集合预报方法在暴雨研究和预报中的应用
|
摘要
机理了解不够和可预报性问题的忽略是暴雨预报不尽人意的两大原因。主要讨论第二方面,即如何面对和处理可预报性问题,这对如何提高现有数值预报的价值、做好气象服务尤其重要。根据作者多年的研究和实践经验以及直接接触的一些研究和方法,简要地总结了数值集合预报方法在暴雨研究和预报中的应用,具体包括以下四个方面:(1)暴雨集合预报系统的建立:初值和物理扰动、成员数、模式分辨率、资料同化和"虚拟"集合预报;(2)预报方法:集合异常预报法、再预报相似集合法和台风路径聚类法;(3)在预报后处理与订正中的应用:平均、成员排序与最佳成员法、加权平均、概率匹配平均法和集合动力因子法;(4)对暴雨天气系统的机理分析与模式初值的改进:初值扰动差异分析和集合敏感性法、目标观测。希望国内气象业务部门能在日常业务中借鉴以上方法以提高暴雨预报和服务水平,为今后的研究工作提供一个新的起点、方向和方法,这包括指导现有的一些业务集合预报系统今后的进一步完善。
Inability in correctly predicting heavy rain events is primarily due to two reasons: lack of full understanding its physical mechanism and negligence of its predictability limit. How to deal with its predictability limit is the focus of this review paper, which is especially important to enhance the value of numerical weather prediction products to better serve end-users. Based mainly on authors' own or directly involved researches and experiences, many applications of ensemble methodology to heavy rain research and prediction are briefly overviewed. Specifically speaking, the following four general areas are discussed:(1) ensemble prediction system including initial condition and model/physics perturbations, optimal ensemble size, model resolution, data assimilation, and various "virtual" ensembles;(2) forecast methods including ensemble anomaly forecasting, reforecasting analog ensemble, and storm track clustering;(3) forecast post-processing and calibration including ensemble mean, performance ranking and best member, weighted ensemble mean, probability-matched ensemble mean, and ensemble of dynamic factors; and(4) weather system analysis and model initial condition improvement including perturbation difference analysis, ensemble sensitivity, and targeted observation. It is expected that this review will inspire actions from both operation and research communities: many proven-to-be effective methods described in this paper could be adopted in routine weather forecasting practice by operational meteorologists to improve their forecast and service; research community could have a new starting point with new ideas and a clearer direction for future science and technology development including the improvement of current existing operational ensemble prediction systems in years to come.
Inability in correctly predicting heavy rain events is primarily due to two reasons: lack of full understanding its physical mechanism and negligence of its predictability limit. How to deal with its predictability limit is the focus of this review paper, which is especially important to enhance the value of numerical weather prediction products to better serve end-users. Based mainly on authors' own or directly involved researches and experiences, many applications of ensemble methodology to heavy rain research and prediction are briefly overviewed. Specifically speaking, the following four general areas are discussed:(1) ensemble prediction system including initial condition and model/physics perturbations, optimal ensemble size, model resolution, data assimilation, and various "virtual" ensembles;(2) forecast methods including ensemble anomaly forecasting, reforecasting analog ensemble, and storm track clustering;(3) forecast post-processing and calibration including ensemble mean, performance ranking and best member, weighted ensemble mean, probability-matched ensemble mean, and ensemble of dynamic factors; and(4) weather system analysis and model initial condition improvement including perturbation difference analysis, ensemble sensitivity, and targeted observation. It is expected that this review will inspire actions from both operation and research communities: many proven-to-be effective methods described in this paper could be adopted in routine weather forecasting practice by operational meteorologists to improve their forecast and service; research community could have a new starting point with new ideas and a clearer direction for future science and technology development including the improvement of current existing operational ensemble prediction systems in years to come.
引文
[1]章国材.防御和减轻气象灾害.气象,2006,32(3):3-5.
[2]陶诗言,等.中国之暴雨.北京:科学出版社,1980.
[3]陈云峰,高歌.近20年我国气象灾害损失的初步分析.气象,2010,36(2):76-80.
[4]张大林.各种非绝热物理过程在中尺度模式中的作用.大气科学,1998,22(4):548-561.
[5]Lorenz E N.混沌的本质.刘式达,刘式适,严中伟译.北京:气象出版社,1997.
[6]丑纪范.大气科学中的非线性与复杂性.北京:气象出版社,2002.
[7]杜钧,陈静.单一值预报向概率预报转变的基础:谈谈集合预报及其带来的变革.气象,2010,36(11):1-11.
[8]王东海,杜钧,柳崇健.正确认识和对待天气预报的不确定性.气象,2011,37(4):385-392.
[9]杜钧,陈静.天气预报的公众评价与发布形式的变革.气象,2010,36(1):1-6.
[10]杜钧,康志明.天气预报中不确定性问题的调查分析.气象科技进展,2014,4(1):58-67.
[11]US National Research Council.Completing the Forecast:Characterizing and Communicating Uncertainty for Better Decision Using Weather and Climate Forecasts.Washington D C:The National Academy Press,2006.
[12]杜钧,邓国.单一值预报向概率预报转变的价值:谈谈概率预报的检验和应用.气象,2010,36(12):10-18.
[13]杜钧.集合预报的现状和前景.应用气象学报,2002,13(1):16-28.
[14]Du J,Yu R C,Cui C G,et al.Using a mesoscale ensemble to predict forecast error and perform targeted observation.Acta Oceanologica Sinica,2014,33(1):83-91.
[15]Du J,Mullen S L,Sanders F.Short-range ensemble forecasting of quantitative precipitation.Mon Wea Rev,1997,125:2427-2459.
[16]Du J,Zhou B B.A dynamical performance-ranking method for predicting individual ensemble member’s performance and its application to ensemble averaging.Mon Wea Rev,2011,129(10):3284-3303.
[17]Li J,D u J,Zhang D L,et al.Ensemble-based analysis and sensitivity of mesoscale forecasts of a vortex over southwest China.Q J R Meteorol Soc,2014,140:766-782.
[18]Zhang F,Weng Y,Kuo Y H,et al.Predicting typhoon Morakot’s catastrophic rainfall with a convection-permitting mesoscale ensemble system.Weather and Forecasting,2010,25:1816-1825.
[19]Stensrud D J,Brooks H E,Du J,et al.Using ensembles for short-range forecasting.Mon Wea Rev,1999,127:433-446.
[20]Yuan H,Mullen S L,Gao X,et al.Verification of probabilistic quantitative precipitation forecasts over the southwest United States during winter 2002/03 by the RSM ensemble system.Mon Wea Rev,2005,133:279-294.
[21]李俊,杜钧,王明欢,等.中尺度暴雨集合预报系统研发中的初值扰动试验.高原气象,2009,28(6):1365-1375.
[22]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.
[23]Toth Z,Kalnay E.Ensemble forecasting at NMC:The generation of perturbations.Bul Amer Meteor Soc,1993,74:2317-2330.
[24]Toth Z,Kalnay E.Ensemble forecasting at NCEP and the breeding method.Mon Wea Rev,1997,125:3297-3319.
[25]Johnson A,Wang X G,Xue M,et al.Multiscale characteristics and evolution of perturbations for warm season convection-allowing precipitation forecast:Dependence on background flow and method of perturbation.Mon Wea Rev,2014,142(3):1053-1073.
[26]李俊,杜钧,王明欢,等.AREM模式两种初值扰动方案的集合降水预报试验及检验.热带气象学报,2010,26(6):217-228.
[27]Du J,Gayno G,Mitchell K E,et al.Sensitivity study of T2m and precipitation forecasts to soil moisture initial condition using NCEP WRF ensemble system.22nd Conf on Weather Analysis and Forecasting/18th Conf on Numerical Weather Prediction,2007,Park City,UT.American Meteor Soc.
[28]Aligo E A,Gallus Jr W A,Segal M.Summer rainfall forecast spread in an ensemble initialized with different soil moisture analyses.Weather and Forecasting,2007,22:2,299-314.
[29]Sutton C,Hamill T M,Warner T T.Will perturbing soil moisture improve warm-season ensemble forecasts?A proof of concept.Mon Wea Rev,2006,134:3174-3189.
[30]Clark A J,Kain J S,Stensrud D J,et al.Probabilistic precipitation forecast skill as a function of ensemble size and spatial scale in a convection-allowing ensemble.Mon Wea Rev,2011,139:1410-1418.
[31]Richardson D S.Measures of skill and value of ensemble prediction systems,their interrelationship and the effect of ensemble size.Quart J Roy Meteor Soc,2001,127:2473-2489.
[32]Clark A J,Gallus Jr W A,Xue M,et al.A comparison of precipitation forecast skill between small convection-permitting and large convection-parameterizing ensembles.Wea and Forecasting,2009,24:1121-1140.
[33]Clark A J,Gallus Jr W A,Xue M,et al.Convection-allowing and convection-parameterizing ensemble forecasts of a mesoscale convective vortex and associated severe weather.Wea Forecasting,2010,25:1052-1081.
[34]Ma J H,Zhu Y J,Wobus R,et al.An effective configuration of ensemble size and horizontal resolution for the NCEP GEFS.Adv Atmos Sci,2012,29(4):782-794.
[35]Aligo E A,Gallus Jr W A,Segal M.On the impact of WRF model vertical grid resolution on Midwest summer rainfall forecasts.Weather and Forecasting,2009,24:2,575-594.
[36]Brooks H E,Tracton M S,Stensrud D J,et al.Short-range ensemble forecasting:Report from a workshop,25-27 July 1994.Bull Amer Meteorol Soc,1995,74:2317-2330.
[37]Mullen S L,Du J,Sanders F.The Dependence of ensemble dispersion on analysis–forecast systems:Implications to shortrange ensemble forecasting of precipitation.Mon Wea Rev,1999,127:1674-1686.
[38]Du J,Tracton M S.Implementation of a real-time short-range ensemble forecasting system at NCEP:An update.9th Conference on Mesoscale Processes,2001,Ft Lauderdale,Florida.Amer Meteor Soc,355-356.http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[39]Du J,Di Mego G,Tracton M S,et al.NCEP short-range ensemble forecasting(SREF)system:multi-IC,multi-model and multiphysics approach.Research Activities in Atmospheric and Oceanic Modelling(edited by J.Cote),Report 33,CAS/JSC Working Group Numerical Experimentation(WGNE),WMO/TD,2003,No.1161,5.09-5.10.http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[40]Zhou B B,Du J.Fog prediction f rom a multimodel mesoscale ensemble prediction system.Wea and Forecasting,2010,25:303-322.
[41]吴政谦,徐海明,王东海,等.中尺度多模式超级集合预报对2010年6月19—20日中国南方大暴雨过程的分析.热带气象学报,2012(5):653-663.
[42]Duan Y H,Gong J D,Du J,et al.An overview of the Beijing 2008 Olympics Research and Development Project(B08RDP).Bull Amer Meteor Soc,2012,93:381-403.
[43]Du J,et al.The NOAA/NWS/NCEP Short Range Ensemble Forecast(SREF)system:Evaluation of an initial condition vs multiple model physics ensemble approach.16th Conf on Numerical Weather Prediction/20th Conf on Weather Analysis and Forecasting,Seattle,WA.Amer Meteor Soc,2004.http://ams.confex.com/ams/pdfpapers/71107.pdf
[44]Kong F Y,et al.Preliminary analysis on the real-time storm-scale ensemble forecasts produced as a part of the NOAA Hazardous Weather Testbed 2007 Spring Experiment.22nd Conf on Weather Analysis and Forecasting/18th Conf on Numerical Weather Prediction,Park City,UT.Amer Meteor Soc,2007.http://ams.confex.com/ams/pdfpapers/124667.pdf
[45]Gilmour I,Smith L A,Buizza R.Linear Regime Duration:Is 24 Hours a Long Time in Synoptic Weather Forecasting?J Atmos Sci,2001,58:3525-3539.
[46]Clark A J,Gallus Jr W A,Chen T C.Contributions of mixed physics versus perturbed initial/lateral boundary conditions to ensemble-based precipitation forecast skill.Monthly Weather Review,2008,136:6,2140-2156.
[47]Stensrud D J,Bao J W,Warner T T.Using initial condition and model physics perturbations in short-range ensemble simulations of mesoscale convective systems.Mon Wea Rev,2000,128:2077-2107.
[48]Buizza R,Palmer T.Stochastic representation of model uncertainties in the ECMWF ensemble prediction system.Quart J Roy Meteor Soc.,1999,125:2887-2908.
[49]谭燕,陈德辉.基于非静力模式物理扰动的中尺度集合预报试验.应用气象学报,2007,18(3):396-406.
[50]Teixeira J,Reynolds C.Stochastic nature of physical parameterizations in ensemble prediction:A stochastic convection approach.Mon Wea Rev,2008,136:483-496.
[51]Li X,Charron M,Spacek L,et al.A regional ensemble prediction system based on moist targeted singular vectors and stochastic parameter perturbations.Mon Wea Rev,2008,136:443-462.
[52]Berner J,Shutts G J,Leutbecher M,et al.a spectral stochastic kinetic energ y backscatter scheme and its impact on flowdependent predictability in the ECMWF ensemble prediction system.J Atmos Sci,2009,66:603-626.
[53]Charron M,Pellerin G,Spacek L,et al.Toward random sampling of model error in the Canadian ensemble prediction system.Mon Wea Rev,2010,138:1877-1901.
[54]Berner J,Ha S Y,Hacker J P,et al.Model uncertainty in a mesosc ale ensemble prediction sy stem:S tochastic versus multiphysics representations.Mon Wea Rev,2011,139:1972-1995.
[55]Bouttier F,ViéB,Nuissier O,et al.Impact of stochastic physics in a convection-permitting ensemble.Mon Wea Rev,2012,140:11,3706-3721.
[56]李俊,杜钧,刘羽.北京“7.21”特大暴雨不同集合预报方案的对比试验.气象学报,2014,待发表.
[57]Jankov I,Gallus Jr W A,Segal M,et al.The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall.Wea Forecasting,2005,20:1048-1060.
[58]Jankov I,Schultz P J,Anderson C J,et al.The impact of different physical parameterizations and their interactions on cold season QPF in the American river basin.Journal of Hydrometeorology,2007,8(5):1141-1151.
[59]Jankov I,Gallus Jr W A,Segal M,et al.Influence of initial conditions on the WRF-ARW model QPF response to physical parameterization changes.Weather and Forecasting,2007,22(3):501-519.
[60]Du J.Impact of model error and imperfect initial condition per tur bations on ensemble-based probabilistic f orec asts:Unpredictable spots.17th Conference on Numerical Weather Prediction/21st Conference on Weather Analysis and Forecasting,Washington DC,Aug 1-5,2005,Amer Meteor Soc,2005.http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[61]Leoncini G,Plant R S,Gray S L,et al.Ensemble forecasts of a flood-producing storm:Comparison of the influence of modelstate perturbations and parameter modifications.Quarterly Journal of the Royal Meteorological Society,2013,139(670):198-211.
[62]Zhang D L,Lin Y,Zhao P,et al.The Beijing extreme rainfall of 21 July 2012:“Right results”but for wrong reasons.Geophys Res Lett,2013,40:1426-1431.
[63]Houtekamer P L,Mitchell H L.Data assimilation using an ensemble Kalman filter technique.Mon Wea Rev,1998,126:796-811.
[64]Houtekamer P L,Mitchell H L.A sequential ensemble Kalman filter for atmospheric data assimilation.Mon Wea Rev,2001,129:123-137.
[65]Anderson J L.An ensemble adjustment Kalman filter for data assimilation.Mon Wea Rev,2001,129:2884-2903.
[66]Evensen G.The ensemble Kalman filter:Theoretical formulation and practical implementation.Ocean Dyn,2003,53:343-367.
[67]Du J,Tracton M S.Impact of lateral boundary conditions on regional-model ensemble predicion.In:Ritchie H.Research Activities in Atmospheric and Oceanic Modelling.Report 28,CAS/JSC Working Group Numerical Experimentation(WGNE),WMO/TD-No.942,6.7-6.8,1999.
[68]Marsigli C A,Montani A,Paccagnella T.Provision of boundary conditions to convection-permitting ensemble:Comparison of two different approaches.Nonlinear Processes in Geophysics,2014,21:393-403.
[69]Hoffman R N,Kalney E.Lagged average forecasting,an alternative to Monte Carlo forecasting.Tellus A,1983,35A(2):100-118.
[70]Ebert E E.Ability of a poor man’s ensemble to predict the probability and distribution of precipitation.Mon Wea Rev,2001,129:2461-2479.
[71]Krishnamurti T N,Kishtawal C M,La Row T,et al.Improved weather and seasonal c limate f orec asts f rom multimodel superensemble.Science,1999,285(5433):1548-1550.
[72]Du J.Hybrid ensemble prediction system:A new ensembling approach.Symposium on the 50th Anniversary of Operational Numerical Weather Prediction,University of Maryland,College Park,Maryland,June 14-17,2004.Amer Meteor Soc,http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[73]Schwartz C S,et al.Toward improved convection-allowing ensembles:Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership.Wea Forecasting,2010,25:263-280.
[74]杜钧,Grumm R H,邓国.预报异常极端高影响天气的“集合异常预报法”:以北京2012.7.21特大暴雨为例.大气科学,2014,38(4):685-699.
[75]Hamill T M,Whitaker J S,Mullen S L.Reforecasts:An important dataset for improving weather predictions.Bull Amer Meteor Soc,2006,87:33-46.
[76]Hamill T M,Whitaker J S.Probabilistic quantitative precipitation forecasts based on reforecast analogs:Theory and application.Mon Wea Rev,2006,134:3209-3229.
[77]Hamill T M,Bates G T,Whitaker J S,et al.NOAA's second-generation global medium-range ensemble reforecast dataset.Bull Amer Meteor Soc,2013,94:1553-1565.
[78]Qian W H,Li J,Shan X L.Application of synoptic-scale anomalous winds predicted by medium-range weather forecast models on the regional heavy rainfall in China in 2010.Science China:Earth Sciences,2013,doi:10.1007/s11430-013-4586-5.
[79]丑纪范.数值天气预报的创新之路——从初值问题到反问题.气象学报,2007,65(5):673-682.
[80]任宏利,丑纪范.统计-动力相结合的相似误差订正法.气象学报,2005,63(6):988-993.
[81]龚建东,丑纪范.论过去资料在数值天气预报中使用的理论和方法.高原气象,1999,18(3):392-399.
[82]邱崇践,丑纪范.天气预报的相似-动力方法.大气科学,1989,13(1):20-28.
[83]Fang X Q,Kuo Y H.Improving ensemble-based quantitative precipitation forecast for topography-enhanced typhoon heavy rainfall over Taiwan with a modified probability-matching technique.Mon Wea Rev,2013,141:3908-3932.
[84]Ebert E E.Probability-matched ensemble mean.2001.http://www.cawcr.gov.au/staff/eee/etrap/probmatch.html
[85]李俊,杜钧,陈超君.降水偏差订正的频率(或面积)匹配方法介绍和分析.气象,2014,40(5):580-588.
[86]高守亭.大气中尺度运动的动力学基础及预报方法.北京:气象出版社,2007.
[87]王成鑫,高守亭,梁莉,等.动力因子对地形影响下的四川暴雨落区的诊断分析.大气科学,2013,37(5):1099-1110.
[88]许娈,何金海,高守亭,等.集合动力因子对登陆台风“莫拉克”(0908)暴雨落区的诊断与预报研究.大气科学,2013,37(1):23-35.
[89]冉令坤,齐彦斌,郝寿昌.“7·21”暴雨过程动力因子分析和预报研究.大气科学,2014,38(1):83-100.
[90]Torn R D,Hakim G J.Ensemble-based sensitivity analysis.Mon Wea Rev,2008,136,663-677.
[91]Zheng M H,Chang E K M,Colle B A.Ensemble sensitivity tools for assessing extratropical cyclone intensity and track predictability.Wea and Forecasting,2013,28(5):1133-1156.
[92]Emanuel K,Langland R.FASTEX adaptive obser vations workshop.Bull Amer Meteor Soc,1998,79:1915-1919.
[93]Langland R H.Issues in targeted observing.Quart J Roy Meteor Soc,2005,131:3409-3425.
[94]李俊,王明欢,公颖,等.AREM短期集合预报系统及其降水预报检验.暴雨灾害,2010,29(1):30-37.
[95]Toth Z,Szunyogh I,Majumdar S,et al.Targeted observations at NCEP:Toward an operational implementation.4th Sym Integrated Obs Sys,Amer Meteo Soc,2000.
[96]Szunyogh I,Toth Z,Morss R C,et al.The effect of targeted dropsonde observations during the 1999 Winter Storm Reconnaissance Program.Mon Wea Rev,2000,128:3520-3537.
[97]Chang E K M,Yu D B.Characteristics of wave packets in the upper troposphere.Part I:Northern Hemisphere winter.J Atmos Sci,1999,56:1708-1728.
[98]Chang E K M.Characteristics of wave packets in the upper troposphere.Part II:Seasonal and hemispheric variations.J Atmos Sci,1999,56:1729-1747.
[99]Yeh T C.On energy dispersion in the atmosphere.J Atmos Sci,1949,6:1-16.
[100]陶诗言,卫捷,梁丰,等.Rossby波的下游效应引发我国高影响天气的分析.气象,2010,36(7):81-93.
[101]邓国,龚建东,邓莲堂,等.国家级区域集合预报系统研发和性能检验.应用气象学报,2010,21(5):513-523.
1TIGGE(the THORPEX Interactive Grand Global Ensemble):THORPEX(The Observing System Research and Predictability Experiment)是世界气象组织(WMO)世界天气研究计划(WWRP)中的一个研究项目:http://www.wmo.int/pages/prog/arep/wwrp/new/thorpex_new.html
1洪景山,个人交流
1为了尽量不浪费其他成员的有用信息而又可采用最佳成员,一个折中的办法是先对集合成员进行聚类,然后在每一分类的子集合中选出最佳的成员作为其代表预报
1顺便指出,如果把一个降水预报的降水量出现频率同观测降水频率相比较,则此法就可应用到降水预报的偏差订正中。李俊等[85]的试验表明此法对预报降水量和降水区面积偏差订正都有很好的效果,但却没有能力来订正预报降水的位置误差
1但这些个例间只是大致相似而已,它们所处的大尺度环流背景其实还是有很大的差别,但这对集合各成员来说却并不是问题(即具有完全一致的大尺度环流背景)
[2]陶诗言,等.中国之暴雨.北京:科学出版社,1980.
[3]陈云峰,高歌.近20年我国气象灾害损失的初步分析.气象,2010,36(2):76-80.
[4]张大林.各种非绝热物理过程在中尺度模式中的作用.大气科学,1998,22(4):548-561.
[5]Lorenz E N.混沌的本质.刘式达,刘式适,严中伟译.北京:气象出版社,1997.
[6]丑纪范.大气科学中的非线性与复杂性.北京:气象出版社,2002.
[7]杜钧,陈静.单一值预报向概率预报转变的基础:谈谈集合预报及其带来的变革.气象,2010,36(11):1-11.
[8]王东海,杜钧,柳崇健.正确认识和对待天气预报的不确定性.气象,2011,37(4):385-392.
[9]杜钧,陈静.天气预报的公众评价与发布形式的变革.气象,2010,36(1):1-6.
[10]杜钧,康志明.天气预报中不确定性问题的调查分析.气象科技进展,2014,4(1):58-67.
[11]US National Research Council.Completing the Forecast:Characterizing and Communicating Uncertainty for Better Decision Using Weather and Climate Forecasts.Washington D C:The National Academy Press,2006.
[12]杜钧,邓国.单一值预报向概率预报转变的价值:谈谈概率预报的检验和应用.气象,2010,36(12):10-18.
[13]杜钧.集合预报的现状和前景.应用气象学报,2002,13(1):16-28.
[14]Du J,Yu R C,Cui C G,et al.Using a mesoscale ensemble to predict forecast error and perform targeted observation.Acta Oceanologica Sinica,2014,33(1):83-91.
[15]Du J,Mullen S L,Sanders F.Short-range ensemble forecasting of quantitative precipitation.Mon Wea Rev,1997,125:2427-2459.
[16]Du J,Zhou B B.A dynamical performance-ranking method for predicting individual ensemble member’s performance and its application to ensemble averaging.Mon Wea Rev,2011,129(10):3284-3303.
[17]Li J,D u J,Zhang D L,et al.Ensemble-based analysis and sensitivity of mesoscale forecasts of a vortex over southwest China.Q J R Meteorol Soc,2014,140:766-782.
[18]Zhang F,Weng Y,Kuo Y H,et al.Predicting typhoon Morakot’s catastrophic rainfall with a convection-permitting mesoscale ensemble system.Weather and Forecasting,2010,25:1816-1825.
[19]Stensrud D J,Brooks H E,Du J,et al.Using ensembles for short-range forecasting.Mon Wea Rev,1999,127:433-446.
[20]Yuan H,Mullen S L,Gao X,et al.Verification of probabilistic quantitative precipitation forecasts over the southwest United States during winter 2002/03 by the RSM ensemble system.Mon Wea Rev,2005,133:279-294.
[21]李俊,杜钧,王明欢,等.中尺度暴雨集合预报系统研发中的初值扰动试验.高原气象,2009,28(6):1365-1375.
[22]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.
[23]Toth Z,Kalnay E.Ensemble forecasting at NMC:The generation of perturbations.Bul Amer Meteor Soc,1993,74:2317-2330.
[24]Toth Z,Kalnay E.Ensemble forecasting at NCEP and the breeding method.Mon Wea Rev,1997,125:3297-3319.
[25]Johnson A,Wang X G,Xue M,et al.Multiscale characteristics and evolution of perturbations for warm season convection-allowing precipitation forecast:Dependence on background flow and method of perturbation.Mon Wea Rev,2014,142(3):1053-1073.
[26]李俊,杜钧,王明欢,等.AREM模式两种初值扰动方案的集合降水预报试验及检验.热带气象学报,2010,26(6):217-228.
[27]Du J,Gayno G,Mitchell K E,et al.Sensitivity study of T2m and precipitation forecasts to soil moisture initial condition using NCEP WRF ensemble system.22nd Conf on Weather Analysis and Forecasting/18th Conf on Numerical Weather Prediction,2007,Park City,UT.American Meteor Soc.
[28]Aligo E A,Gallus Jr W A,Segal M.Summer rainfall forecast spread in an ensemble initialized with different soil moisture analyses.Weather and Forecasting,2007,22:2,299-314.
[29]Sutton C,Hamill T M,Warner T T.Will perturbing soil moisture improve warm-season ensemble forecasts?A proof of concept.Mon Wea Rev,2006,134:3174-3189.
[30]Clark A J,Kain J S,Stensrud D J,et al.Probabilistic precipitation forecast skill as a function of ensemble size and spatial scale in a convection-allowing ensemble.Mon Wea Rev,2011,139:1410-1418.
[31]Richardson D S.Measures of skill and value of ensemble prediction systems,their interrelationship and the effect of ensemble size.Quart J Roy Meteor Soc,2001,127:2473-2489.
[32]Clark A J,Gallus Jr W A,Xue M,et al.A comparison of precipitation forecast skill between small convection-permitting and large convection-parameterizing ensembles.Wea and Forecasting,2009,24:1121-1140.
[33]Clark A J,Gallus Jr W A,Xue M,et al.Convection-allowing and convection-parameterizing ensemble forecasts of a mesoscale convective vortex and associated severe weather.Wea Forecasting,2010,25:1052-1081.
[34]Ma J H,Zhu Y J,Wobus R,et al.An effective configuration of ensemble size and horizontal resolution for the NCEP GEFS.Adv Atmos Sci,2012,29(4):782-794.
[35]Aligo E A,Gallus Jr W A,Segal M.On the impact of WRF model vertical grid resolution on Midwest summer rainfall forecasts.Weather and Forecasting,2009,24:2,575-594.
[36]Brooks H E,Tracton M S,Stensrud D J,et al.Short-range ensemble forecasting:Report from a workshop,25-27 July 1994.Bull Amer Meteorol Soc,1995,74:2317-2330.
[37]Mullen S L,Du J,Sanders F.The Dependence of ensemble dispersion on analysis–forecast systems:Implications to shortrange ensemble forecasting of precipitation.Mon Wea Rev,1999,127:1674-1686.
[38]Du J,Tracton M S.Implementation of a real-time short-range ensemble forecasting system at NCEP:An update.9th Conference on Mesoscale Processes,2001,Ft Lauderdale,Florida.Amer Meteor Soc,355-356.http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[39]Du J,Di Mego G,Tracton M S,et al.NCEP short-range ensemble forecasting(SREF)system:multi-IC,multi-model and multiphysics approach.Research Activities in Atmospheric and Oceanic Modelling(edited by J.Cote),Report 33,CAS/JSC Working Group Numerical Experimentation(WGNE),WMO/TD,2003,No.1161,5.09-5.10.http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[40]Zhou B B,Du J.Fog prediction f rom a multimodel mesoscale ensemble prediction system.Wea and Forecasting,2010,25:303-322.
[41]吴政谦,徐海明,王东海,等.中尺度多模式超级集合预报对2010年6月19—20日中国南方大暴雨过程的分析.热带气象学报,2012(5):653-663.
[42]Duan Y H,Gong J D,Du J,et al.An overview of the Beijing 2008 Olympics Research and Development Project(B08RDP).Bull Amer Meteor Soc,2012,93:381-403.
[43]Du J,et al.The NOAA/NWS/NCEP Short Range Ensemble Forecast(SREF)system:Evaluation of an initial condition vs multiple model physics ensemble approach.16th Conf on Numerical Weather Prediction/20th Conf on Weather Analysis and Forecasting,Seattle,WA.Amer Meteor Soc,2004.http://ams.confex.com/ams/pdfpapers/71107.pdf
[44]Kong F Y,et al.Preliminary analysis on the real-time storm-scale ensemble forecasts produced as a part of the NOAA Hazardous Weather Testbed 2007 Spring Experiment.22nd Conf on Weather Analysis and Forecasting/18th Conf on Numerical Weather Prediction,Park City,UT.Amer Meteor Soc,2007.http://ams.confex.com/ams/pdfpapers/124667.pdf
[45]Gilmour I,Smith L A,Buizza R.Linear Regime Duration:Is 24 Hours a Long Time in Synoptic Weather Forecasting?J Atmos Sci,2001,58:3525-3539.
[46]Clark A J,Gallus Jr W A,Chen T C.Contributions of mixed physics versus perturbed initial/lateral boundary conditions to ensemble-based precipitation forecast skill.Monthly Weather Review,2008,136:6,2140-2156.
[47]Stensrud D J,Bao J W,Warner T T.Using initial condition and model physics perturbations in short-range ensemble simulations of mesoscale convective systems.Mon Wea Rev,2000,128:2077-2107.
[48]Buizza R,Palmer T.Stochastic representation of model uncertainties in the ECMWF ensemble prediction system.Quart J Roy Meteor Soc.,1999,125:2887-2908.
[49]谭燕,陈德辉.基于非静力模式物理扰动的中尺度集合预报试验.应用气象学报,2007,18(3):396-406.
[50]Teixeira J,Reynolds C.Stochastic nature of physical parameterizations in ensemble prediction:A stochastic convection approach.Mon Wea Rev,2008,136:483-496.
[51]Li X,Charron M,Spacek L,et al.A regional ensemble prediction system based on moist targeted singular vectors and stochastic parameter perturbations.Mon Wea Rev,2008,136:443-462.
[52]Berner J,Shutts G J,Leutbecher M,et al.a spectral stochastic kinetic energ y backscatter scheme and its impact on flowdependent predictability in the ECMWF ensemble prediction system.J Atmos Sci,2009,66:603-626.
[53]Charron M,Pellerin G,Spacek L,et al.Toward random sampling of model error in the Canadian ensemble prediction system.Mon Wea Rev,2010,138:1877-1901.
[54]Berner J,Ha S Y,Hacker J P,et al.Model uncertainty in a mesosc ale ensemble prediction sy stem:S tochastic versus multiphysics representations.Mon Wea Rev,2011,139:1972-1995.
[55]Bouttier F,ViéB,Nuissier O,et al.Impact of stochastic physics in a convection-permitting ensemble.Mon Wea Rev,2012,140:11,3706-3721.
[56]李俊,杜钧,刘羽.北京“7.21”特大暴雨不同集合预报方案的对比试验.气象学报,2014,待发表.
[57]Jankov I,Gallus Jr W A,Segal M,et al.The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall.Wea Forecasting,2005,20:1048-1060.
[58]Jankov I,Schultz P J,Anderson C J,et al.The impact of different physical parameterizations and their interactions on cold season QPF in the American river basin.Journal of Hydrometeorology,2007,8(5):1141-1151.
[59]Jankov I,Gallus Jr W A,Segal M,et al.Influence of initial conditions on the WRF-ARW model QPF response to physical parameterization changes.Weather and Forecasting,2007,22(3):501-519.
[60]Du J.Impact of model error and imperfect initial condition per tur bations on ensemble-based probabilistic f orec asts:Unpredictable spots.17th Conference on Numerical Weather Prediction/21st Conference on Weather Analysis and Forecasting,Washington DC,Aug 1-5,2005,Amer Meteor Soc,2005.http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[61]Leoncini G,Plant R S,Gray S L,et al.Ensemble forecasts of a flood-producing storm:Comparison of the influence of modelstate perturbations and parameter modifications.Quarterly Journal of the Royal Meteorological Society,2013,139(670):198-211.
[62]Zhang D L,Lin Y,Zhao P,et al.The Beijing extreme rainfall of 21 July 2012:“Right results”but for wrong reasons.Geophys Res Lett,2013,40:1426-1431.
[63]Houtekamer P L,Mitchell H L.Data assimilation using an ensemble Kalman filter technique.Mon Wea Rev,1998,126:796-811.
[64]Houtekamer P L,Mitchell H L.A sequential ensemble Kalman filter for atmospheric data assimilation.Mon Wea Rev,2001,129:123-137.
[65]Anderson J L.An ensemble adjustment Kalman filter for data assimilation.Mon Wea Rev,2001,129:2884-2903.
[66]Evensen G.The ensemble Kalman filter:Theoretical formulation and practical implementation.Ocean Dyn,2003,53:343-367.
[67]Du J,Tracton M S.Impact of lateral boundary conditions on regional-model ensemble predicion.In:Ritchie H.Research Activities in Atmospheric and Oceanic Modelling.Report 28,CAS/JSC Working Group Numerical Experimentation(WGNE),WMO/TD-No.942,6.7-6.8,1999.
[68]Marsigli C A,Montani A,Paccagnella T.Provision of boundary conditions to convection-permitting ensemble:Comparison of two different approaches.Nonlinear Processes in Geophysics,2014,21:393-403.
[69]Hoffman R N,Kalney E.Lagged average forecasting,an alternative to Monte Carlo forecasting.Tellus A,1983,35A(2):100-118.
[70]Ebert E E.Ability of a poor man’s ensemble to predict the probability and distribution of precipitation.Mon Wea Rev,2001,129:2461-2479.
[71]Krishnamurti T N,Kishtawal C M,La Row T,et al.Improved weather and seasonal c limate f orec asts f rom multimodel superensemble.Science,1999,285(5433):1548-1550.
[72]Du J.Hybrid ensemble prediction system:A new ensembling approach.Symposium on the 50th Anniversary of Operational Numerical Weather Prediction,University of Maryland,College Park,Maryland,June 14-17,2004.Amer Meteor Soc,http://www.emc.ncep.noaa.gov/mmb/SREF/reference.html
[73]Schwartz C S,et al.Toward improved convection-allowing ensembles:Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership.Wea Forecasting,2010,25:263-280.
[74]杜钧,Grumm R H,邓国.预报异常极端高影响天气的“集合异常预报法”:以北京2012.7.21特大暴雨为例.大气科学,2014,38(4):685-699.
[75]Hamill T M,Whitaker J S,Mullen S L.Reforecasts:An important dataset for improving weather predictions.Bull Amer Meteor Soc,2006,87:33-46.
[76]Hamill T M,Whitaker J S.Probabilistic quantitative precipitation forecasts based on reforecast analogs:Theory and application.Mon Wea Rev,2006,134:3209-3229.
[77]Hamill T M,Bates G T,Whitaker J S,et al.NOAA's second-generation global medium-range ensemble reforecast dataset.Bull Amer Meteor Soc,2013,94:1553-1565.
[78]Qian W H,Li J,Shan X L.Application of synoptic-scale anomalous winds predicted by medium-range weather forecast models on the regional heavy rainfall in China in 2010.Science China:Earth Sciences,2013,doi:10.1007/s11430-013-4586-5.
[79]丑纪范.数值天气预报的创新之路——从初值问题到反问题.气象学报,2007,65(5):673-682.
[80]任宏利,丑纪范.统计-动力相结合的相似误差订正法.气象学报,2005,63(6):988-993.
[81]龚建东,丑纪范.论过去资料在数值天气预报中使用的理论和方法.高原气象,1999,18(3):392-399.
[82]邱崇践,丑纪范.天气预报的相似-动力方法.大气科学,1989,13(1):20-28.
[83]Fang X Q,Kuo Y H.Improving ensemble-based quantitative precipitation forecast for topography-enhanced typhoon heavy rainfall over Taiwan with a modified probability-matching technique.Mon Wea Rev,2013,141:3908-3932.
[84]Ebert E E.Probability-matched ensemble mean.2001.http://www.cawcr.gov.au/staff/eee/etrap/probmatch.html
[85]李俊,杜钧,陈超君.降水偏差订正的频率(或面积)匹配方法介绍和分析.气象,2014,40(5):580-588.
[86]高守亭.大气中尺度运动的动力学基础及预报方法.北京:气象出版社,2007.
[87]王成鑫,高守亭,梁莉,等.动力因子对地形影响下的四川暴雨落区的诊断分析.大气科学,2013,37(5):1099-1110.
[88]许娈,何金海,高守亭,等.集合动力因子对登陆台风“莫拉克”(0908)暴雨落区的诊断与预报研究.大气科学,2013,37(1):23-35.
[89]冉令坤,齐彦斌,郝寿昌.“7·21”暴雨过程动力因子分析和预报研究.大气科学,2014,38(1):83-100.
[90]Torn R D,Hakim G J.Ensemble-based sensitivity analysis.Mon Wea Rev,2008,136,663-677.
[91]Zheng M H,Chang E K M,Colle B A.Ensemble sensitivity tools for assessing extratropical cyclone intensity and track predictability.Wea and Forecasting,2013,28(5):1133-1156.
[92]Emanuel K,Langland R.FASTEX adaptive obser vations workshop.Bull Amer Meteor Soc,1998,79:1915-1919.
[93]Langland R H.Issues in targeted observing.Quart J Roy Meteor Soc,2005,131:3409-3425.
[94]李俊,王明欢,公颖,等.AREM短期集合预报系统及其降水预报检验.暴雨灾害,2010,29(1):30-37.
[95]Toth Z,Szunyogh I,Majumdar S,et al.Targeted observations at NCEP:Toward an operational implementation.4th Sym Integrated Obs Sys,Amer Meteo Soc,2000.
[96]Szunyogh I,Toth Z,Morss R C,et al.The effect of targeted dropsonde observations during the 1999 Winter Storm Reconnaissance Program.Mon Wea Rev,2000,128:3520-3537.
[97]Chang E K M,Yu D B.Characteristics of wave packets in the upper troposphere.Part I:Northern Hemisphere winter.J Atmos Sci,1999,56:1708-1728.
[98]Chang E K M.Characteristics of wave packets in the upper troposphere.Part II:Seasonal and hemispheric variations.J Atmos Sci,1999,56:1729-1747.
[99]Yeh T C.On energy dispersion in the atmosphere.J Atmos Sci,1949,6:1-16.
[100]陶诗言,卫捷,梁丰,等.Rossby波的下游效应引发我国高影响天气的分析.气象,2010,36(7):81-93.
[101]邓国,龚建东,邓莲堂,等.国家级区域集合预报系统研发和性能检验.应用气象学报,2010,21(5):513-523.
1TIGGE(the THORPEX Interactive Grand Global Ensemble):THORPEX(The Observing System Research and Predictability Experiment)是世界气象组织(WMO)世界天气研究计划(WWRP)中的一个研究项目:http://www.wmo.int/pages/prog/arep/wwrp/new/thorpex_new.html
1洪景山,个人交流
1为了尽量不浪费其他成员的有用信息而又可采用最佳成员,一个折中的办法是先对集合成员进行聚类,然后在每一分类的子集合中选出最佳的成员作为其代表预报
1顺便指出,如果把一个降水预报的降水量出现频率同观测降水频率相比较,则此法就可应用到降水预报的偏差订正中。李俊等[85]的试验表明此法对预报降水量和降水区面积偏差订正都有很好的效果,但却没有能力来订正预报降水的位置误差
1但这些个例间只是大致相似而已,它们所处的大尺度环流背景其实还是有很大的差别,但这对集合各成员来说却并不是问题(即具有完全一致的大尺度环流背景)