MCC降水过程集合预报不同物理过程扰动方案的对比试验研究
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摘要
利用WRF模式,从模式的不确定性角度来构造中尺度的集合预报,重点对比分析了不同物理参数化方案、物理过程随机扰动方案、积云对流参数化敏感参数扰动方案对中尺度对流复合体降水集合预报的影响。试验结果表明:3种物理过程扰动方法都可以反映中尺度对流复合体降水预报的不确定性特征,其预报效果比控制预报好。物理过程随机扰动方案集合平均的降水落区及强度最接近实况,并且其降水的ETS评分要高于其他2种方案。从均方根误差与离散度的角度来看,3种方案中物理过程随机扰动的均方根误差要小于其他2种方案,而其离散度要大于其他2种方案,物理过程随机扰动方案要优于其他2种方案。
The Weather Research and Forecasting( WRF) mesoscale numerical prediction model w as used to construct mesoscale ensemble forecast from the aspects of model uncertainty.The focus w as to compare and analyze the influence on precipitation forecast of mesoscale convection complex( M CC) exerted by the three methods,w hich w ere different physical parameterization method,the method of disturbing sensitive parameters in cumulus convection parameterization scheme and the stochastic physical perturbation method. The results show ed that all of the three ensemble forecast methods could reflect the uncertainty of M CC precipitation forecast and they performed better than control forecast.Compared to the other tw o methods,the spatial distribution and intensity of ensemble mean 24-hour accumulated rainfall by stochastic physical perturbation method w ere closer to the reality. The 24-hour rainfall ETS of stochastic physical perturbation method w as better than the other tw o methods. In terms of root mean square error( RM SE),the stochastic physical perturbation method had smaller RM SEs than the other tw o methods,w hile its dispersion w as larger than the other tw o.In all,the stochastic physical perturbation method w as superior to the other tw o methods.
The Weather Research and Forecasting( WRF) mesoscale numerical prediction model w as used to construct mesoscale ensemble forecast from the aspects of model uncertainty.The focus w as to compare and analyze the influence on precipitation forecast of mesoscale convection complex( M CC) exerted by the three methods,w hich w ere different physical parameterization method,the method of disturbing sensitive parameters in cumulus convection parameterization scheme and the stochastic physical perturbation method. The results show ed that all of the three ensemble forecast methods could reflect the uncertainty of M CC precipitation forecast and they performed better than control forecast.Compared to the other tw o methods,the spatial distribution and intensity of ensemble mean 24-hour accumulated rainfall by stochastic physical perturbation method w ere closer to the reality. The 24-hour rainfall ETS of stochastic physical perturbation method w as better than the other tw o methods. In terms of root mean square error( RM SE),the stochastic physical perturbation method had smaller RM SEs than the other tw o methods,w hile its dispersion w as larger than the other tw o.In all,the stochastic physical perturbation method w as superior to the other tw o methods.
引文
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钱卓蕾,郭品文,2016.2013年浙江两次汛期暴雨过程对比分析[J].大气科学学报,39(2):253-259.Qian Z L,Guo P W,2016.Comparative analysis of two torrential rainstorms that occurred in Zhejiang in 2013[J].Trans Atmos Sci,39(2):253-259.(in Chinese).
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谭燕,陈德辉,2007.基于非静力模式物理扰动的中尺度集合预报试验[J].应用气象学报,18(3):396-406,418.Tan Y,Chen D H,2007.Meso-scale ensemble forecasts on physical perturbation using a non-hydrostatic model[J].J Appl Meteor Sci,18(3):396-406,418.(in Chinese).
Zhang F Q,Odins A M,Nielsen-Gammon J W,2006.Mesoscale predictability of an extreme warm-season precipitation event[J].Wea Forecasting,21(2):149-166.
张涵斌,陈静,智协飞,等,2014.基于GRAPES_Meso 的集合预报扰动方案设计与比较[J].大气科学学报,37(3)276-284.Zhang H B,Chen J,Zhi X F,et al.,2014.Design and comparison of perturbation schemes for GRAPES_Meso based ensemble forecast[J].Trans Atmos Sci,37:376-284.(in Chinese).
张涵斌,智协飞,陈静,等,2017.区域集合预报扰动方法研究进展综述[J].大气科学学报,40(2):145-157.Zhang H B,Zhi X F,Chen J,et al.,2017.Achievement of perturbation methods for regional ensemble forecast[J].Trans Atmos Sci,40(2):145-157.(in Chinese).
赵思雄,孙建华,2013.近年来灾害天气机理和预测研究的进展[J].大气科学,37(2):297-312.Zhao S X,Sun J H,2013.Study on mechanism and prediction of disastrous weathers during recent years[J].Chin J Atmos Sci,37(2):297-312.(in Chinese).
Zhu J S,Kong F Y,Lei H C,2013.A regional ensemble forecast system for stratiform precipitation events in the northern China Region.Part Ⅱ:seasonal evaluation for summer 2010[J].Adv Atmos Sci,30(1):15-28.
Buizza R,Miller M,Palmer T,1999.Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System[J].Quart J Roy Meteor Soc,125(560):2887-2908.
曹萍萍,闵锦忠,陈耀登,2018.一种根据湿对流区域时空分布调整的BGB扰动改进方案[J].大气科学学报,41(6):850-860.Cao P P,Min J Z,Chen Y D,2018.An improved breeding of the growing mode based on spatio-temporal distribution of moist convection zone[J].Trans Atmos Sci,41(6):850-860.(in Chinese).
陈静,薛纪善,颜宏,2003.华南中尺度暴雨数值预报的不确定性与集合预报试验[J].气象学报,61(4):432-446.Chen J,Xue J S,Yan H,2003.The uncertainty of mesoscale numerical prediction of South China heavy rain and the ensemble simulations[J].Acta Meteorologica Sinica,61(4):432-446.(in Chinese).
Eckel F A,Mass C F,2005.Aspects of effective mesoscale,short-range ensemble forecasting[J].Wea Forecasting,20(3):328-350.
Grell G A,Dévényi D,2002.A generalized approach to parameterizing convection combining ensemble and data assimilation techniques[J].Geophys Res Lett,29(14):38-1-38-4.
Houtekamer P L,Lefaivre L,Derome J,et al.,1996.A system simulation approach to ensemble prediction[J].Mon Wea Rev,124(6):1225-1242.
Kain J S,Fritsch J M,1990.A one-dimensional entraining/detraining plume model and its application in convective parameterization[J].J Atmos Sci,47(23):2784-2802.
Kain J S,Fritsch J M,1992.The role of the convective?trigger function?in numerical forecasts of mesoscale convective systems[J].Meteor Atmos Phys,49(1/2/3/4):93-106.
Leith C E,1974.Theoretical skill of monte carlo forecasts[J].Mon Wea Rev,102(6):409-418.
李刚,王铁,谭言科,等,2010.WRF3.0参数化敏感性及集合预报试验[J].解放军理工大学学报,11(1):90-96.Li G,Wang Y,Tan Y K,et al.,2010.Impact of parameterization schemes in WRF3.0 model on numerical simulation of rainstorm and experiment of ensemble forecast[J].Journal of PLA University of Science and Technology,11(1):90-96.(in Chinese).
钱卓蕾,郭品文,2016.2013年浙江两次汛期暴雨过程对比分析[J].大气科学学报,39(2):253-259.Qian Z L,Guo P W,2016.Comparative analysis of two torrential rainstorms that occurred in Zhejiang in 2013[J].Trans Atmos Sci,39(2):253-259.(in Chinese).
Stensrud D J,Bao J W,Warner T T,2000.Using initial condition and model physics perturbations in short-range ensemble simulations of mesoscale convective systems[J].Mon Wea Rev,128(7):2077-2107.
谭伟才,钟玮,陆汉城,等,2018.致洪暴雨过程中尺度涡旋的结构和准平衡特征分析[J].大气科学学报,41(1):25-35.Tan W C,Zhong W,Lu H C,et al.,2018.Structure and quasi-balanced feature analyses of the mesoscale vortex during a flash-flood-producing rainstorm process[J].Trans Atmos Sci,41(1):25-35.(in Chinese).
谭燕,陈德辉,2007.基于非静力模式物理扰动的中尺度集合预报试验[J].应用气象学报,18(3):396-406,418.Tan Y,Chen D H,2007.Meso-scale ensemble forecasts on physical perturbation using a non-hydrostatic model[J].J Appl Meteor Sci,18(3):396-406,418.(in Chinese).
Zhang F Q,Odins A M,Nielsen-Gammon J W,2006.Mesoscale predictability of an extreme warm-season precipitation event[J].Wea Forecasting,21(2):149-166.
张涵斌,陈静,智协飞,等,2014.基于GRAPES_Meso 的集合预报扰动方案设计与比较[J].大气科学学报,37(3)276-284.Zhang H B,Chen J,Zhi X F,et al.,2014.Design and comparison of perturbation schemes for GRAPES_Meso based ensemble forecast[J].Trans Atmos Sci,37:376-284.(in Chinese).
张涵斌,智协飞,陈静,等,2017.区域集合预报扰动方法研究进展综述[J].大气科学学报,40(2):145-157.Zhang H B,Zhi X F,Chen J,et al.,2017.Achievement of perturbation methods for regional ensemble forecast[J].Trans Atmos Sci,40(2):145-157.(in Chinese).
赵思雄,孙建华,2013.近年来灾害天气机理和预测研究的进展[J].大气科学,37(2):297-312.Zhao S X,Sun J H,2013.Study on mechanism and prediction of disastrous weathers during recent years[J].Chin J Atmos Sci,37(2):297-312.(in Chinese).
Zhu J S,Kong F Y,Lei H C,2013.A regional ensemble forecast system for stratiform precipitation events in the northern China Region.Part Ⅱ:seasonal evaluation for summer 2010[J].Adv Atmos Sci,30(1):15-28.
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