GRAPES全球三维变分同化中卫星微波温度计亮温的背景误差及在质量控制中的应用
|
摘要
模式变量背景误差在观测空间的投影,也即观测变量的背景误差包含了变分同化系统的重要信息,其在诊断和分析变分同化系统中资料的影响等方面具有重要作用,特别是在背景场检查质量控制中。在GRAPES全球三维变分同化(3DVar)系统中仅给定了控制变量的背景误差,并未直接给定观测变量的背景误差。为了能够对GRAPES全球3DVar进行全面的诊断和分析,改进卫星微波温度计资料的质量控制,推导出GRAPES全球3DVar同化系统控制变量随机扰动方法估计观测变量的背景误差的公式,为分析和改进GRAPES全球3DVar提供了一个有力工具,并进而估计了AMSU-A亮温的背景误差,分析了AMSU-A不同通道亮温的背景误差特征,将其应用于GRAPES全球3DVar的AMSU-A亮温的背景场检查质量控制中。结果表明,控制变量随机扰动方法估计的GRAPES全球3DVar同化系统AMSU-A亮温的背景误差正确合理。同化循环预报试验结果表明,亮温的背景误差在背景场检查中的应用显著提高了GRAPES全球3DVar同化的亮温资料的数量,显著提高了GRAPES南半球对流层中高层位势高度场的预报技巧。在GRAPES全球3DVar同化系统中推导和实现的控制变量扰动方法为诊断和分析GRAPES全球3DVar观测资料同化效果提供了有力工具。
Background errors(BEs)for observable quantities are valuable for diagnostic analysis of the response of the data assimilation system to these observable quantities and play an important role in improving the variational data assimilation system.BEs are widely applied to assess impacts of observable quantities on analysis.The condition number of the Hessian matrix is determined by background errors for observable quantities,observation errors and observation count number.The background errors of observable quantities can also be used in the procedure of background check in data quality control.However,the background errors are specified in terms of those quantities that lead to a compact formulation of the background termJb,i.e.the balanced stream function,unbalanced Exner pressure,velocity potential and specific humidity in GRAPES 3DVar system.It is not clear how the magnitudes of these background errors can be compared with various observation errors.The formulations of control variable randomization method in GRAPES are illustrated by applying the observation operators of GRAPES 3DVar system to a set of random vectors drawn from a population whose probability density function is given by an assumed background error covariance.This method is applied to estimate the background error for AMSU-A radiance data in grid-point space.The background error for radiance data is then applied in its quality control scheme.The results of forecast experiments show that more radiance data are assimilated using the new quality control scheme,which has a positive effect on geopotential height forecast in both the southern and northern Hemisphere.A statistically significant improvement in the anomaly correlation scores for geopotential height simulation in the southern Hemisphere at all forecast time is obtained.More than0.2 day of forecast skill of geopotential height at 500 hPa is obtained in southern Hemisphere.
Background errors(BEs)for observable quantities are valuable for diagnostic analysis of the response of the data assimilation system to these observable quantities and play an important role in improving the variational data assimilation system.BEs are widely applied to assess impacts of observable quantities on analysis.The condition number of the Hessian matrix is determined by background errors for observable quantities,observation errors and observation count number.The background errors of observable quantities can also be used in the procedure of background check in data quality control.However,the background errors are specified in terms of those quantities that lead to a compact formulation of the background termJb,i.e.the balanced stream function,unbalanced Exner pressure,velocity potential and specific humidity in GRAPES 3DVar system.It is not clear how the magnitudes of these background errors can be compared with various observation errors.The formulations of control variable randomization method in GRAPES are illustrated by applying the observation operators of GRAPES 3DVar system to a set of random vectors drawn from a population whose probability density function is given by an assumed background error covariance.This method is applied to estimate the background error for AMSU-A radiance data in grid-point space.The background error for radiance data is then applied in its quality control scheme.The results of forecast experiments show that more radiance data are assimilated using the new quality control scheme,which has a positive effect on geopotential height forecast in both the southern and northern Hemisphere.A statistically significant improvement in the anomaly correlation scores for geopotential height simulation in the southern Hemisphere at all forecast time is obtained.More than0.2 day of forecast skill of geopotential height at 500 hPa is obtained in southern Hemisphere.
引文
龚建东,魏丽,陶士伟等.2006a.全球资料同化中误差协方差三维结构的准确估计与应用Ⅰ:观测空间协方差的准确估计.气象学报,64(6):669-683,doi:10.11676/qxxb2006.065.Gong J D,Wei L,Tao S W,et al.2006a.Accurate estimation and application of 3-D error covariance structure in global data assimilation.PartⅠ:Accurate estimation of error covariance in observation space.Acta Meteor Sinica,64(6):669-683,doi:10.11676/qxxb2006.065(in Chinese)
龚建东,赵刚.2006b.全球资料同化中误差协方差三维结构的准确估计与应用Ⅱ:背景误差协方差调整与数值试验分析.气象学报,64(6):684-698,doi:10.11676/qxxb2006.066.Gong J D,Zhao G.2006b.Accurate estimation and application of 3-D error covariance structures in global data assimilation.PartⅡ:Background error covariance structure adjustment and numerical experiments.Acta Meteor Sinica,64(6):684-698,doi:10.11676/qxxb2006.066(in Chinese)
王金成,庄照荣,韩威等.2014.GRAPES全球变分同化背景误差协方差的改进及对分析预报的影响:背景误差协方差三维结构的估计.气象学报,72(1):62-78,doi:10.11676/qxxb2015.005.Wang J C,Zhuang Z R,Han W,et al.2014.An improved background error covariance in the global GRAPES variational data assimilation and its impact on the analysis and prediction:Statistics of the three-dimensional structure of background error covariance.Acta Meteor Sinica,72(1):62-78,doi:10.11676/qxxb2015.005(in Chinese)
薛纪善,陈德辉.2008.数值天气预报系统GRAPES的科学设计与应用.北京:科学出版社,1-61.Xue J S,Chen D H.2008.Scientific Design and Application of Numerical Prediction System GRAPES.Beijing:Science Press,1-61(in Chinese)
庄世宇,薛纪善,朱国富等.2005.GRAPES全球三维变分同化系统:基本设计方案与理想试验.大气科学,29(6):872-884.Zhuang S Y,Xue J S,Zhu G F,et al.2005.GRAPES Global 3 D-Var system:Basic design and ideal experiments.Chinese J Atmos Sci,29(6):872-884(in Chinese)
Anderson E,Pailleux J,Thépaut J N,et al.1994.Use of cloudcleared radiances in three/four-dimensional variational data assimilation.Quart J Roy Meteor Soc,120(517):627-653
Anderson E,Fisher M,Munro R,et al.2000.Diagnosis of background errors for radiances and other observable quantities in a variational data assimilation scheme,and the explanation of a case of poor convergence.Quart J Roy Meteor Soc,126(565):1455-1472
Anderson J L,Anderson S L.1999.A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts.Mon Wea Rev,127(12):2714-2758
Barlow R J.1989.Statistics:A Guide to the Use of Statistical Methods in the Physical Sciences.New York:John Wiley and Sons Ltd,78pp
Bormann N,Fouilloux A,Bell W.2013.Evaluation and assimilation of ATMS data in the ECMWF system.J Geophys Res,118(23):12970-12980,doi:10.1002/2013JD020325
Bouttier F.2001.The use of profiler data at ECMWF.Meteor Zeitschr,10(6):497-510
Cardinali C,Isaksen L,Andersson E.2003.Use and impact of automated aircraft data in a Global 4DVAR data assimilation system.Mon Wea Rev,131(8):1865-1877,doi:10.1175∥2569.1
Daley R.1991.Atmospheric Data Analysis:Cambridge Atmospheric and Space Sciences Series.Cambridge:Cambridge University Press
Fisher M,Courtier P.1995.Estimating the Covariance Matrices of Analysis and Forecast Error in Variational Data Assimilation.ECMWF Technical Memorandum 220,Reading,Berkshire,UK:ECMWF
Hollingsworth A,Lonnberg P.1986.The statistical structure of short-range forecast errors as determined from radiosonde data.Part I:The wind field.Tellus A,38A(2):111-136
Jarvinen H,Undén P.1997.Observation Screening and Background Quality Control in the ECMWF 3DVar Data Assimilation System.ECMWF Research Department Technical Memorandum no.236,Shinfield Park,Reading,UK:ECMWF
Leith C E.1974.Theoretical skill of Monte Carlo forecasts.Mon Wea Rev,102(6):409-418
Lorenc A C.1986.Analysis methods for numerical weather prediction.Quart J Roy Meteor Soc,112(474):1177-1194
McNally A P,Derber J C,Wu W,et al.2000.The use of TOVS level-1B radiances in the NCEP SSI analysis system.Quart J Roy Meteor Soc,126(563):689-724
Rabier F,McNally A,Anderson E,et al.1998.The ECMWF implementation of three-dimensional variational assimilation(3DVar).II:Structure functions.Quart J Roy Meteor Soc,124(550):1809-1829
Toth Z,Kalnay E.1997.Ensemble forecasting at NCEP:the breeding method.Mon Wea Rev,125(12):3297-3318
Wu W S,Rurser R J,Parrish D F.2002.Three-dimensional variational analysis with spatially inhomogeneous covariances.Mon Wea Rev,130(12):2905-2916
Xu Q,Wei L,Van Tuyl A,et al.2001.Estimation of three-dimensional error covariances.Part I:Analysis of height innovation vectors.Mon Wea Rev,129(8):2126-2135
Zhu T,Zhang D L,Weng F Z.2002.Impact of the advanced microwave sounding unit measurements on hurricane prediction.Mon Wea Rev,130(10):2416-2432
龚建东,赵刚.2006b.全球资料同化中误差协方差三维结构的准确估计与应用Ⅱ:背景误差协方差调整与数值试验分析.气象学报,64(6):684-698,doi:10.11676/qxxb2006.066.Gong J D,Zhao G.2006b.Accurate estimation and application of 3-D error covariance structures in global data assimilation.PartⅡ:Background error covariance structure adjustment and numerical experiments.Acta Meteor Sinica,64(6):684-698,doi:10.11676/qxxb2006.066(in Chinese)
王金成,庄照荣,韩威等.2014.GRAPES全球变分同化背景误差协方差的改进及对分析预报的影响:背景误差协方差三维结构的估计.气象学报,72(1):62-78,doi:10.11676/qxxb2015.005.Wang J C,Zhuang Z R,Han W,et al.2014.An improved background error covariance in the global GRAPES variational data assimilation and its impact on the analysis and prediction:Statistics of the three-dimensional structure of background error covariance.Acta Meteor Sinica,72(1):62-78,doi:10.11676/qxxb2015.005(in Chinese)
薛纪善,陈德辉.2008.数值天气预报系统GRAPES的科学设计与应用.北京:科学出版社,1-61.Xue J S,Chen D H.2008.Scientific Design and Application of Numerical Prediction System GRAPES.Beijing:Science Press,1-61(in Chinese)
庄世宇,薛纪善,朱国富等.2005.GRAPES全球三维变分同化系统:基本设计方案与理想试验.大气科学,29(6):872-884.Zhuang S Y,Xue J S,Zhu G F,et al.2005.GRAPES Global 3 D-Var system:Basic design and ideal experiments.Chinese J Atmos Sci,29(6):872-884(in Chinese)
Anderson E,Pailleux J,Thépaut J N,et al.1994.Use of cloudcleared radiances in three/four-dimensional variational data assimilation.Quart J Roy Meteor Soc,120(517):627-653
Anderson E,Fisher M,Munro R,et al.2000.Diagnosis of background errors for radiances and other observable quantities in a variational data assimilation scheme,and the explanation of a case of poor convergence.Quart J Roy Meteor Soc,126(565):1455-1472
Anderson J L,Anderson S L.1999.A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts.Mon Wea Rev,127(12):2714-2758
Barlow R J.1989.Statistics:A Guide to the Use of Statistical Methods in the Physical Sciences.New York:John Wiley and Sons Ltd,78pp
Bormann N,Fouilloux A,Bell W.2013.Evaluation and assimilation of ATMS data in the ECMWF system.J Geophys Res,118(23):12970-12980,doi:10.1002/2013JD020325
Bouttier F.2001.The use of profiler data at ECMWF.Meteor Zeitschr,10(6):497-510
Cardinali C,Isaksen L,Andersson E.2003.Use and impact of automated aircraft data in a Global 4DVAR data assimilation system.Mon Wea Rev,131(8):1865-1877,doi:10.1175∥2569.1
Daley R.1991.Atmospheric Data Analysis:Cambridge Atmospheric and Space Sciences Series.Cambridge:Cambridge University Press
Fisher M,Courtier P.1995.Estimating the Covariance Matrices of Analysis and Forecast Error in Variational Data Assimilation.ECMWF Technical Memorandum 220,Reading,Berkshire,UK:ECMWF
Hollingsworth A,Lonnberg P.1986.The statistical structure of short-range forecast errors as determined from radiosonde data.Part I:The wind field.Tellus A,38A(2):111-136
Jarvinen H,Undén P.1997.Observation Screening and Background Quality Control in the ECMWF 3DVar Data Assimilation System.ECMWF Research Department Technical Memorandum no.236,Shinfield Park,Reading,UK:ECMWF
Leith C E.1974.Theoretical skill of Monte Carlo forecasts.Mon Wea Rev,102(6):409-418
Lorenc A C.1986.Analysis methods for numerical weather prediction.Quart J Roy Meteor Soc,112(474):1177-1194
McNally A P,Derber J C,Wu W,et al.2000.The use of TOVS level-1B radiances in the NCEP SSI analysis system.Quart J Roy Meteor Soc,126(563):689-724
Rabier F,McNally A,Anderson E,et al.1998.The ECMWF implementation of three-dimensional variational assimilation(3DVar).II:Structure functions.Quart J Roy Meteor Soc,124(550):1809-1829
Toth Z,Kalnay E.1997.Ensemble forecasting at NCEP:the breeding method.Mon Wea Rev,125(12):3297-3318
Wu W S,Rurser R J,Parrish D F.2002.Three-dimensional variational analysis with spatially inhomogeneous covariances.Mon Wea Rev,130(12):2905-2916
Xu Q,Wei L,Van Tuyl A,et al.2001.Estimation of three-dimensional error covariances.Part I:Analysis of height innovation vectors.Mon Wea Rev,129(8):2126-2135
Zhu T,Zhang D L,Weng F Z.2002.Impact of the advanced microwave sounding unit measurements on hurricane prediction.Mon Wea Rev,130(10):2416-2432