摘要
适应性观测是近几年国际上提出的一种有效改善中短期天气预报质量的新思想,是国际THORPEX科学计划的核心内容,也是当前国际数值预报领域研究的前沿热点问题。无论是适应性观测理论,还是针对高影响天气系统的观测试验,我国都处于初步阶段。为积极参加国际THORPEX科学计划,提升我国适应性观测研究的科学水平,改善高影响天气预报质量,本文对适应性观测相关科学问题开展了研究。
本研究主要针对我国典型性高影响天气系统特征,借鉴与吸收国际最新适应性观测研究成果,根据集合卡尔曼变换(ETKF)理论,研究发展了ETKF适应性观测系统与基于ETKF初始扰动方案的GRAPES全球集合预报系统。利用GRAPES全球集合预报和国际TIGGE集合预报资料,针对我国台风和江淮强降水高影响天气,研究了ETKF信号方差的结构特征,揭示了信号方差(目标观测区)与集合数、预报时间长度、气象物理量之间的关系及其对不同集合预报的依赖性,并着重研究了适应性观测对我国典型性高影响天气预报的影响及其目标观测区的分布特征。论文的创新之处与主要科学结论有如下几个方面:
(1)发展建立了ETKF适应性观测系统根据ETKF理论,结合GRAPES 3DVar资料同化系统,发展建立了适用于我国高影响天气系统的ETKF适应性观测系统。选择能够准确反映预报不确定性的总能量构造信号方差,作为识别目标观测区的度量变量。ETKF适应性观测系统具有较强的预报信号方差的能力,可以合理的识别出目标观测区。
(2)目标观测区结构特征及其与影响因素的关系集合成员数对中低纬度热带气旋的目标观测区预报的准确性具有明显的影响,大于37个集合成员识别的目标观测区比较准确。目标观测区的结构与可靠性随预报长度的不同也存在变化,对不同集合预报具有较强的依赖性,表明集合预报质量对ETKF适应性观测具有重要的作用。
(3)我国台风预报的适应性观测研究研究表明,西太平洋热带台风的目标观测主要位于台风中心北侧引导气流区。目标观测并不能确保改善所有的分析误差,对不同层次、不同物理量的改善程度也存在差别,同时也可能降低分析质量。对位势高度与温度的分析误差和预报误差具有明显的改善作用,对不同层次的风场预报的影响不完全相同。对台风路径和中心强度的前24h预报误差具有明显的改善,其后的改善效果并不显著。目标观测资料对路径预报优于对台风强度预报的改善效果。
(4)适应性观测在江淮强降水预报中的应用研究江淮强降水天气系统的目标观测敏感区基本位于引起强降水的低涡系统的槽前位置。目标观测对分析和预报均表现出改善效果,但也存在局部质量降低的情形。不同的分析变量和层次,其改善或降低的效果也不完全相同。对预报的改善主要体现在对流层中低层的部分预报变量,尤其是位势高度的改善作用最为明显。目标观测对降水预报的落区和强降水中心具有一定的改善作用,但并没有明显改善强降水预报的量级。
(5)发展了基于ETKF初始扰动方案的GRAPES全球集合预报系统GRAPES集合初始扰动在北半球可以反映出分析误差方差的主要特征结构,扰动大小合理,并能具有合理的集合离散度,但南半球扰动效果并不理想;扰动增长与预报误差的增长特征基本一致,集合方差可以正确地解释更多的预报误差方差;集合预报能够合理的表示出实际大气可能的发展状态。基于ETKF初始扰动方案的GRAPES全球集合预报系统显示出良好的发展潜力与应用价值。
本研究工作首先建立了我国具有科研与业务应用能力的ETKF适应性观测系统,对我国积极从事国际适应性观测研究合作和开展我国的适应性观测试验提供了系统平台。本工作对我国高影响天气系统目标观测的科学问题有了初步理解,为将来持续研究奠定了基础。同时,也为改善我国高影响天气预报质量提供了有效途径和积极的探索。GRAPES全球集合预报系统也为我国全球业务集合预报的发展提供了新方案。
Adaptive observation is a new idea raised in recent years internationally to improve the quality of medium and short term weather forecast, the key content in international THORPEX, and is a frontier hot problem in numerical prediction field. No matter in the theory of adaptive observation or in observational experiment that aims to resolve high impact weather, the research in China is in its junior stage. For taking part in international THORPEX scientific plan program and at the same time, promoting our skill in research of adaptive observation and improving the outcome of the forecast of high impact weather, this paper will explore research on scientific problems related with adaptive observation.
Taking the latest international research results of adaptive observation and according to ETKF theory, this paper develop ETKF adaptive observation system and GRAPES global ensemble prediction system that based on the ensemble transform Kalman filter (ETKF) initial perturbation scheme, especially considering the specialty of China's typical high impact weather system. Focusing on China's tropical typhoon and high impact weather that lead to heavy rainfall in Jianghuai area, this paper using data from GRAPES global ensemble forecast model and international TIGGE ensemble forecast to study the structural properties of ETKF signal variance, discover the relation between signal variance and the number of ensemble, the forecast time scale and meteorological variables, and still discover the dependence of that relations on different model ensemble forecast. Besides, this paper will intend to investigate the influence of adaptive observation to China's typical high impact weather system. The innovations and the main scientific conclusions of this paper are as follows:
(1) Develop and build ETKF adaptive observation system. Combining with GRAPES 3DVAR, ETKF adaptive observation system suitable for China's high impact weather is built based on ETKF theory. Choose the total energy that can reflect exactly the prediction uncertainty as a measurement variable to distinguish targeting observation area. The ETKF adaptive observation system is of strong ability to predict signal variance and can identify targeting observation area.
(2) The structural properties of targeting area and its relationships with influential factors. The number of ensemble has apparent influence on forecast veracity of tropical cyclone targeting observation area in low and middle latitude. Basically, ensemble with more than 37 members can identify exactly targeting observation area. The structure and reliability of targeting observation area can vary with forecast length, and have strong dependence on different ensemble forecast, and so, those show that the quality of ensemble prediction are important to ETKF adaptive observation.
(3) Research on adaptive observation of China typhoon forecast. Research show that targeted observations of tropical typhoon in West Pacific is mainly in steering flow area that located by the north side of typhoon center. Whereas, targeted observations cannot ascertain that analysis error can definitely be improved. It changed with different levels and variables, and can reduce the analysis quality. Targeted observations can help to improve analysis error and forecast error of the geopotential height and those of temperature, but have different effect to wind forecast on different levels. It can make the forecast error of typhoon track and center strength smaller in 24 hr but the situation is not so after that. Another point is that targeted observations have better improvements on track forecast than on strength forecast.
(4) Application of adaptive observation on heavy rainfall forecast in Jianghuai. Targeting observation area of heavy rainfall synoptic system in Jianghuai is basically located at ahead of depression system trough that will bring heavy rainfall. Targeted observations can improve both analysis and forecast, but will partially reduce those in some instances. For different analysis variables and layers, the effect is totally different. For forecast of some part of variables, improvement is mainly in low middle layer of troposphere, especially to geopotential height. Targeted observations play a certain part in predicting rainfall area and the heavy rain center, but do not take effect in improving the magnitude of the rainfall.
(5) Developing GRAPES global ensemble prediction system which based on ETKF initial perturbation scheme. GRAPES ensemble initial perturbations can present main structure of analysis error variance in the North Hemisphere. The perturbation magnitude and ensemble spread is reasonable. However, the effect in south hemisphere is not that well. Perturbation increase is accord with increase of forecast error, and ensemble variance can correctly explain more forecast error variance. Ensemble forecast can reasonably express the developments status of real atmosphere. GRAPES global ensemble prediction system which based on ETKF initial perturbation scheme would better potential and values.
This paper firstly built ETKF adaptive observation system that can be used both in scientific research and operational forecast, and provide a platform for China to enthusiastically join the collaboration on adaptive observation in international. This paper also gives first understanding on some scientific questions about targeting observation of China high impact weather, builds a foundation for future consistent study, and proposes an available method to improve the forecast quality of high impact weather. GRAPES global ensemble prediction system provides us a new scheme for global operational ensemble forecast as well.
引文
[1]Rabier,F.,E.Klinker,P.Coutier,and A.Hollingsworth.Sensitivity of forecast errors to initial conditions.Q.J.R.Meteor.Soc.,1996,122:121-150
[2]Pu,Z.X.,E.Kalnay,J.Sela and I.Szunyogh.Sensitivity of forecast errors to initial conditions with a quasi-inverse linear method.Mon.Wea.Rev.,1997,125:2479-2503
[3]Bergot,T.,G.Hello,A.Joly,and S.Marlardel.Adaptive observations:A feasibility study.Mon.Wea.Rev.,1999,127:743-765
[4]Melvyn A.Shapiro,Alan J.Thope.THORPEX International Science Plan.WMO/TD-No.1246 WWRP/THORPEX No.2.2004,pp1-51
[5]Thompson,P.D.Uncertainty of initial state as a factor in the Predictability of large scale atmospheric flow patterns.Tellus,1957,9:275-295
[6]Toth,Z.,I.Szunyogh,C.Bishop,S.Majumdar,R.Morss,and S.Lord.On the use of targeted observations in operational numerical weather prediction.Preprints for the Fifth Symposium on Integrated Observing Systems.January,15 - 19,2001,Albaquerque,NM,AMS,72 - 79
[7]Snyder,C.Summary of an workshop on adaptive observations and FASTEX.Bull.Amer.Meteor.Soc.,1996,77:953-961
[8]Lorenz,E.N.,and K.E.Emanuel.Optimal sites for supplementary observations:Simulations with a small model,J.Atmos.Sci.,1998,55:399-414
[9]Morss,R.E.,K.A.Emanuel,and C.Snyder.Idealised adaptive observation strategies for improving numerical weather prediction.J.Atmos.Soi.,2001,58:210-232
[10]Joly,A.,Jorgensen.D.and Shapiro,M.A.,et al.The Fronts and Atlantic Storm-Track Experiment(FASTEX):scientific objectives and experimental design.Bull.Amer.Meteor.Soc.,1997,78:1917-1940
[11]Joly,A.,Browning,K.A.,and Bessemoulin,P.,et al.Overview of the field phase of the Fronts and Atlantic Storm-Track EXperiment (FASTEX)project.Q.J.R.Meteo.Soc.,1999,125:3131-3163
[12]Bergot,T.Influence of the assimilation scheme on the efficiency of adaptive observations.Q.J.R.Meteorol.Soc.,2001,127:635-660
[13]Bergot,T.Adaptive observations during FASTEX:a systematic survey of upstream flights.Q.J.R.Meteor.Soc.,1999,125:3271-3298
[14]Gelaro,R.,R.Langland,G.D.Rohaly,and T.E.Rosmond.An assessment of the singular vector approach to targeted observations using the FASTEX data set.Q.J.R.Meteorol.Soc.,1999,125:3299-3328
[15]Langland,R.H.,Gelaro,R..,Rohaly,G.D.and Shapiro,M.A.Targeted observations in FASTEX:Adjoint-based targeting procedures and data impact experiments in IOP-17 and IOP-18.Q.J.R.Meteorol.Soc.,1999,125:3241-3270
[16]Montani,A.,Thorpe,A.J.,Buizza,R.and Unden,P.Forecast skill of the ECMWF model using targeted observations during FASTEX.Q.J.R.Meteorol.Soc.,1999,125:3219- 3240
[17]Szunyogh,I.,Z.Toth,K.A.Emanuel,C.H.Bishop,C.Snyder,R.E.Morss,J.Woolen,and T.Marchok.Ensemble-based targeting experiments during FASTEX:the effect of dropsonde data from the Lear jet.Q.J.R.Meteorol.Soc.,1999,125:3189- 3218
[18]Doerenbecher,A.and Bergot,T.Sensitivity to observations applied to FASTEX cases.Nonlinear Processes Geophys.,2001,8:467 - 481
[19]Fourrie,N.,Doerenbecher,A.,Bergot,T.and Joly,A.Adjoint sensitivity of the forecast to TOVS observations.Q.J.R.Meteorol.Soc,2002,128:2759-2777
[20]Langland,R.H.,Toth,Z.and Gelaro,R.,et al.The North Pacific Experiment(NORPEX-98):targeted observations for improved North American weather forecasts.Bull.Amer.Meteor.Soc.,1999,80:1363-1384
[21]Majumdar,S.J.,C.S.Bishop,R.Buizza and R.Gelaro.A comparison of Ensemble Transform Kalman Filter Targeting Guidance with ECMWF and NRL Total-Energy Singular Vector Guidance.Q.J.R.Meteorol.Soc.,2002,128:2527-2549
[22]Cardinali,C.and Buizza,R.Forecast skill of targeted observations:A singular-vector-based diagnostic,J.Atmos.Sci,2003,60:1927-1940
[23]Toth,Z.,I.Szunyogh,S.J.Ma jumdar,R.E.Morss,B.J.Etherton,C.H.Bishop,and S.J.Lord.The 1999 Winter Storm Reconnaissance Program.Preprints,13th Conf.on Numerical Weather Prediction,1999,Denver,CO,Amer.Meteor.Soc.,27-32
[24]Szunyogh,I.,Z.Toth,S.Ma jumdar,R.Morss,B.Etherton,and C.Bishop.The effect of targeted dropsonde observations during the 1999 Winter Storm Reconnaissance program.Mon.Wea.Rev,2000,128:3520-3537
[25] Toth, Z., Szunyogh, I., Bishop, C., Majumdar, S., et al. Adaptive observations at NCEP: Past, present, and future. In Proceedings of the symposium on observations, data assimilation, and probabilistic prediction, 2002, 13 -17 January 2002, Orlando, Fla. American Meteorological Society, Boston, USA
[26] Szunyogh, I., Toth, Z., Zimin, A. V., Majumdar, S. J. and Persson, A. Propagation of the effect of targeted observations: The 2000 Winter Storm Reconnaissance Program. Mon. Wea. Rev., 2002, 130:1144-1165
[27] Mansfield, D., Richardson, D. and Truscott, B. An overview of the Atlantic THORPEX Regional Campaign, A-TRec. In Proceedings of the THORPEX Science Symposium, 2005, 6-10 December 2004, Montreal, Canada. World Meteorological Organization, Geneva, Switzerland.
[28] Gelaro, R., Rosmond, T. and Daley, R. Singular vector calculations with an analysis error variance metric. Mon. Wea. Rev., 2002, 130:1166-1186
[29] Leutbecher, M., Barkmeijer, J., Palmer, T. N. and Thorpe, A. J. Potential improvement of forecasts of two severe storms using targeted observations. Q. J. R. Meteorol. Soc., 2002, 128:1641-1670
[30] Coutinho, M. M., Hoskins, B. J. and Buizza, R. The influence of physical processes on extratropical singular vectors. J. Atmos. Sci., 2004, 61:195-209
[31] Langland, R.H. and Baker, N. L A technical description of the NAVDAS adjoint system. NRL/MR/7530-04-8746. 2004, Available from the Naval Research Laboratory, Monterey, CA 93943-5502, USA
[32] Majumdar, S. J., Bishop, C.H., Etherton, B.J. and Toth, Z. Adaptive sampling with the ensemble transform Kalman filter. II: Field program implementation. Mon. Wea. Rev., 2002, 130:1356-1369
[33] Leutbecher, M., Doerenbecher, A., Grazzini, F. and Cardinali, C. Planning of adaptive observations during the Atlantic THORPEX regional campaign 2003. 2004, Pp. 16 - 25 in ECMWF Newsletter No. 102. Available from the European Centre for Medium-Range Weather Forecasts, Reading, UK
[34] Fourrie, N., Marchal, D., Rabier, F., Chapnik, B. and Desroziers, G. Impact study of the 2003 North Atlantic THORPEX regional campaign. Q. J. R. Meteorol. Soc, 2006, 132, 275-295
[35] Iriguchi, T. Impact of NA-TreC extra observations on JMA global forecasts. In Proceedings of the THORPEX science symposium, 6-10 December 2004, Montreal, Canada. 2005, World Meteorological Organization,Geneva,Switzerland
[36]Wu,C.C.,P.H.Lin,and S.Aberson,et al.Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region(DOTSTAR):An Overview.Bull.Amer.Meteor.Soc.,2005,86:787-790
[37]Wu,C.C.,P.H.Lin,I.I.Lin.and T.C.Yeh.A Review on "Dropsonde Observation for Typhoon Surveillance near the TAiwan Region (DOTSTAR)" and "Typhoon-Ocean-Bio-Geochemistry Interaction"Research Projects.Atmos.Sci.,2004,32:275-292
[38]Chou,K.H.,C.C.Wu.Development of the Typhoon Initialization in a Mesoscale Model-Combination of the Bogused Vortex and the Dropwindsonde Data in DOTSTAR.Mon.Wea.Rev.2008,136:865-879
[39]Wu,C.C.,J.H.then,P.H.Lin,and K.H.Chou.Targeted observations of tropical cyclones based on the adjoint-derived sensitivity steering vector,J.Atmos.Sci.,2007,64:2611-2626.
[40]Wu,C.C.,K.H.Chou,P.H.Lin,S.D.Aberson,et al.The impact of dropwindsonde data on typhoon track forecasts in DOTSTAR.Weather and Forecasting,2007,22:1157-1176
[41]Morss,R.E.,K.A.Emanuel.Influence of added observations on analysis and forecast errors:Results from idealized systems.Quart.J.R.Meteor.Soc.,2002,128:285-321
[42]Fischer,C.Linear amplification and error growth in the 2d eady problem with uniform potential vorticity,J.Atmos.Sci.,1998,55:3363-3380
[43]Rabier,F.,Jarvinen,H.Klinker,E.,Mahfouf,J.F.and Simmons,A.The ECMWF operational implementation of four-dimensional variational assimilation Ⅰ:Experimental results with simplified physics.Quart.J.R.Meteoro.Soc.,2000,126:1143-1170
[44]Berliner,L.M.,Q.Lu,and C.Snyder.Statistical design for adaptive weather observations.J.Atmos.Sci.,1999,56:2536-2552
[45]Gilmour,I.,A.Leonard and R.Buizza.Linear regime duration:Is 24 hours a long time in synoptic weather forecasting.J.Atmos.Sci.,2001,58:3525-3539
[46]Errico,R.M.,T.Vukicevic,and K.Raeder.Examination of the accuracy of a tangent linear model.Tellus,1993,45A:462-477
[47]Rabier,F.and P.Courtier,1992:Four-dimensional assimilation in the presence of baroclinic instability.Q.J.Roy.Meteorol.Soc.,118:649 - 672
[48]薛纪善,庄世宇,朱国富,张华.GRAPEs 3D-Var 资料同化系统的科学设 计方案.中国气象科学研究院气象数值预报研究中心.2001,内部资料.
[49]陈德辉,薛纪善,沈学顺等.新一代静力/非静力多尺度通用数值预报动力模式理论方案设计及试验.《中国气象数值预报系统创新研究》技术手册,2003,内部资料.
[50]Palmer,T.N.,R.Gelaro,J.Barkmeijer,and R.Buizza.Singular vectors,metrics,and adaptive observations,J.Atmos.Sci,1998,55:633 - 653
[51]Buizza,R.,A.Montani.Targeting observations using singular vectors,J.Atmos.Sci.,1999,56:2965-2985
[52]Langland,R.H.,and G.D.Rohaly.Adjoint-based targeting of observations for FASTEX cyclones.Preprints,Seventh Conf.on Mesoscale Processes.Reading,United Kingdom,Amer.Meteor.Soc.,1996,369-371
[53]Baker,No L.and R.Daley.Observation and background adjoint sensitivity in the adaptive observation-targeting problem.Q.J.Roy.Meteorol.Soc.,2000,126:1431 - 1454
[54]Pu,Z.X.,and E.Kalnay.Targeting observations with the quasilinear inverse and adjoint and adjoint NCEP global models:Performance during FASTEX.Q.J.R.Meteorol.Soc.,1999,125:3329-3338
[55]Pu,Z.X.,S.J.Lord,and E.Kalnay.Forecast sensitivity with dropwindsonde data and targeted observations.Tellus,1998,50A:391-410
[56]Bishop,C.H.,and Z.Toth.Ensemble transformation and adaptive observations,J.Atmos.Sci,1999,56:1748-1765
[57]Bishop,C.H.,B.J.Etherton,and S.J.Ma jumdar.Adaptive sampling with the ensemble transform Kalman filter.Part Ⅰ:Theoretical aspects.Mon.Wea.Rev,2001,129:420-436
[58]Hamill,T.M.,C.Snyder.Using Improved Background-Error Covariances from an Ensemble Kalman Filter for Adaptive Observations.Mon.Wea.Rev,2002,130:1552-1572
[59]穆穆,王洪利,周菲凡.条件非线性最优扰动方法在适应性观测研究中的初步应用.大气科学,2007,31(6):1102-1112
[60]Petersen,G.N.,A.J.Thorpe.The impact on weather forecasts of targeted observations during A-TReC.Q.J.R.Meteorol.Soc.,2007,133:417-431
[61]Lorenz,E.N.A study of the predictability of a 28-variable atmospheric model.Tellus,1965,17:321-333
[62]Farrell,B.Optimal excitation of baroclinic waves,J.Atmos.Sci.,1989,46:1193-1206
[63]Farrell,B.F.Small error dynamics and the predictability of atmospheric flows,J.Atmos.Sci.,1990,47:2409-2416
[64]Ehrendorfer,M.and J.J.rribbia.Optimal prediction of forecast error covariances through singular vectors.J.Atmos.Sci.,1997,54:286-313
[65]Barkmei jer,J.,M.Van Gi jzen,and F.Bouttier.Singular vectors and estimates of the analysis-error covariance metric.Q.J.R.Meteorol.Soc.1998,124:1695- 1713
[66]Barkmei jer,J.,Buizza,R.,Palmer,T.N.3D-Var Hessian singular vectors and their potential use in the ECMWF Ensemble Prediction System.Q.J.R.Meteorol.Soc.,1999,125:2333-2351
[67]Evensen,G.,and P.J.van Leeuwen.Assimilation of Geosat altimeter data for the Agulhas Current using the ensemble Kalman filter with a quasigeotrophic model.Mon.Wea.Rev,1996,124:85 - 96
[68]Houtekamer P.L.,Mitchell H.L.Data assimilation using an ensemble Kalman filter technique.Mon.Wea.Rev,1998,126:796-811
[69]Anderson,J.L.,S.L.Anderson.A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts.Mon.Wea.Rev,1999,127:2741-2758
[70]Hamill,T.M.,and C.Snyder.A hybrid ensemble Kalman filter 3D-Variational analysis scheme.Mon.Wea.Rev,2000,128:2905-2919
[71]Desroziers,G.,B.Pouponneau,J.N.Thepaut,M.Janiskova,and F.Veerse.Four-dimensional variational analyses of FASTEX situations using special observations.Q.J.R.Meteorol.Soc.,1999,125:3339-3358
[72]Leutbecher,M.A reduced rank estimate of forecast error variance changes due to intermittent modifications of the observing network.J.Atmos.Sci.,2003,60:729-742
[73]Leith C.E.Theoretical skill of Monte Carlo forecasts.Mon.Wea.Rev.,1974,102:409-418
[74]Hollingsworth A.An experiment in Monte Carlo forecasting procedure.ECMWF Workshop on stochastic dynamic forecasting.ECMWF.1980
[75]Hoffman R.N.,Kalnay E.Lagged average forecasting,an alternative to Monte Carlo forecasting.Tellus,1983,35A:100-118
[76]Toth Z.,Kalnay E.Ensemble forecasting at NMC:The generation of perturbations.Bull.Amer.Meteor.Soc.,1993,74:2317-2330
[77]Toth Z.,Kalnay E.Ensemble forecasting at NCEP and the breeding method.Mon.Wea.Rev.,1997,125:3297-3319
[78]Buizza R.,Palmer T.N.The singular-vector structure of the atmospheric global circulation,J.Atmos.Sci.,1995,52:1434- 1456
[79]Molteni F.,Buizza R.,Palmer T.N.,et al.The ECMWF ensemble prediction system:Methodology and validation.Q.J.R.Meteorol.Soc.,1996,122:73-119
[80]noutekamer P.L.,Lefaivre L.,Derome J.,et al.A system simulation approach to ensemble prediction.Mon.Wea.Rev,1996,124:1225-1242
[81]Buizza R.,noutekamer P.L.,Toth Z.,et al.Acomparison of the ECMWF,MSC and NCEP global ensemble prediction systems.Mon.Wea.Rev,2005,133:1076-1097
[82]杨学胜,陈德辉,冷亭波,等.时间滞后与奇异向量初值生成方法的比较试验.应用气象学报,2002,13(1):62-66
[83]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
[84]Wei M.,Toth Z.A new measure of ensemble performance:perturbations versus error correlation analysis(PECA).Mon.Wea.Rev,2003,131:1549-1565
[85]Hamill T.M.,Snyder C.,and Morss R.E.A comparison of probabilistic forecasts from bred,singular vector,and perturbed observation ensembles.Mon.Wea.Rev,2000,128:1835-1851
[86]Wang X.and Bishop C.H.A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes,J.Atmos.Soi.,2003,60:1140-1158
[87]Bishop C.H.,Reynolds C.A.and Tippett M.K.Optimization of the fixed global observing network in a simple model,J.Atmos.Sci.,2003,60:1471-1489
[88]Hoskins,B.J.and Coutinho,M.M.Moist singular vectors and the predictability of some high impact European cyclones.Q.J.R.Meteorol.Soc.,2005,131:581 - 601
[89]Reynolds,C.A.and Rosmond,T.E.Nonlinear growth of singular-vector-based perturbations,Q.J.R.Meteorol.Soc,2003,129:3059 - 3078
[90]Gelaro,R.,Buizza,R.,Palmer,T.N.and Klinker,E.Sensitivity analysis of forecast errors and the construction of optimal perturbations using singular vectors.J.Atmos Sci.,1998,55:1012 - 1037
[91]Gelaro,R.,C.A.Reynolds,R.H.Langland,and Rohaly,G.D.A predictability study using geostationary satellite wind observations during NORPEX.Mon.Wea.Rev,2000,128:3789 - 3807
[92]Kim,Hyun Mee,Michael C.Morgan,and Rebecca E.Morss.Evolution of analysis error and adjoint-based sensitivities:Implications for adaptive observations.J.Atmos.Sci.,2004,61:795-812
[93]Petersen,G.N.,S.J.Ma jumdar and A.J.Thorpe.The properties of sensitive area predictions based on the ensemble transform Kalman filter(ETKF).Quart.J.Roy.Meteor.Soc.,2007,133:697-710
[94]Klinker,E.,Rabier,F.and Gelaro,R.Estimation of key analysis errors using the adjoint technique.Q.J.R.Meteorol.Soc.,1998,124:1909-1933
[95]Hello,G.,Lalaurette,F.and Thepaut,J.N.Combined use of sensitivity information and observations to improve meteorological forecasts:A feasibility study applied to the 'Christmas Storm'case.Q.J.R.Meteorol.Soc.,2000,126:621 - 647
[96]Langland,R.H.,Shapiro,M.A.and Gelaro,R.Initial condition sensitivity and error growth in forecasts of the 25 January 2000 East coast snowstorm.Mon.Weather Rev,2002,130:957-974
[97]Peter S.Maybeck.Stochastic models,estimation and control.Volume 1.New York:Academic press,INC,1979,1-16
[98]Welch G.and G.Bishop.An introduction to the Kalman filter.UNC-Chapel Hill,TR 95-041,2003,1-16
[99]Evensen G.Sequential data assimilation with a nonlinear quasi-geostrophic model using Montre Carlo methods to forecast error statistics.J.Geophys Res,1994,99(10):143-162
[100]Ma jumdar,S.J.,C.H.Bishop,R.Buizza and R.Gelaro.A Comparison of Ensemble Transform Kalman Filter Targeting Guidance with ECMWF and NRL Total Energy Singular Vector Guidance.Q.J.R.Meteor.Soc.,2002,128:1-24
[101]Houtekamer,P.L.,and J.Oerome.Prediction experiments with two-member ensembles.Mon,Wea.Rev.,1994,122:2179-2191
[102]Buizza,R.Optimal perturbation time evolution and sensitivity of ensemble prediction to perturbation amplitude.Q.J.R.Meteorol.Soc.,1995,121:1705-1738
[103]Ma jumdar,S.J.,C.H.Bishop,B.J.Etherton,I.Szunyogh,and Z.Toth. Can an ensemble transform Kalman filter predict the reduction in forecast-error variance produced by targeted observations? Q.J.R.Meteorol.Soc.,2001,127:2803 - 2820
[104]Evensen,G.Sequential data assimilation with a non-linear quasi-geostrophic model using Monte Carlo methods to forecast error statistics,J.Geophys.Res.,1994,99(C5):10143-10162
[105]Ma jumdar S.J.,Aberson S.D.,Bishop C.H.,Buizza R.,Peng M.S.,Reynolds C.A.A comparison of adaptive observing guidance for Atlantic tropical cyclones.Mon.Wea.Rev,2006,134:2354-2372
[106]马旭林,薛纪善,陆维松.GRAPES全球集合预报的集合卡尔曼变换初始扰动方案初步研究.气象学报,2007,待刊
[107]Szunyogh,I.,Z.Toth,S.J.Ma jumdar,R.E.Morss,C.H.Bishop,and S.J.Lord.Ensemble-based targeted observations during NORPEX.Preprints,Third Symp.on Integrated Observing Systems,Dallas,TX,Amer.Meteor.Soc.,1999b,74 - 77
[108]Toth,Z.and Coauthors.Targeted observations at NCEP:Toward an operational implementation.Preprints,Fourth Symp.on Integrated Observing Systems,Long Beach,CA,Amer.Meteor.Soc.,2000,186-193
[108]Buizza R.,Richardson D.S,Palmer T.N.Benefits of increased resolution in the ECMWF ensemble system and comparison with poor-man' s ensemble.Q.J.R.Meteorol.Soc.,2003,129:1269 - 1288
[109]Leutbecher M.,Anderson E.,Bel jaars A.,Hortal M.,Janssen P.Planning of adaptive observations during the Atlantic THORPEX regional Campaign 2003.ECMWF Newsletter,2004,102:16-25
[110]Buizza,R.and T.N.Palmer.Impact of Ensemble Size on Ensemble Prediction.Mon.Wea.Rev,1998,126:2503-2518
[111]Mitchell H.L.and P.L.Houtekamer.Ensemble Size,Balance,and Model-Error Representation in an Ensemble Kalman Filter.Mon.Wea.Rev,2002,130:2791-2808
[112]Bishop C.H.,B.J.Etherton and S.J.Ma jumdar.Verification region selection and data assimilation for adaptive sampling.Q.J.R.Meteorol.Soc.,2006,132:915-933
[113]Thorpe A.J.,Petersen G.N.Predictability and targeted observations.Predictability of Weather and Climate.Pp 561- 583.Ed.Palmer T,Hagedorn R.Cambridge University Press:Cambridge,UK,2006
[114]Aberson,S.D.Targeted observations to improve operational tropical cyclone track forecast guidance.Mon.Wea.Rev,2003,131: 1613-1628
[115]Burpee,R.W.Franklin,J.L.,Lord,S.J.,Tuleya,R.E.and Aberson,S.D.The impact of Omega dropwindsondes on operational hurricane track forecast models.Bull.Amer.Meteorol.Soc.,1996,77:925 - 933
[116]Tuleya,R.E.and Lord,S.J.The impact of dropwindsonde data on GFDL hurricane model forecasts using global analyses.Weather and Forecasting,1997,12:307 - 323
[117]Aberson.S.D.,Franklin,J.L.Impact on hurricane track and intensity forecasts of GPS dropwindsonde observations from the first-season flights of the NOAA Gulfstream-Ⅳ jet aircraft.Bull.Amer.Meteorol.Soc.,1999,80:421 - 427
[118]Tuleya,R.E.and Kurihara,Y.A numerical study on the effects of enviroumental flow on tropical storm genesis,Mon.Wea.Rev,1981,109:2487- 2506
[119]Arnold,C.P.,Jr.and C.H.Dey.Observing-system simulation experiments:Past,present,and future.Bull.Amer.Meteor.Soc.,1986,67:687-695
[120]Newton,C.W.Analysis and Data Problems in Relation to Numerical Prediction.Bull Amer.Meteor.Soc.,1954,35:287-294
[121]Cane,M.A.,V.J.Cardone,M.Halem,and I.Halberstam.On the sensitivity of numerical wether prediction to remotely sensed marine surface wind data:a simulation study,J.Geophys.Res,1981,86:8093-8106
[122]Halem,M.and R.Dlouhy.Observing system simulation experiments related to space-borne lidar wind profiling.Part Ⅰ:Forecast impacts of highly idealized observing systems.Preprints,Conference on Satellite Meteorology/ Remote Sensing and Application Clearwater,Fla.,American Meteorological Society,1984,272-279
[123]Daley R.and T.Mayer.Estimates of Global Analysis Error from the Global Weather Experiment Observational Network.Mon.Wea.Rev.,1986,114:1642-1653
[124]Atlas,R.,E.Kalnay,J.Susskind,W.E.Baker and M.Halem.Simulation studies of the impact of future observing systems on weather prediction.Proc.Seventh Conf.On NWP.1985,145-151
[125]Hoffman,R.N,C.Grassotti,R.Isaacs,J.Louis,T.Nehrkorn,and D.Norquist.Assessment of the impact of simulated satellite lidar wind and retrieved 183 GHz water vapor observations on a global data assimilation system.Mon.Wea.Rev.,1990,118:2513-2542
[126]Atlas,R.and G.D.Emmitt.Implications of several orbit inclinations for the impact of LAWS on global climate studies.Second Symposium on Global Change Studies,New Orleans,1991,28-32
[127]Rohaly,G.D.and T.N.Krishnamurti.An observing system simulation experiment for the Laser Atmospheric Wind Sounder(LAWS).J.Applied Meteor.,1993,32:1453-1471
[128]Stephen J.Lord,Michiko Masutani,J.S.Woollen,J.C.Derber.Observing System Simulation Experiments for NPOESS.5th INTEGRATED OBSERVING SYSTEMS,American Meteorological Society,2001
[129]Masutani,M.,J.S.Woollen,S.J.Lord,R.Treadon,G.D.Emmitt,Z.Toth,and J.LeMarshall.Global OSSE at NCEP.Thr First THORPEX International Science Symposium,6-10 December 2004,Montreal,Canada.WMO publication.2004a
[130]Masutani M.,Stephen J.Lord,John S Woollen et al.Global OSSE at NCEP Eighth Symposium on Integrated Observing and Assimilation Systems for Atmosphere,Oceans,and Land Surface Seattle,WA,2004b
[131]马旭林,庄照荣,薛纪善,陆维松.GRAPES非静力数值预报模式的三维变分资料同化系统的发展.气象学报,2007,待刊
[132]Holland L.D.,Toth Z.,Moskaitis J.,Ma jumdar S.,Bishop C.H.,Smith R.2004.Results from the Winter Storm Reconnaissance program 2002 - 2003.In Proceedings of the 84th AMS annual meeting,11 - 14January 2004,Seattle,WA,USA.
[133]Daley R.Atmospheric Data Analysis.Cambridge University Press,1991.457pp
[134]Wang X.,Bishop C.H.and Julier S.J.Which is better,an ensemble of positive/negative pairs or a centered spherical simplex ensemble?Mon.Wea.Rev.,2004,132:1590-1605
[135]Wei M.,Toth Z.and Wobus R.Ensemble transform Kalman filter-based ensemble perturbations in an operational global prediction system at NCEP.Tellus,2006,58A:28-44