不同物理参数化方案对黄河源区降雨模拟的适用性研究
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摘要
为分析不同物理参数化方案在模拟黄河源区降水时的适用性,采用中尺度WRF模式中常用的5种微物理方案和3种积云对流方案进行组合,模拟黄河源区的一次降水过程,利用直方图曼哈顿距离相似度对模拟结果和实况降水空间分布进行对比,并分析各方案组合模拟的降水中心(河南站)逐小时降水分布和24h累积降水量,以得到WRF模式模拟黄河源区降水的最优方案配置,提高模拟精度。结果表明,WRF模式的各方案基本可以再现降水强度、中心和范围,基于Morrison方案的组合对降水的还原能力较好;就降水中心的降水时间序列和24h累积降水量来看,基于Morrison方案的组合与实际降水的一致性较好;Morrison微物理方案和Grell 3积云对流方案组合的模拟结果与实际降水的空间分布相似度最高,表明该方案组合是WRF模式模拟黄河源区降水过程的最优模拟方案。研究成果对于提高黄河源区降水模拟的精度有重要意义。
Five kinds of microphysical schemes and three cumulus convection schemes commonly used in the mesoscale WRF model are combined to simulate a precipitation process in the source region of the Yellow River.The simulation results and the spatial distribution of the actual precipitation is compared by the distance similarity of the histogram.The hourly precipitation distribution and the 24 hcumulative precipitation of the precipitation center(Henan Station)simulated by each combination are also analyzed.The optimal scheme combination of the WRF model to simulate the precipitation in the source area of the Yellow River is obtained,and the simulation accuracy is improved.The results show that the WRF model can basically simulate the intensity,center and range of the precipitation.The combination of the Morrison scheme is better for the precipitation reduction;the precipitation time series of the precipitation center and the24 hcumulative precipitation based on Morrison scheme combination has good consistency with actual precipitation;the simulation results of Morrison microphysical scheme and Grell 3 cumulus convection scheme combination have the highest similarity with the spatial distribution of actual precipitation,indicating that this is optimal scheme combination to simulate precipitation in the source region of the Yellow River.The research result has important significance to improve the simulation accuracy of precipitation in the source region of the Yellow River.
Five kinds of microphysical schemes and three cumulus convection schemes commonly used in the mesoscale WRF model are combined to simulate a precipitation process in the source region of the Yellow River.The simulation results and the spatial distribution of the actual precipitation is compared by the distance similarity of the histogram.The hourly precipitation distribution and the 24 hcumulative precipitation of the precipitation center(Henan Station)simulated by each combination are also analyzed.The optimal scheme combination of the WRF model to simulate the precipitation in the source area of the Yellow River is obtained,and the simulation accuracy is improved.The results show that the WRF model can basically simulate the intensity,center and range of the precipitation.The combination of the Morrison scheme is better for the precipitation reduction;the precipitation time series of the precipitation center and the24 hcumulative precipitation based on Morrison scheme combination has good consistency with actual precipitation;the simulation results of Morrison microphysical scheme and Grell 3 cumulus convection scheme combination have the highest similarity with the spatial distribution of actual precipitation,indicating that this is optimal scheme combination to simulate precipitation in the source region of the Yellow River.The research result has important significance to improve the simulation accuracy of precipitation in the source region of the Yellow River.
引文
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[4]李得勤,文小航,段云霞,等.MODIS产品反演与WRF模式默认植被覆盖度对比研究[J].气象与环境学报,2015,31(4):26-34.
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[9] Morrison H,Thompson G,TatarskⅡV.Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line:Comparison of One-and Two-moment Schemes[J].Monthly Weather Review,2009,137(3):991-1 007.
[10]Kain J S.The Kain-Fritsch Convective Parameterization:An Update[J].Journal of Applied Meteorology,2004,43(1):170-181.
[11]Janjic'ZI.TheStep-mountain Eta Coordinate Model:Further Developments of the Convection,Viscous Sublayer,and Turbulence Closure Schemes[J].Monthly Weather Review,1994,122(5):927-945.
[12]Grell G A,Dévényi D.A Generalized Approach to Parameterizing Convection Combining Ensemble and Data Assimilation Techniques[J].Geophysical Research Letters,2002,29(14):38-1-38-4.
[13]尤桑杰.2007~2011年青藏高原强降水的统计特征及典型个例成因分析[D].南京:南京信息工程大学,2014.
[14]Wang Y Q.An Explicit Simulation of Tropical Cyclones with a Triply Nested Movable Mesh Primitive Equation Model:TCM3.Part I:Model Description and Control Experiment[J].Monthly Weather Review,2001,129(6):1 370-1 394.
[2]何由,阳坤,姚檀栋,等.基于WRF模式对青藏高原一次强降水的模拟[J].高原气象,2012,31(5):1 183-1 191.
[3] Efstathiou G A,Zoumakis N M,Melas D,et al.Sensitivity of WRF to Boundary Layer Parameterizations in Simulating a Heavy Rainfall Event Using Different Microphysical Schemes.Effect on largescale processes[J].Atmospheric Research,2013,132-133(10):125-143.
[4]李得勤,文小航,段云霞,等.MODIS产品反演与WRF模式默认植被覆盖度对比研究[J].气象与环境学报,2015,31(4):26-34.
[5] Kessler E.On the Distribution and Continuity of Water Substance in Atmospheric Circulations[M]//On the Distribution and Continuity of Water Substance in Atmospheric Circulations.American Meteorological Society,1969:1-84.
[6] Lin Y L,Farley R D,Orville H D.Bulk Parameterization of the Snow Field in a Cloud Model[J].Journal of Climate and Applied Meteorology,1983,22(6):1 065-1 092.
[7] Hong S Y,Lim J O J.The WRF Single-moment 6-class Microphysics Scheme(WSM6)[J].J.Korean Meteor.Soc,2006,42(2):129-151.
[8] Thompson G,Field P R,Rasmussen R M,et al.Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme.PartⅡ:Implementation of a New Snow Parameterization[J].Monthly Weather Review,2008,136(12):5 095-5 115.
[9] Morrison H,Thompson G,TatarskⅡV.Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line:Comparison of One-and Two-moment Schemes[J].Monthly Weather Review,2009,137(3):991-1 007.
[10]Kain J S.The Kain-Fritsch Convective Parameterization:An Update[J].Journal of Applied Meteorology,2004,43(1):170-181.
[11]Janjic'ZI.TheStep-mountain Eta Coordinate Model:Further Developments of the Convection,Viscous Sublayer,and Turbulence Closure Schemes[J].Monthly Weather Review,1994,122(5):927-945.
[12]Grell G A,Dévényi D.A Generalized Approach to Parameterizing Convection Combining Ensemble and Data Assimilation Techniques[J].Geophysical Research Letters,2002,29(14):38-1-38-4.
[13]尤桑杰.2007~2011年青藏高原强降水的统计特征及典型个例成因分析[D].南京:南京信息工程大学,2014.
[14]Wang Y Q.An Explicit Simulation of Tropical Cyclones with a Triply Nested Movable Mesh Primitive Equation Model:TCM3.Part I:Model Description and Control Experiment[J].Monthly Weather Review,2001,129(6):1 370-1 394.