EnKF同化雷达资料对一次极端局地强降水事件预报影响及其可预报性分析
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摘要
局地强降水可以引发山洪、泥石流等次生灾害,目前准确预报局地强降水依然是天气预报业务的难点.本文针对一次发生在西北太平洋副热带高压边缘、导致12人死亡的极端局地强降水事件,利用集合卡尔曼滤波(En KF)开展多普勒雷达径向风观测资料同化试验,并对En KF同化过程不确定性进行分析.结果表明:不同化观测资料,采用单一初值的确定性预报或增加初值扰动、采用多物理过程的集合预报均不能正确预报强降水发生位置,而利用En KF同化雷达径向速度观测资料能有效改进确定性和集合预报效果,特别是强降水位置预报.通过En KF同化雷达资料,建立深厚的中尺度对流系统是改进降水预报效果的直接原因.在具备了对流发生条件的大尺度环境背景场中,上游地区、对流层中下层经向风和水汽场的合理扰动是影响同化过程和降水预报的关键因素.该个例预报过程受实际可预报性影响,具有不确定性,大尺度初始条件的差异或初始扰动场振幅偏小导致的En KF分析场差异都会对模拟结果造成较大影响,而采用En KF循环同化有助于提高该个例的预报准确性.敏感性试验还表明未来通过改进数值模式或改善观测系统,提供更准确观测信息,可以对此类短时强降水事件做出更准确预报.
引文
兰伟仁,朱江,Xue M,Gao J D,雷霆.2010a.风暴尺度天气下利用集合卡尔曼滤波模拟多普勒雷达资料同化试验Ⅰ:不考虑模式误差的情形.大气科学,34:640-652
兰伟仁,朱江,Xue M,雷霆,Gao J D.2010b.风暴尺度天气下利用集合卡尔曼滤波模拟多普勒雷达资料同化试验Ⅱ:考虑模式误差的情形.大气科学,34:737-753
闵锦忠,陈杰,王世璋,鲍艳松.2011.WRF-En SRF同化系统的效果检验及其应用.气象科学,31:135-144
许小永,刘黎平,郑国光.2006.集合卡尔曼滤波同化多普勒雷达资料的数值试验.大气科学,30:712-728
张小玲,余蓉,杜牧云.2014.梅雨锋上短时强降水系统的发展模态.大气科学,38:770-781
朱本璐,林万涛,张云.2009.初始扰动对一次华南暴雨预报的影响的研究.大气科学,33:1333-1347
Aksoy A,Dowell D C,Snyder C.2009.A multi-case comparative assessment of the ensemble Kalman filter for assimilation of radar observations.Part I:Storm-scale analyses.Mon Weather Rev,137:1805-1824
Aksoy A,Dowell D C,Snyder C.2010.A multi-case comparative assessment of the ensemble Kalman filter for assimilation of radar observations.Part II:Short-range ensemble forecasts.Mon Weather Rev,138:1273-1292
Barker D M,Huang W,Guo Y R,Bourgeois A J,Xiao Q N.2004.Athree-dimensional variational data assimilation system for MM5:Implementation and initial results.Mon Weather Rev,132:897-914
Bei N F,Zhang F Q.2007.Mesoscale predictability of the torrential rainfall along the mei-yu front of China.Q J R Meteorol Soc,133:83-99
Dowell D C,Zhang F Q,Wicker L J,Snyder C,Crook A.2004.Wind and thermodynamic retrievals in the 17 May 1981Arcadia,Oklahoma,supercell:Ensemble Kalman filter experiments.Mon Weather Rev,132:1982-2005
Hong S Y,Dudhia J,Chen S H.2004.A revised approach to ice-microphysical processes for the bulk parameterization of cloud and precipitation.Mon Weather Rev,132:103-120
Liu J Y,Tan Z M.2009.Mesoscale predictability of Mei-yu heavy rainfall.Adv Atmos Sci,26:438-450
Lorenz.1969.Atmospheric predictability as revealed by naturally occurring analogues.J Atmos Sci,26:636-646
Melhauser C,Zhang F Q.2012.Practical and intrin-sic predictability of severe and convective weather at the mesoscales.J Atmos Sci,69:3350-3371
Meng Z Y,Zhang F Q.2007.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part II:Imperfect-model experiments.Mon Weather Rev,135:1403-1423
Meng Z Y,Zhang F Q.2008a.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part III:Comparison with 3DVAR in a real-data case study.Mon Weather Rev,136:522-540
Meng Z Y,Zhang F Q.2008b.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part IV:Performance over a warm-season month of June 2003.Mon Weather Rev,136:3671-3682
Noh Y,Cheon W G,Hong S Y.2003.Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data.Bound-Layer Meteor,107:401-427
Schumacher R S,Johnson R H.2005.Organization and environmental properties of extreme-rain-producing mesoscale convective systems.Mon Weather Rev,133:961-976
Schumacher R S,Johnson R H.2006.Characteristics of U.S.extreme rain events during 1999-2003.Weather Forecast,21:69-85
Sippel J A,Braun S A,Shie C L.2011.Environmental influences on the strength of Tropical Storm Debby(2006).J Atmos Sci,68:2557-2581
Sippel J A,Zhang F Q.2008.A probabilistic analysis of the dynamics and predictability of tropical cyclogenesis.J Atmos Sci,65:3440-3459
Sippel J A,Zhang F Q.2010.Factors affecting the predictability of Hurricane Humberto(2007).J Atmos Sci,67:1759-1778
Skamarock W C,Klemp J B,Dudhia J,Gill D O,Barker D M,Duda M G,Huang X Y,Wang W,Powers J R.2008.A description of the Advanced Research WRF version 3.NCAR Tech Note4751STR,113
Snyder C,Zhang F Q.2003.Tests of an ensemble Kalman filter for convective-scale data assimilation.Mon Weather Rev,131:1663-1677
Tippett M K,Anderson J L,Bishop C H,Hamill T M,Whitaker J S.2003.Ensemble square root filters.Mon Weather Rev,131:1485-1490
Tong M,Xue M.2005.Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model:OSS experiments.Mon Weather Rev,133:1789-1807
Xue M,Tong M,Droegemeier K K.2006.An OSSE framework based on the ensemble square-root Kalman filter for evaluating impact of data from radar networks on thunderstorm analysis and forecast.J Atmos Ocean Technol,23:46-66
Weng Y H,Zhang F.2012.Assimilating Airborne Doppler Radar Observations with an Ensemble Kalman Filter for Convection-Permitting Hurricane Initialization and Prediction:Katrina(2005).Mon Weather Rev,140:841-859
Whitaker J S,Hamill T M.2002.Ensemble data assimilation without perturbed observations.Mon Weather Rev,130:1913-1924
Zhang F Q,Snyder C,Rotunno R.2004.Tests of an ensemble Kalman filter for convective-scale data assimilation:Impact of initial estimate and observations.Mon Weather Rev,132:1238-1253
Zhang F Q,Odins A M,Nielsen-Gammon J W.2006a.Mesoscale predictability of an extreme warm-season precipitation event.Weather Forecast,21:149-166
Zhang F Q,Meng Z Y.Aksoy A.2006b.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part I:Perfect-model experiments.Mon Weather Rev,134:722-736
Zhang F Q,Weng Y H,Sippel A J,Meng Z Y.2009a.Convection-permitting hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter:Humberto(2007).Mon Weather Rev,137:2105-2125
Zhang F Q,Sippel J A.2009b.Effects of moist convection on hurricane predictability.J Atmos Sci,66:1944-1961
Zhang F Q,Weng Y H.2015.Modernizing the prediction of hurricane intensity and associated hazards:A five-year real-time forecast experiment concluded by superstorm Sandy(2012).Bull Amer Meteorol Soc,96:25-33
兰伟仁,朱江,Xue M,雷霆,Gao J D.2010b.风暴尺度天气下利用集合卡尔曼滤波模拟多普勒雷达资料同化试验Ⅱ:考虑模式误差的情形.大气科学,34:737-753
闵锦忠,陈杰,王世璋,鲍艳松.2011.WRF-En SRF同化系统的效果检验及其应用.气象科学,31:135-144
许小永,刘黎平,郑国光.2006.集合卡尔曼滤波同化多普勒雷达资料的数值试验.大气科学,30:712-728
张小玲,余蓉,杜牧云.2014.梅雨锋上短时强降水系统的发展模态.大气科学,38:770-781
朱本璐,林万涛,张云.2009.初始扰动对一次华南暴雨预报的影响的研究.大气科学,33:1333-1347
Aksoy A,Dowell D C,Snyder C.2009.A multi-case comparative assessment of the ensemble Kalman filter for assimilation of radar observations.Part I:Storm-scale analyses.Mon Weather Rev,137:1805-1824
Aksoy A,Dowell D C,Snyder C.2010.A multi-case comparative assessment of the ensemble Kalman filter for assimilation of radar observations.Part II:Short-range ensemble forecasts.Mon Weather Rev,138:1273-1292
Barker D M,Huang W,Guo Y R,Bourgeois A J,Xiao Q N.2004.Athree-dimensional variational data assimilation system for MM5:Implementation and initial results.Mon Weather Rev,132:897-914
Bei N F,Zhang F Q.2007.Mesoscale predictability of the torrential rainfall along the mei-yu front of China.Q J R Meteorol Soc,133:83-99
Dowell D C,Zhang F Q,Wicker L J,Snyder C,Crook A.2004.Wind and thermodynamic retrievals in the 17 May 1981Arcadia,Oklahoma,supercell:Ensemble Kalman filter experiments.Mon Weather Rev,132:1982-2005
Hong S Y,Dudhia J,Chen S H.2004.A revised approach to ice-microphysical processes for the bulk parameterization of cloud and precipitation.Mon Weather Rev,132:103-120
Liu J Y,Tan Z M.2009.Mesoscale predictability of Mei-yu heavy rainfall.Adv Atmos Sci,26:438-450
Lorenz.1969.Atmospheric predictability as revealed by naturally occurring analogues.J Atmos Sci,26:636-646
Melhauser C,Zhang F Q.2012.Practical and intrin-sic predictability of severe and convective weather at the mesoscales.J Atmos Sci,69:3350-3371
Meng Z Y,Zhang F Q.2007.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part II:Imperfect-model experiments.Mon Weather Rev,135:1403-1423
Meng Z Y,Zhang F Q.2008a.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part III:Comparison with 3DVAR in a real-data case study.Mon Weather Rev,136:522-540
Meng Z Y,Zhang F Q.2008b.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part IV:Performance over a warm-season month of June 2003.Mon Weather Rev,136:3671-3682
Noh Y,Cheon W G,Hong S Y.2003.Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data.Bound-Layer Meteor,107:401-427
Schumacher R S,Johnson R H.2005.Organization and environmental properties of extreme-rain-producing mesoscale convective systems.Mon Weather Rev,133:961-976
Schumacher R S,Johnson R H.2006.Characteristics of U.S.extreme rain events during 1999-2003.Weather Forecast,21:69-85
Sippel J A,Braun S A,Shie C L.2011.Environmental influences on the strength of Tropical Storm Debby(2006).J Atmos Sci,68:2557-2581
Sippel J A,Zhang F Q.2008.A probabilistic analysis of the dynamics and predictability of tropical cyclogenesis.J Atmos Sci,65:3440-3459
Sippel J A,Zhang F Q.2010.Factors affecting the predictability of Hurricane Humberto(2007).J Atmos Sci,67:1759-1778
Skamarock W C,Klemp J B,Dudhia J,Gill D O,Barker D M,Duda M G,Huang X Y,Wang W,Powers J R.2008.A description of the Advanced Research WRF version 3.NCAR Tech Note4751STR,113
Snyder C,Zhang F Q.2003.Tests of an ensemble Kalman filter for convective-scale data assimilation.Mon Weather Rev,131:1663-1677
Tippett M K,Anderson J L,Bishop C H,Hamill T M,Whitaker J S.2003.Ensemble square root filters.Mon Weather Rev,131:1485-1490
Tong M,Xue M.2005.Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model:OSS experiments.Mon Weather Rev,133:1789-1807
Xue M,Tong M,Droegemeier K K.2006.An OSSE framework based on the ensemble square-root Kalman filter for evaluating impact of data from radar networks on thunderstorm analysis and forecast.J Atmos Ocean Technol,23:46-66
Weng Y H,Zhang F.2012.Assimilating Airborne Doppler Radar Observations with an Ensemble Kalman Filter for Convection-Permitting Hurricane Initialization and Prediction:Katrina(2005).Mon Weather Rev,140:841-859
Whitaker J S,Hamill T M.2002.Ensemble data assimilation without perturbed observations.Mon Weather Rev,130:1913-1924
Zhang F Q,Snyder C,Rotunno R.2004.Tests of an ensemble Kalman filter for convective-scale data assimilation:Impact of initial estimate and observations.Mon Weather Rev,132:1238-1253
Zhang F Q,Odins A M,Nielsen-Gammon J W.2006a.Mesoscale predictability of an extreme warm-season precipitation event.Weather Forecast,21:149-166
Zhang F Q,Meng Z Y.Aksoy A.2006b.Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation.Part I:Perfect-model experiments.Mon Weather Rev,134:722-736
Zhang F Q,Weng Y H,Sippel A J,Meng Z Y.2009a.Convection-permitting hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter:Humberto(2007).Mon Weather Rev,137:2105-2125
Zhang F Q,Sippel J A.2009b.Effects of moist convection on hurricane predictability.J Atmos Sci,66:1944-1961
Zhang F Q,Weng Y H.2015.Modernizing the prediction of hurricane intensity and associated hazards:A five-year real-time forecast experiment concluded by superstorm Sandy(2012).Bull Amer Meteorol Soc,96:25-33