GRAPES全球集合预报初始条件及模式物理过程不确定性方法研究
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摘要
为描述GRAPES全球模式初始条件的不确定性,基于适合集合预报应用的GRAPES全球奇异向量技术,依据大气初始误差符合正态分布的特征,采用高斯取样奇异向量来构造全球集合预报初始扰动,在此基础上建立了GRAPES全球集合预报系统(GRAPES-GEPS)。利用GRAPES全球同化分析场,对采用初始扰动的GRAPES-GEPS连续试验预报结果进行检验和分析。结果表明:GRAPES-GEPS中高度场、风场及温度场预报的集合离散度能有效快速增加,集合平均均方根误差与集合离散度的关系合理;相对控制预报的均方根误差,集合平均的预报优势在预报中期非常显著。为进一步体现GRAPES-GEPS中模式物理过程的不确定性,发展了模式物理过程倾向随机扰动技术(SPPT)。试验结果表明:SPPT方案的应用有效提高了GRAPES-GEPS在南、北半球和热带地区等压面要素预报的集合离散度,同时一定程度减小了集合平均误差,进而改进了集合平均误差与集合离散度的关系,其中SPPT方案在热带地区的改进最为显著。本文发展的基于奇异向量的初始扰动方法和模式扰动SPPT方案在中国气象局2018年12月业务化运行的GRAPES-GEPS中得到了应用。
According to the normal distribution characteristics of initial atmospheric errors,in order to describe the uncertainties in the initial conditions of the GRAPES global model,this paper used the Gausssian sampling method to construct initial perturbations for GRAPES global ensemble prediction system( GRAPE-GEPS) from GRAPES singular vectors( SVs),w hich are specifically designed for ensemble forecasting.Using the global assimilation analysis field of GRAPES,this paper carried out the ensemble experiments of GRAPES-GEPS w ith SV-based initial perturbations.Results show that the grow ths of ensemble spreads of geopotential height,w ind speed and temperature increase quickly,and the grow th rate remains stable during the forecast range.The small distance betw een ensemble mean RM SE and ensemble spread indicates that there are reasonable spread-skill relations in the GRAPES-GEPS.Compared w ith RM SE of unperturbed control forecast,there are clear advantages observed in RM SE of ensemble mean,particularly in the middle range forecasts. The stochastically perturbed parametrization tendency( SPPT) scheme is used to represent the model uncertainties in the GRAPES-GEPS.It can be seen that the inclusion of the SPPT scheme improves the ensemble spreads of geopotential height,temperature and w ind speed at each forecast lead time in the Northern( Southern) Hemispheric extra-tropics and the tropics in particular,and improves the spread-skill relations as w ell.The SV-based initial perturbations and SPPT scheme have been used in the operational GRAPES-GEPS at China M eteorological Administration since December 2018.
According to the normal distribution characteristics of initial atmospheric errors,in order to describe the uncertainties in the initial conditions of the GRAPES global model,this paper used the Gausssian sampling method to construct initial perturbations for GRAPES global ensemble prediction system( GRAPE-GEPS) from GRAPES singular vectors( SVs),w hich are specifically designed for ensemble forecasting.Using the global assimilation analysis field of GRAPES,this paper carried out the ensemble experiments of GRAPES-GEPS w ith SV-based initial perturbations.Results show that the grow ths of ensemble spreads of geopotential height,w ind speed and temperature increase quickly,and the grow th rate remains stable during the forecast range.The small distance betw een ensemble mean RM SE and ensemble spread indicates that there are reasonable spread-skill relations in the GRAPES-GEPS.Compared w ith RM SE of unperturbed control forecast,there are clear advantages observed in RM SE of ensemble mean,particularly in the middle range forecasts. The stochastically perturbed parametrization tendency( SPPT) scheme is used to represent the model uncertainties in the GRAPES-GEPS.It can be seen that the inclusion of the SPPT scheme improves the ensemble spreads of geopotential height,temperature and w ind speed at each forecast lead time in the Northern( Southern) Hemispheric extra-tropics and the tropics in particular,and improves the spread-skill relations as w ell.The SV-based initial perturbations and SPPT scheme have been used in the operational GRAPES-GEPS at China M eteorological Administration since December 2018.
引文
Barkmeuer J,Buizza R,Palmer T N,1999.3D-Var Hessian singular vectors and their potential use in ECMWF ensemble prediction system[J].Quart J Roy Meteor Soc,125(558):2333-2351.
Bowler N E,Arribas A,Mylne K R,et al.,2008.The MOGREPS short-range ensemble prediction system[J].Quart J Roy Meteor Soc,134(632):703-722.
Buehner M,McTaggart-Cowan R,Beaulne A,et al.,2015.Implementation of deterministic weather forecasting systems based on Ensemble—variational data assimilation at environment canada.part I:the global system[J].Mon Wea Rev,143(7):2532-2559.
Buizza R,2008.Comparison of a 51-member low-resolution (TL399L62) ensemble with a 6-member high-resolution (TL799L91) lagged-forecast ensemble[J].Mon Wea Rev,136(9):3343-3362.
Buizza R,Palmer T N,1995.The singular-vector structure of the atmospheric global circulation[J].J Atmos Sci,52(9):1434-1456.
Buizza R,Leutbecher M,Isaksen L,2008.Potential use of an ensemble of analyses in the ECMWF ensemble prediction system[J].Quart J Roy Meteor Soc,134(637):2051-2066.
Charron M,Pellerin G,Spacek L,et al.,2010.Toward random sampling of model error in the canadian ensemble prediction system[J].Mon Wea Rev,138(5):1877-1901.
陈超辉,刘梅,智协飞,等,2018.基于BGM框架的短期集合预报扰动典型规律研究[J].大气科学学报,41(4):483-493.Chen C H,Liu M,Zhi X F,et al.,2018.Typical characteristics of spatio-temporal evolution of initial perturbations in short-range ensemble prediction system based on the breeding method[J].Trans Atmos Sci,41(4):483-493.(in Chinese).
Coutinho M M,Hoskins B J,Buizza R,2004.The influence of physical processes on extratropical singular vectors[J].J Atmos Sci,61(2):195-209.
Houtekamer P L,Mitchell H L,2005.Ensemble Kalman filtering[J].Quart J Roy Meteor Soc,131(613):3269-3289.
Leutbecher M,Palmer T N,2008.Ensemble forecasting[J].Journal of Computational Physics,227(7):3515-3539.
Leutbecher M,Lock S J,Ollinaho P,et al.,2017.Stochastic representations of model uncertainties at ECMWF:state of the art and future vision[J].Quart J Roy Meteor Soc,143(707):2315-2339.
Li X,Charron M,Spacek L,et al.,2008.A regional ensemble prediction system based on moist targeted singular vectors and stochastic parameter perturbations[J].Mon Wea Rev,136(2):443-462.
李晓莉,刘永柱,2019.GRAPES全球奇异向量方法改进及试验分[J].气象学报,77(待刊).doi:10.11676/qxxb2019.020.Li X L,Liu Y Z,2019.The improvement of GRAPES global extratropical singular vectors and experimental research[J].Acta Meteorologica Sinica,77(in Press).doi:10.11676/qxxb2019.020.(in Chinese).
刘永柱,沈学顺,李晓莉,2013.基于总能量模的GRAPES全球模式奇异向量扰动研究[J].气象学报,71(3):517-526.Liu Y Z,Shen X S,Li X L,2013.Research on the singular vector perturbation of the GRAPES global model based on the total energy norm[J].Acta Meteorologica Sinica,71(3):517-526.(in Chinese).
刘永柱,张林,金之雁,2017.GRAPES 全球切线性和伴随模式的调优[J].应用气象学报,28(1):62-71.Liu Y Z,Zhang L,Jin Z Y,2017.The optimization of GRAPES global tangent linear model and adjoint model[J].J Appl Meteor Sci,28(1):62-71.(in Chinese).
Palmer T N,Molteni F,Mureau R,et al.,1993.Ensemble prediction[C]//Proc.of the ECMWF seminar on validation of models over Europe.Reading,UK.
Palmer T N,Gelaro R,Barkmeijer J,et al.,1998.Singular vectors,metrics,and adaptive observations[J].J Atmos Sci,55(4):633-653.
Palmer T N,Buizza R,Doblas-Reyes F,et al.,2009.Stochastic parametrization and model uncertainty[R].Reading,UK:ECMWF.
Pegion P,Bates G,Gehne M,et al.,2016.Stochastic parameterization development in the NOAA/NCEP Global Forecast System[R].Reading,UK:ECMWF/WWRP.
彭飞,李晓莉,陈静,等,2019.GRAPES 全球集合预报系统模式扰动随机动能补偿方案初步探究[J].气象学报,77(2):180-195.Peng F,Li X L,Chen J,et al.,2019.A stochastic kinetic energy backscatter scheme for model perturbations in the GRAPES global ensemble prediction system[J].Acta Meteorologica Sinica,77(2):180-195.(in Chinese).
Sanchez C,Williams K D,Collins M,2016.Improved stochastic physics schemes for global weather and climate models[J].Quart J Roy Meteor Soc,142(694):147-159.
Toth Z,Kalnay E,1993.Ensemble forecasting at NMC:the generation of perturbations[J].Bull Amer Meteor Soc,74(12):2317-2330.
Wei M,Toth Z,Wobus R,et al.,2008.Initial perturbations based on ensemble transform (ET) technique in the NCEP global operational forecast system[J].Telllus,60(1):,62-79.
袁月,李晓莉,陈静,等,2016.GRAPES区域集合预报系统模式不确定性的随机扰动技术研究[J].气象,42(10):1161-1175.Yuan Y,Li X L,Chen J,et al.,2016.Stochastic parametrization toward model uncertainty for the GRAPES mesoscale ensemble prediction system[J].Meteor Mon,42(10):1161-1175.(in Chinese).
Zhang H B,Chen J,Zhi X F,et al.,2015.Study on multi-scale blending initial condition perturbations for a regional ensemble prediction system[J].Adv Atmos Sci,32(8):1143-1155.
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).
智协飞,朱寿鹏,孙晶,等,2015.基于BGM与ETKF的台风“苏拉”(1209)集合预报的对比试验Ⅰ:路径预报[J].大气科学学报,38(6):776-784.Zhi X F,Zhu S P,Sun J,et al.,2015.Comparative experiments of ensemble forecasting of typhoon Saola(1209) based on BGM and ETKF,Part Ⅰ:track forecast[J].Trans Atmos Sci,38(6):776-784.(in Chinese).
Zhou X Q,Zhu Y J,Hou D C,et al.,2017.Performance of the new NCEP global ensemble forecast system in a parallel experiment[J].Wea Forecasting,32(5):1989-2004.
Bowler N E,Arribas A,Mylne K R,et al.,2008.The MOGREPS short-range ensemble prediction system[J].Quart J Roy Meteor Soc,134(632):703-722.
Buehner M,McTaggart-Cowan R,Beaulne A,et al.,2015.Implementation of deterministic weather forecasting systems based on Ensemble—variational data assimilation at environment canada.part I:the global system[J].Mon Wea Rev,143(7):2532-2559.
Buizza R,2008.Comparison of a 51-member low-resolution (TL399L62) ensemble with a 6-member high-resolution (TL799L91) lagged-forecast ensemble[J].Mon Wea Rev,136(9):3343-3362.
Buizza R,Palmer T N,1995.The singular-vector structure of the atmospheric global circulation[J].J Atmos Sci,52(9):1434-1456.
Buizza R,Leutbecher M,Isaksen L,2008.Potential use of an ensemble of analyses in the ECMWF ensemble prediction system[J].Quart J Roy Meteor Soc,134(637):2051-2066.
Charron M,Pellerin G,Spacek L,et al.,2010.Toward random sampling of model error in the canadian ensemble prediction system[J].Mon Wea Rev,138(5):1877-1901.
陈超辉,刘梅,智协飞,等,2018.基于BGM框架的短期集合预报扰动典型规律研究[J].大气科学学报,41(4):483-493.Chen C H,Liu M,Zhi X F,et al.,2018.Typical characteristics of spatio-temporal evolution of initial perturbations in short-range ensemble prediction system based on the breeding method[J].Trans Atmos Sci,41(4):483-493.(in Chinese).
Coutinho M M,Hoskins B J,Buizza R,2004.The influence of physical processes on extratropical singular vectors[J].J Atmos Sci,61(2):195-209.
Houtekamer P L,Mitchell H L,2005.Ensemble Kalman filtering[J].Quart J Roy Meteor Soc,131(613):3269-3289.
Leutbecher M,Palmer T N,2008.Ensemble forecasting[J].Journal of Computational Physics,227(7):3515-3539.
Leutbecher M,Lock S J,Ollinaho P,et al.,2017.Stochastic representations of model uncertainties at ECMWF:state of the art and future vision[J].Quart J Roy Meteor Soc,143(707):2315-2339.
Li X,Charron M,Spacek L,et al.,2008.A regional ensemble prediction system based on moist targeted singular vectors and stochastic parameter perturbations[J].Mon Wea Rev,136(2):443-462.
李晓莉,刘永柱,2019.GRAPES全球奇异向量方法改进及试验分[J].气象学报,77(待刊).doi:10.11676/qxxb2019.020.Li X L,Liu Y Z,2019.The improvement of GRAPES global extratropical singular vectors and experimental research[J].Acta Meteorologica Sinica,77(in Press).doi:10.11676/qxxb2019.020.(in Chinese).
刘永柱,沈学顺,李晓莉,2013.基于总能量模的GRAPES全球模式奇异向量扰动研究[J].气象学报,71(3):517-526.Liu Y Z,Shen X S,Li X L,2013.Research on the singular vector perturbation of the GRAPES global model based on the total energy norm[J].Acta Meteorologica Sinica,71(3):517-526.(in Chinese).
刘永柱,张林,金之雁,2017.GRAPES 全球切线性和伴随模式的调优[J].应用气象学报,28(1):62-71.Liu Y Z,Zhang L,Jin Z Y,2017.The optimization of GRAPES global tangent linear model and adjoint model[J].J Appl Meteor Sci,28(1):62-71.(in Chinese).
Palmer T N,Molteni F,Mureau R,et al.,1993.Ensemble prediction[C]//Proc.of the ECMWF seminar on validation of models over Europe.Reading,UK.
Palmer T N,Gelaro R,Barkmeijer J,et al.,1998.Singular vectors,metrics,and adaptive observations[J].J Atmos Sci,55(4):633-653.
Palmer T N,Buizza R,Doblas-Reyes F,et al.,2009.Stochastic parametrization and model uncertainty[R].Reading,UK:ECMWF.
Pegion P,Bates G,Gehne M,et al.,2016.Stochastic parameterization development in the NOAA/NCEP Global Forecast System[R].Reading,UK:ECMWF/WWRP.
彭飞,李晓莉,陈静,等,2019.GRAPES 全球集合预报系统模式扰动随机动能补偿方案初步探究[J].气象学报,77(2):180-195.Peng F,Li X L,Chen J,et al.,2019.A stochastic kinetic energy backscatter scheme for model perturbations in the GRAPES global ensemble prediction system[J].Acta Meteorologica Sinica,77(2):180-195.(in Chinese).
Sanchez C,Williams K D,Collins M,2016.Improved stochastic physics schemes for global weather and climate models[J].Quart J Roy Meteor Soc,142(694):147-159.
Toth Z,Kalnay E,1993.Ensemble forecasting at NMC:the generation of perturbations[J].Bull Amer Meteor Soc,74(12):2317-2330.
Wei M,Toth Z,Wobus R,et al.,2008.Initial perturbations based on ensemble transform (ET) technique in the NCEP global operational forecast system[J].Telllus,60(1):,62-79.
袁月,李晓莉,陈静,等,2016.GRAPES区域集合预报系统模式不确定性的随机扰动技术研究[J].气象,42(10):1161-1175.Yuan Y,Li X L,Chen J,et al.,2016.Stochastic parametrization toward model uncertainty for the GRAPES mesoscale ensemble prediction system[J].Meteor Mon,42(10):1161-1175.(in Chinese).
Zhang H B,Chen J,Zhi X F,et al.,2015.Study on multi-scale blending initial condition perturbations for a regional ensemble prediction system[J].Adv Atmos Sci,32(8):1143-1155.
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).
智协飞,朱寿鹏,孙晶,等,2015.基于BGM与ETKF的台风“苏拉”(1209)集合预报的对比试验Ⅰ:路径预报[J].大气科学学报,38(6):776-784.Zhi X F,Zhu S P,Sun J,et al.,2015.Comparative experiments of ensemble forecasting of typhoon Saola(1209) based on BGM and ETKF,Part Ⅰ:track forecast[J].Trans Atmos Sci,38(6):776-784.(in Chinese).
Zhou X Q,Zhu Y J,Hou D C,et al.,2017.Performance of the new NCEP global ensemble forecast system in a parallel experiment[J].Wea Forecasting,32(5):1989-2004.