雷达反射率三维拼图观测资料在北方区域数值模式预报系统中的同化应用研究
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摘要
以业务应用为目标,开展雷达反射率三维拼图观测资料在北方区域数值预报系统中的同化应用研究。采用雷达反射率间接同化方法同化北方雷达反射率拼图观测资料,重点关注其对降水、湿度、温度及风的预报能力影响。首先,基于2017年8月雷达拼图观测资料批量同化和对比试验,对雷达拼图资料同化应用效果进行定量评估,结果表明雷达拼图资料同化虽然加大了地面风场预报误差,但在降水预报和湿度、温度预报等方面有明显的改善作用。其次,选择在业务中预报难度较大的强降水个例开展分析研究,分析表明:(1)同化雷达拼图观测资料有效提高了模式降水预报性能,临近降水发生的循环起报时次预报效果更好;(2)对于短时间多次强降水过程发生的预报,循环同化雷达拼图资料可及时弥补模式中由于前次降水导致的水汽、能量等消耗及热/动力条件削弱,持续支持降水系统发展。最后,通过考察雷达反射率的不同同化方案,发现同化反演水凝物或者估计水汽均能改善模式降水预报性能,但是同化估计水汽对降水预报性能的改善更为明显,联合使用两方案能同时对水凝物分布、热力场等进行调整,可提高模式降水预报性能。
The three-dimensional(3 D) radar reflectivity mosaic covering North China is assimilated into the regional numerical weather forecasting system RMAPS-ST via an indirect radar reflectivity assimilation method of WRF-3 DVAR to improve the model forecasting skill with focuses on the influences on precipitation, specific humidity, temperature and wind forecasting. Firstly, experiments with/without radar reflectivity mosaic assimilation have been performed from 1 to 31 August 2017, and quantitative verification is conducted based on the batch experiments. The results show that the radar reflectivity mosaic assimilation significantly improves the skill for precipitation, specific humidity and temperature forecasting but increases the forecasting error in the wind field. Secondly, how the radar reflectivity mosaic assimilation improves the forecasting skill of RMAPS-ST is displayed based on a heavy rainfall case, which shows:(1) Precipitation forecasting skill is greatly improved and the cycle that is closer to the beginning of rainfall has higher forecasting skill by assimilating radar mosaic.(2) Water vapor, energy and thermal condition which are consumed and weakened by the previous rainfall can be boosted and re-organized to trigger new rainfall by assimilating radar mosaic reflectivity in the cycling way, which plays an important role in the situation of multiple rainfalls occurring during a short time period. Finally, two schemes of the WRF-3 DVAR indirect radar reflectivity assimilation method are tested. Results indicate that the retrieved hydrometeor assimilation scheme and the derived water vapor assimilation scheme both can improve precipitation forecasting, but the latter one plays a more important role and using two schemes together can make reasonable adjustments for the rainwater, snow water, water vapor and thermal condition, which are critical for the improvement of precipitation forecasting.
The three-dimensional(3 D) radar reflectivity mosaic covering North China is assimilated into the regional numerical weather forecasting system RMAPS-ST via an indirect radar reflectivity assimilation method of WRF-3 DVAR to improve the model forecasting skill with focuses on the influences on precipitation, specific humidity, temperature and wind forecasting. Firstly, experiments with/without radar reflectivity mosaic assimilation have been performed from 1 to 31 August 2017, and quantitative verification is conducted based on the batch experiments. The results show that the radar reflectivity mosaic assimilation significantly improves the skill for precipitation, specific humidity and temperature forecasting but increases the forecasting error in the wind field. Secondly, how the radar reflectivity mosaic assimilation improves the forecasting skill of RMAPS-ST is displayed based on a heavy rainfall case, which shows:(1) Precipitation forecasting skill is greatly improved and the cycle that is closer to the beginning of rainfall has higher forecasting skill by assimilating radar mosaic.(2) Water vapor, energy and thermal condition which are consumed and weakened by the previous rainfall can be boosted and re-organized to trigger new rainfall by assimilating radar mosaic reflectivity in the cycling way, which plays an important role in the situation of multiple rainfalls occurring during a short time period. Finally, two schemes of the WRF-3 DVAR indirect radar reflectivity assimilation method are tested. Results indicate that the retrieved hydrometeor assimilation scheme and the derived water vapor assimilation scheme both can improve precipitation forecasting, but the latter one plays a more important role and using two schemes together can make reasonable adjustments for the rainwater, snow water, water vapor and thermal condition, which are critical for the improvement of precipitation forecasting.
引文
陈敏,陈明轩,范水勇.2014.雷达径向风观测在华北区域数值预报系统中的实时三维变分同化应用试验.气象学报,72(4):658-677.Chen M,Chen M X,Fan S Y.2014.The real-time radar radial velocity 3DVar assimilation experiments for application to an operational forecast model in North China.Acta Meteor Sinica,72(4):658-677 (in Chinese)
陈明轩,王迎春,肖现等.2012.基于雷达资料四维变分同化和三维云模式对一次超级单体风暴发展维持热动力机制的模拟分析.大气科学,36(5):929-944.Chen M X,Wang Y C,Xiao X,et al.2012.A case simulation analysis on thermodynamical mechanism of supercell storm development using 3-D cloud model and 4-D variational assimilation on radar data.Chinese J Atmos Sci,36(5):929-944 (in Chinese)
陈明轩,肖现,高峰等.2016.基于雷达四维变分分析系统的强对流高分辨率模拟个例分析和批量检验.气象学报,74(3):421-441.Chen M X,Xiao X,Gao F,et al.2016.A case study and batch verification on high resolution numerical simulations of severe convective events using an analysis system based on rapid-refresh 4-D variational radar data assimilation.Acta Meteor Sinica,74(3):421-441 (in Chinese)
范水勇,王洪利,陈敏等.2013.雷达反射率资料的三维变分同化研究.气象学报,71(3):527-537.Fan S Y,Wang H L,Chen M,et al.2013.Study of the data assimilation of radar reflectivity with the WRF 3D-Var.Acta Meteor Sinica,71(3):527-537 (in Chinese)
刘红亚,徐海明,胡志晋等.2007a.雷达反射率因子在中尺度云分辨模式初始化中的应用Ⅰ:云微物理量和垂直速度的反演.气象学报,65(6):896-905.Liu H Y,Xu H M,Hu Z J,et al.2007a.Application of radar reflectivity to initialization of cloud resolving mesoscale model.Part Ⅰ:Retrieval of microphysical parameters and vertical velocity.Acta Meteor Sinica,65(6):896-905 (in Chinese)
刘红亚,徐海明,薛纪善等.2007b.雷达反射率因子在中尺度云分辨模式初始化中的应用Ⅱ:数值模拟试验.气象学报,65(6):906-918.Liu H Y,Xu H M,Xue J S,et al.2007b.Application of radar reflectivity to initialization of cloud resolving mesoscale model.Part Ⅱ:Numerical simulation experiments.Acta Meteor Sinica,65(6):906-918 (in Chinese)
卢冰,孙继松,仲跻芹等.2017.区域数值预报系统在北京地区的降水日变化预报偏差特征及成因分析.气象学报,75(2):248-259.Lu B,Sun J S,Zhong J Q,et al.2017.Analysis of characteristic bias in diurnal precipitation variation forecasts and possible reasons in a regional forecast system over Beijing area.Acta Meteor Sinica,75(2):248-259 (in Chinese)
孙娟珍,陈明轩,范水勇.2016.雷达资料同化方法:回顾与前瞻.气象科技进展,6(3):17-27.Sun J Z,Chen M X,Fan S Y.2016.Radar data assimilation methods:Review and future perspective.Adv Meteor Sci Technol,6(3):17-27 (in Chinese)
肖现,王迎春,陈明轩等.2013.基于雷达资料四维变分同化技术对北京地区一次下山突发性增强风暴热动力机制的模拟分析.气象学报,71(5):797-816.Xiao X,Wang Y C,Chen M X,et al.2013.A mechanism analysis of the thermo-dynamical field of a suddenly intensifying storm from mountains in the Beijing area with the radar data 4DVar.Acta Meteor Sinica,71(5):797-816 (in Chinese)
杨吉,郑媛媛,夏文梅等.2015.雷达拼图资料上中尺度对流系统的跟踪与预报.气象,41(6):738-744.Yang J,Zheng Y Y,Xia W M,et al.2015.Mesoscale convective systems (MCSs) tracking and nowcasting based on radar mosaic data.Meteor Mon,41(6):738-744 (in Chinese)
杨艳蓉,曾明剑.2012.雷达资料同化对暴雨预报影响的数值模拟研究.气象科学,32(2):145-152.Yang Y R,Zeng M J.2012.Numerical simulation analysis on radar data assimilation for summer rainstorm forecast.J Meteor Sci,32(2):145-152 (in Chinese)
杨毅,邱崇践,龚建东等.2008.三维变分和物理初始化方法相结合同化多普勒雷达资料的试验研究.气象学报,66(4):479-488.Yang Y,Qiu C J,Gong J D,et al.2008.Three-dimensional variational combined with physical initialization for assimilation of Doppler radar data.Acta Meteor Sinica,66(4):479-488 (in Chinese)
张诚忠,薛纪善,张林等.2012.基于雷达反射率反演降水率的一维+三维变分同化研究及试验.气象学报,70(5):1128-1136.Zhang C Z,Xue J S,Zhang L,et al.2012.Study of the "1D+3D var" assimilation of the rain rate retrieved from radar reflectivity and its experiments.Acta Meteor Sinica,70(5):1128-1136 (in Chinese)
Barker D M,Huang W,Guo Y R,et al.2004.A three-dimensional variational data assimilation system for MM5:Implementation and initial results.Mon Wea Rev,132(4):897-914
Benjamin S G,Weygandt S S,Brown J M,et al.2016.A North American hourly assimilation and model forecast cycle:The rapid refresh.Mon Wea Rev,144(4):1669-1694
Caya A,Sun J,Snyder C.2005.A comparison between the 4DVAR and the ensemble Kalman filter techniques for radar data assimilation.Mon Wea Rev,133(11):3081-3094
Dowell D C,Wicker L J,Snyder C.2011.Ensemble Kalman filter assimilation of radar observations of the 8 May 2003 Oklahoma City supercell:Influences of reflectivity observations on storm-scale analyses.Mon Wea Rev,139(1):272-294
Gao J D,Smith T M,Stensrud D J,et al.2013.A real-time weather-adaptive 3DVAR analysis system for severe weather detections and warnings.Wea Forecasting,28(3):727-745
Gao J D,Stensrud D J.2012.Assimilation of reflectivity data in a convective-scale,cycled 3DVAR framework with hydrometeor classification.J Atmos Sci,69(3):1054-1065
Gilmore M S,Wicker L J.1998.The influence of midtropospheric dryness on supercell morphology and evolution.Mon Wea Rev,126(4):943-958
Hsiao L F,Chen D S,Kuo Y H,et al.2012.Application of WRF 3DVAR to operational typhoon prediction in Taiwan:Impact of outer loop and partial cycling approaches.Wea Forecasting,27(5):1249-1263
Hu M,Xue M,Brewster K.2006a.3DVAR and cloud analysis with WSR-88D Level-Ⅱ data for the prediction of the Fort Worth,Texas,tornadic thunderstorms.Part Ⅰ:Cloud analysis and its impact.Mon Wea Rev,134(2):675-698
Hu M,Xue M,Gao J D,et al.2006b.3DVAR and cloud analysis with WSR-88D Level-Ⅱ data for the prediction of the Fort Worth,Texas,tornadic thunderstorms.Part Ⅱ:Impact of radial velocity analysis via 3DVAR.Mon Wea Rev,134(2):699-721
Hu M,Benjamin S G,Ladwig T T,et al.2017.GSI three-dimensional ensemble-variational hybrid data assimilation using a global ensemble for the regional rapid refresh model.Mon Wea Rev,145(10):4205-4225
Johnson A,Wang X G,Carley J R,et al.2015.A comparison of multiscale GSI-Based EnKF and 3DVar data assimilation using radar and conventional observations for midlatitude convective-scale precipitation forecasts.Mon Wea Rev,143(8):3087-3108
Jung Y,Zhang G F,Xue M.2008a.Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman filter.Part Ⅰ:Observation operators for reflectivity and polarimetric variables.Mon Wea Rev,136(6):2228-2245
Jung Y,Xue M,Zhang G F,et al.2008b.Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman filter.Part Ⅱ:Impact of polarimetric data on storm analysis.Mon Wea Rev,136(6):2246-2260
Lin Y,Ray P S,Johnson K W.1993.Initialization of a modeled convective storm using Doppler radar-derived fields.Mon Wea Rev,121(10):2757-2775
Lin Y L,Farley R D,Orville H D.1983.Bulk parameterization of the snow field in a cloud model.J Climate Appl Meteor,22(6):1065-1092
Liu S,DiMego G,Guan S C,et al.2016.WSR-88D radar data processing at NCEP.Wea Forecasting,31(6):2047-2055
Parrish D F,Derber J C.1992.The national meteorological center's spectral statistical-interpolation analysis system.Mon Wea Rev,120(8):1747-1763
Smith P L Jr,Myers C G,Orville H D.1975.Radar reflectivity factor calculations in numerical cloud models using bulk parameterization of precipitation.J Appl Meteor,14(6):1156-1165
Sun J Z,Crook N A.1997.Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint.Part Ⅰ:Model development and simulated data experiments.J Atmos Sci,54(12):1642-1661
Sun J Z,Wang H L.2013.Radar data assimilation with WRF 4D-Var.Part Ⅱ:Comparison with 3DVar for a squall line over the U.S.Great Plains.Mon Wea Rev,141(7):2245-2264
Sun J Z,Wang H L,Tong W X,et al.2016.Comparison of the impacts of momentum control variables on high-resolution variational data assimilation and precipitation forecasting.Mon Wea Rev,144(1):149-169
Wang H L,Sun J Z,Fan S Y,et al.2013.Indirect assimilation of radar reflectivity with WRF 3D-Var and its impact on prediction of four summertime convective events.J Appl Meteor Climatol,52(4):889-902
Wang X G,Barker D M,Snyder C,et al.2008a.A hybrid ETKF-3DVAR data assimilation scheme for the WRF model.Part Ⅰ:Observing system simulation experiment.Mon Wea Rev,136(12):5116-5131
Wang X G,Barker D M,Snyder C,et al.2008b.A hybrid ETKF-3DVAR data assimilation scheme for the WRF model.Part Ⅱ:Real observation experiments.Mon Wea Rev,136(12):5132-5147
Weygandt S S,Benjamin S G,Smirnova T G,et al.2008.Assimilation of radar reflectivity data using a diabatic digital filter within the rapid update cycle//Proceedings of the 12th Conference on IOAS-AOLS.New Orleans,LA:American Meteorology Society
Wu W S,Purser R J,Parrish D F.2002.Three-dimensional variational analysis with spatially inhomogeneous covariances.Mon Wea Rev,130(12):2905-2916
Xiao Q N,Kuo Y H,Sun J Z,et al.2005.Assimilation of Doppler radar observations with a regional 3DVAR system:Impact of Doppler velocities on forecasts of a heavy rainfall case.J Appl Meteor,44(6):768-788
Xiao Q N,Kuo Y H,Sun J Z,et al.2007a.An approach of radar reflectivity data assimilation and its assessment with the Inland QPF of typhoon Rusa (2002) at landfall.J Appl Meteor Climatol,46(1):14-22
Xiao Q N,Sun J Z.2007b.Multiple-radar data assimilation and short-range quantitative precipitation forecasting of a squall line observed during IHOP_2002.Mon Wea Rev,135(10):3381-3404
Zhang G F,Sun J Z,Brandes E A.2006.Improving parameterization of rain microphysics with disdrometer and radar observations.J Atmos Sci,63(4):1273-1290
陈明轩,王迎春,肖现等.2012.基于雷达资料四维变分同化和三维云模式对一次超级单体风暴发展维持热动力机制的模拟分析.大气科学,36(5):929-944.Chen M X,Wang Y C,Xiao X,et al.2012.A case simulation analysis on thermodynamical mechanism of supercell storm development using 3-D cloud model and 4-D variational assimilation on radar data.Chinese J Atmos Sci,36(5):929-944 (in Chinese)
陈明轩,肖现,高峰等.2016.基于雷达四维变分分析系统的强对流高分辨率模拟个例分析和批量检验.气象学报,74(3):421-441.Chen M X,Xiao X,Gao F,et al.2016.A case study and batch verification on high resolution numerical simulations of severe convective events using an analysis system based on rapid-refresh 4-D variational radar data assimilation.Acta Meteor Sinica,74(3):421-441 (in Chinese)
范水勇,王洪利,陈敏等.2013.雷达反射率资料的三维变分同化研究.气象学报,71(3):527-537.Fan S Y,Wang H L,Chen M,et al.2013.Study of the data assimilation of radar reflectivity with the WRF 3D-Var.Acta Meteor Sinica,71(3):527-537 (in Chinese)
刘红亚,徐海明,胡志晋等.2007a.雷达反射率因子在中尺度云分辨模式初始化中的应用Ⅰ:云微物理量和垂直速度的反演.气象学报,65(6):896-905.Liu H Y,Xu H M,Hu Z J,et al.2007a.Application of radar reflectivity to initialization of cloud resolving mesoscale model.Part Ⅰ:Retrieval of microphysical parameters and vertical velocity.Acta Meteor Sinica,65(6):896-905 (in Chinese)
刘红亚,徐海明,薛纪善等.2007b.雷达反射率因子在中尺度云分辨模式初始化中的应用Ⅱ:数值模拟试验.气象学报,65(6):906-918.Liu H Y,Xu H M,Xue J S,et al.2007b.Application of radar reflectivity to initialization of cloud resolving mesoscale model.Part Ⅱ:Numerical simulation experiments.Acta Meteor Sinica,65(6):906-918 (in Chinese)
卢冰,孙继松,仲跻芹等.2017.区域数值预报系统在北京地区的降水日变化预报偏差特征及成因分析.气象学报,75(2):248-259.Lu B,Sun J S,Zhong J Q,et al.2017.Analysis of characteristic bias in diurnal precipitation variation forecasts and possible reasons in a regional forecast system over Beijing area.Acta Meteor Sinica,75(2):248-259 (in Chinese)
孙娟珍,陈明轩,范水勇.2016.雷达资料同化方法:回顾与前瞻.气象科技进展,6(3):17-27.Sun J Z,Chen M X,Fan S Y.2016.Radar data assimilation methods:Review and future perspective.Adv Meteor Sci Technol,6(3):17-27 (in Chinese)
肖现,王迎春,陈明轩等.2013.基于雷达资料四维变分同化技术对北京地区一次下山突发性增强风暴热动力机制的模拟分析.气象学报,71(5):797-816.Xiao X,Wang Y C,Chen M X,et al.2013.A mechanism analysis of the thermo-dynamical field of a suddenly intensifying storm from mountains in the Beijing area with the radar data 4DVar.Acta Meteor Sinica,71(5):797-816 (in Chinese)
杨吉,郑媛媛,夏文梅等.2015.雷达拼图资料上中尺度对流系统的跟踪与预报.气象,41(6):738-744.Yang J,Zheng Y Y,Xia W M,et al.2015.Mesoscale convective systems (MCSs) tracking and nowcasting based on radar mosaic data.Meteor Mon,41(6):738-744 (in Chinese)
杨艳蓉,曾明剑.2012.雷达资料同化对暴雨预报影响的数值模拟研究.气象科学,32(2):145-152.Yang Y R,Zeng M J.2012.Numerical simulation analysis on radar data assimilation for summer rainstorm forecast.J Meteor Sci,32(2):145-152 (in Chinese)
杨毅,邱崇践,龚建东等.2008.三维变分和物理初始化方法相结合同化多普勒雷达资料的试验研究.气象学报,66(4):479-488.Yang Y,Qiu C J,Gong J D,et al.2008.Three-dimensional variational combined with physical initialization for assimilation of Doppler radar data.Acta Meteor Sinica,66(4):479-488 (in Chinese)
张诚忠,薛纪善,张林等.2012.基于雷达反射率反演降水率的一维+三维变分同化研究及试验.气象学报,70(5):1128-1136.Zhang C Z,Xue J S,Zhang L,et al.2012.Study of the "1D+3D var" assimilation of the rain rate retrieved from radar reflectivity and its experiments.Acta Meteor Sinica,70(5):1128-1136 (in Chinese)
Barker D M,Huang W,Guo Y R,et al.2004.A three-dimensional variational data assimilation system for MM5:Implementation and initial results.Mon Wea Rev,132(4):897-914
Benjamin S G,Weygandt S S,Brown J M,et al.2016.A North American hourly assimilation and model forecast cycle:The rapid refresh.Mon Wea Rev,144(4):1669-1694
Caya A,Sun J,Snyder C.2005.A comparison between the 4DVAR and the ensemble Kalman filter techniques for radar data assimilation.Mon Wea Rev,133(11):3081-3094
Dowell D C,Wicker L J,Snyder C.2011.Ensemble Kalman filter assimilation of radar observations of the 8 May 2003 Oklahoma City supercell:Influences of reflectivity observations on storm-scale analyses.Mon Wea Rev,139(1):272-294
Gao J D,Smith T M,Stensrud D J,et al.2013.A real-time weather-adaptive 3DVAR analysis system for severe weather detections and warnings.Wea Forecasting,28(3):727-745
Gao J D,Stensrud D J.2012.Assimilation of reflectivity data in a convective-scale,cycled 3DVAR framework with hydrometeor classification.J Atmos Sci,69(3):1054-1065
Gilmore M S,Wicker L J.1998.The influence of midtropospheric dryness on supercell morphology and evolution.Mon Wea Rev,126(4):943-958
Hsiao L F,Chen D S,Kuo Y H,et al.2012.Application of WRF 3DVAR to operational typhoon prediction in Taiwan:Impact of outer loop and partial cycling approaches.Wea Forecasting,27(5):1249-1263
Hu M,Xue M,Brewster K.2006a.3DVAR and cloud analysis with WSR-88D Level-Ⅱ data for the prediction of the Fort Worth,Texas,tornadic thunderstorms.Part Ⅰ:Cloud analysis and its impact.Mon Wea Rev,134(2):675-698
Hu M,Xue M,Gao J D,et al.2006b.3DVAR and cloud analysis with WSR-88D Level-Ⅱ data for the prediction of the Fort Worth,Texas,tornadic thunderstorms.Part Ⅱ:Impact of radial velocity analysis via 3DVAR.Mon Wea Rev,134(2):699-721
Hu M,Benjamin S G,Ladwig T T,et al.2017.GSI three-dimensional ensemble-variational hybrid data assimilation using a global ensemble for the regional rapid refresh model.Mon Wea Rev,145(10):4205-4225
Johnson A,Wang X G,Carley J R,et al.2015.A comparison of multiscale GSI-Based EnKF and 3DVar data assimilation using radar and conventional observations for midlatitude convective-scale precipitation forecasts.Mon Wea Rev,143(8):3087-3108
Jung Y,Zhang G F,Xue M.2008a.Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman filter.Part Ⅰ:Observation operators for reflectivity and polarimetric variables.Mon Wea Rev,136(6):2228-2245
Jung Y,Xue M,Zhang G F,et al.2008b.Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman filter.Part Ⅱ:Impact of polarimetric data on storm analysis.Mon Wea Rev,136(6):2246-2260
Lin Y,Ray P S,Johnson K W.1993.Initialization of a modeled convective storm using Doppler radar-derived fields.Mon Wea Rev,121(10):2757-2775
Lin Y L,Farley R D,Orville H D.1983.Bulk parameterization of the snow field in a cloud model.J Climate Appl Meteor,22(6):1065-1092
Liu S,DiMego G,Guan S C,et al.2016.WSR-88D radar data processing at NCEP.Wea Forecasting,31(6):2047-2055
Parrish D F,Derber J C.1992.The national meteorological center's spectral statistical-interpolation analysis system.Mon Wea Rev,120(8):1747-1763
Smith P L Jr,Myers C G,Orville H D.1975.Radar reflectivity factor calculations in numerical cloud models using bulk parameterization of precipitation.J Appl Meteor,14(6):1156-1165
Sun J Z,Crook N A.1997.Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint.Part Ⅰ:Model development and simulated data experiments.J Atmos Sci,54(12):1642-1661
Sun J Z,Wang H L.2013.Radar data assimilation with WRF 4D-Var.Part Ⅱ:Comparison with 3DVar for a squall line over the U.S.Great Plains.Mon Wea Rev,141(7):2245-2264
Sun J Z,Wang H L,Tong W X,et al.2016.Comparison of the impacts of momentum control variables on high-resolution variational data assimilation and precipitation forecasting.Mon Wea Rev,144(1):149-169
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