从单个模式成员和集合平均的结果来看,在整个预报时段(60 h)内都能较好地预报;不同高度上的气象要素和不同量级的降水对物理过程参数化方案的敏感性不同,预报效果也存在差异.集合平均方法对于大部分气象要素场的预报效果超过单个模式成员.

Abstract: Using perturbed physics method ,a short range ensemble forecasting system based on Weather Research and Forecasting(WRF)modcl was built for southeastern China.The forecasted results of May and June 2010 were verified against the upper-level fields from National Centers for Environmental Prediction Ulobal Data Assimilation System and surface observations from more than 1000 stations(including base stations, basic stations and general sta- tions)in the forecast domain. An analysis of how physical parameterization schemes and ensemble mean approach af- feet the forecasting performance was done.The results showed that WRF model performed fairly well in forecasting the meteorological fields in southeastern China. For the whole forecast period(60 h),the ensemble forecast system had certain skill in precipitation forecasting,judging from the performance of model members and ensemble mean. Meteorological elements at different pressure levels and precipitation at different thresholds were different in sensi- tivity to physical parameterization schemes and forecasting performance. For most meteorological fields,ensemble mean performed better than single model member.

[1]Richardson L F. Weather prediction by numeric process.The 2nd Edition. Cambridge;Cambridge University Press,2007,1一236.
[2]Lorenz E N. Deterministic nonperiodic flow. Jour-nal of the Atmospheric Sciences, 1963,20:130~141
[3]Epstein E S. Stochastic dynamic prediction.Tel-lus,1969,21:739一759.
[4]Leith C E.Theorctical skill of Monte Carlo forte casts. Monthly Weather Review, 1974,102:409 ~418.
[5]Tradon M S, Kalnay E. Operational ensemble prediction at National Meteorological Center; Practical aspects. Weather and Forecasting, 1993,8:379一398.
[6]Molteni F, Buizza R, Palmer T N, et al. The ECM WF ensemble prediction system; Methodology and verification. Quarterly Journal of the Royal Meteoro-
logical Society, 1996,122;73一119.
[7]Toth Z,Kalnay E. Ensemble forecasting at NMC;The generation of perturbations. Bulletin of the American Meteorological Society,1993,79;2317一2330.
[8]Houtekamer P L and Derome J. Methods for en semble prediction. Monthly Weather Review 1995,123.2181一2196.
[9]Houtekamcr P L, Lefaivre L, Derome J,et al. A system simulation approach to ensemble predic- tion. Monthly Weather Review, 1996,124:1225~1242.
[10]Buizza R,Miller M,Palmer T N. Stochastic represen- tation of model uncertainties in the ECMWF ensemble prediction system. Quarterly Journal of the Royal Me- teorological Society,l999,125;2887一2908.
[11]Stensrud D J,Bao J W,Warner T.Using initial condition and model physics perturbation in short range ensemble simulations of mesoscalc
connective systems. Monthly Weather Review, 2000,128:2077一2107.
[12]Brooks H E,Zi-acton M S,Stensrud D J,et al. Short range ensemble forecasting;Report from a workshop, 25一27 July 1994. Bulletin of the American Meteoro-
logical Society,1995, 76:1617一1624.
[13]Stensrud D J,Brooks H E,IW J,et al. Using en sembles for short range forecasting. Monthly Weather Review, 1999,127:433~446.
[14]Chien F C,Liu Y C,Jou B J D. MM5 ensemble mean forecasts in the Taiwan area for the 2003 Mei-Yu season. Weather and Forecasting, 2006,
21:1006一1023.
[15]Zhao M,Jiang Y,Tang J P,et al. Effects of land surface process on heavy rain; A new RIEMS model. Journal of Nanjing University(Natural
Sciences),2003,39(3);370 -381.(赵鸣,江勇,汤剑平等.用新RIFMS模式研究陆面过程对暴雨的影响.南京大学学报(自然科学),2003,39 (3):370一381).
[16]Chen J,Xue J S, Yan H.The impact of physics parameterization schemes on mesoscalc heavy rainfall simulation. Acta Mctcorologica Sinica,
2003,61(2):203一218.(陈静,薛纪善,颜宏.物理过程参数化方案对中尺度暴雨数值模拟影响的研究.气象学报,2003,61(2);203-218).
[17]Chen J,Xue J S, Yan H.The uncertainty of me- soscale numerical prediction of south China heavy rain and the ensemble simulations. Acta Meteoro-
logica Sinica,2003,61(4):432一446.(陈静,薛纪善,颜宏.华南中尺度暴雨数值预报的不确定性与集合预报试验.气象学报,2003,61(4); 432一446).
[18]Chen J,Xue J S, Yan H. A new initial perturba- tion method of ensemble mesoscalc heavy rain prediction. Chinese Journal of Atmospheric Sci-
ences,2005,29(5):717一726.(陈静,薛纪善,颜宏.一种新型的中尺度暴雨集合预报初值扰动方法研究.大气科学,2005,29(5);717-726).
[19]Wang C X, Duan Y H. Experiment and research of short- range ensemble forecasting techniques in fore- casting Meiyu Precipitation. Journal of Applied Me-
teorological Science, 2003 , 14 ( 1) ; 69 -78.(王晨稀,端义宏.短期集合预报技术在梅雨降水预报中的试验研究.应用气象学报,2003,14(1);69-78).
[20]Wang C X. Experiments of short range ensemble precipitation probability forecasts. Journal of Applied Meteorological Science, 2005 , 16 ( 1) ; 78 -88.(王晨
稀.短期集合降水概率预报试验.应用气象学报,2005,16(1):78一88).
[21]Wang C X, Yao J Q, Liang X D. The establish- ment and verification of the operational ensemble forecast system for Shanghai region precipitation.
Journal of Applied Meteorological Science, 2007,18 (2) ; 173-180.(王晨稀,姚建群,梁旭东.上海区域降水集合预报系统的建立与运行结果的检验.
应用气象学报,2007,18(2);173-180).
[22]Wang C X, Yao J Q, Liang X D. The comparing experiment of improving the operational ensemble prediction system for Shanghai region precipitati-
on. Scientia Meteorologica Sinica, 2007,27(5): 481-487.(王晨稀,姚建群,梁旭东.上海区域降水集合预报系统改进的对比试验.气象科学,2007,27(5):481一487).
[23]Skamarock W C,Klemp J B, Dudhia J,et al. A description of the Advanced Research WRF ver- lion 3. Boulder; NCAR Technical Notc,2008,65-78.
[24]Gilbert G K. Finley’s tornado predictions. American Meteorological Journal, 1884,1:166一172.





No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!