Tropical cyclone(TC)track predictions of the 10-km resolution WRF(provisionally named"AAMC-WRF")of the Hong Kong Observatory(HKO),spanning(20°S-60°N,45°E-160°E)is studied for a 1-year per...Tropical cyclone(TC)track predictions of the 10-km resolution WRF(provisionally named"AAMC-WRF")of the Hong Kong Observatory(HKO),spanning(20°S-60°N,45°E-160°E)is studied for a 1-year period from April 2018 to Mar 2019.Real-time predictions,up to 4 times a day and T+48 h ahead,are verified against operational analysis positions of HKO for storms over the South China Sea(SCS)and Western North Pacific(WNP);and of the New Delhi Regional Specialised Meteorological Centre(RSMC)for storms over the North Indian Ocean basin(NIO;including the Bay of Bengal).Out of 21 named TCs over SCS and WNP,mean positional errors of the AAMC-WRF are 33 km(T+0),63 km(T+24),and 107 km(T+48)based on 209,178 and 142 forecasts.The AAMC-WRF outperformed Meso-NHM,also run in real-time at HKO,with mean error reduction up to 34 km or 24%.Mean positional errors for 13 NIO storms are 38 km(T+0),69 km(T+24)and 107 km(T+48)based on 183,131 and 85 forecasts.This is the first study in which TC predictions of a regional model are simultaneously examined over the SCS,WNP and NIO basins through real-time experiments.展开更多
A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advec- tion fog event over Shanghai Pudong International Airport （ZSPD） with the Weather Research and Fore...A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advec- tion fog event over Shanghai Pudong International Airport （ZSPD） with the Weather Research and Forecasting （WRF） model. Using the current operational settings at the Meteorological Center of East China Air Traffic Manage- ment Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are per- formed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation （both longwave and shortwave） processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, sug- gesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physi- cal processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.展开更多
基于历史资料的模式距平积分预报订正(Anomaly Numerical-correction with Observations,ANO)方法,结合欧洲中期天气预报中心的ERA-interim再分析资料和0.1°×0.1°分辨率的中国地面自动站与CMORPH卫星反演降水资料融合逐...基于历史资料的模式距平积分预报订正(Anomaly Numerical-correction with Observations,ANO)方法,结合欧洲中期天气预报中心的ERA-interim再分析资料和0.1°×0.1°分辨率的中国地面自动站与CMORPH卫星反演降水资料融合逐时降水产品,对高分辨率非静力天气研究和预报(WRF)模式的数值预报结果进行订正试验,检验了ANO方法对灾害性天气、尤其是对持续性强降水预报的订正改进效果。对1983—2013年7月中旬四川地区订正前后数值预报结果与观测和再分析数据的比较表明,ANO方法不仅在环流场的预报订正试验中有较为显著的效果,对模式降水预报结果也有改进,能够有效提高模式对强降水的预报精度和评分,减小预报偏差。对2013年7月8—13日高分辨率预报结果的ANO订正试验发现,订正环流场各变量均有所改进,其中,位势高度距平相关系数平均提高了7.8%,均方根误差平均降低了55.7%,降水(特别是暴雨以上量级)的ETS评分和TS评分也有不同程度的提高,并得到多年独立样本的高分辨率数值预报订正结果的支持。展开更多
鉴于云南观测信息相对不足、局地强降水突出的现状,利用WRF(Weather Research and Forecasting)模式及其变分同化系统进行雷达反射率因子和反演风场的三维变分同化试验。通过对2012年9月12日00:00—13日00:00发生在云南的一次强降水过...鉴于云南观测信息相对不足、局地强降水突出的现状,利用WRF(Weather Research and Forecasting)模式及其变分同化系统进行雷达反射率因子和反演风场的三维变分同化试验。通过对2012年9月12日00:00—13日00:00发生在云南的一次强降水过程进行数值模拟和对比分析,结果表明,同时同化雷达反演风场和基本反射率因子,对区域模式同化系统中风矢量、相对湿度、位势高度几个基本分析量都有明显影响。雷达资料的同化,有利于区域模式初始场中强降水区域的上游中低层空气湿度增加、水汽输送增强和强降水发生区域的风场辐合加强,从而改善区域模式对强降水落区、强度的预报质量。对于切变线等天气尺度系统影响下的强降水过程,雷达资料的同化持续时间选取3 h、同化间隔为1 h较适宜。另外,雷达反演风场和基本反射率因子的同化均对降水预报改善有明显贡献,且多种资料的同化效果好于单一资料同化。展开更多
为了研究海表面温度(sea surface temperature,SST)对低空大气波导数值模拟的影响,针对南海海域基于天气研究与预报(weather research and forecasting,WRF)模式开展了不同SST对低空大气波导数值模拟的影响研究.结果表明:精确的SST对低...为了研究海表面温度(sea surface temperature,SST)对低空大气波导数值模拟的影响,针对南海海域基于天气研究与预报(weather research and forecasting,WRF)模式开展了不同SST对低空大气波导数值模拟的影响研究.结果表明:精确的SST对低空大气波导数值模拟影响最大,其次是更新周期;美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)提供的最优插值SST给出的大气波导模拟结果最好,正确率为68.2%,且波导底高平均误差和标准差最小,这是由于其模拟的相对湿度和气温变化较为准确,其次为气候预报再分析系统(climate forecast system reanalysis,CFSR)给出的SST方案较好;此外不同嵌套网格方式对大气波导数值模拟也有影响,在最优方案中子网格模拟的大气波导正确率和发生概率分别提高了11.8%和10.4%,虚报率降低了2.4%.该研究可为南海低空大气波导的精确预报提供技术支撑.展开更多
基于Babin模型并分析了海上蒸发波导对气象输入参数的敏感性,引入数值天气预报中集合预报的思路,提出了一种新的蒸发波导诊断方法——集合诊断方法(Babin_Ens法).运用它对中国近海4个岛屿站点的实测数据进行了波导诊断结果的对比验证,发...基于Babin模型并分析了海上蒸发波导对气象输入参数的敏感性,引入数值天气预报中集合预报的思路,提出了一种新的蒸发波导诊断方法——集合诊断方法(Babin_Ens法).运用它对中国近海4个岛屿站点的实测数据进行了波导诊断结果的对比验证,发现:与Babin模型(Babin法)相比,Babin_Ens法使波导高度与强度偏差的平均改进率分别达到了23.49%与19.29%.进一步尝试运用Babin_Ens法对WRF (Weather Research and Forecasting)模式的预报信息进行了蒸发波导的数值预报,波导高度与强度预报偏差的平均改进率分别提高了14.01%和16.92%.研究表明,集合诊断可以显著地提高波导信息的诊断准确度,是一种改进蒸发波导诊断准确度的可行途径.展开更多
文摘Tropical cyclone(TC)track predictions of the 10-km resolution WRF(provisionally named"AAMC-WRF")of the Hong Kong Observatory(HKO),spanning(20°S-60°N,45°E-160°E)is studied for a 1-year period from April 2018 to Mar 2019.Real-time predictions,up to 4 times a day and T+48 h ahead,are verified against operational analysis positions of HKO for storms over the South China Sea(SCS)and Western North Pacific(WNP);and of the New Delhi Regional Specialised Meteorological Centre(RSMC)for storms over the North Indian Ocean basin(NIO;including the Bay of Bengal).Out of 21 named TCs over SCS and WNP,mean positional errors of the AAMC-WRF are 33 km(T+0),63 km(T+24),and 107 km(T+48)based on 209,178 and 142 forecasts.The AAMC-WRF outperformed Meso-NHM,also run in real-time at HKO,with mean error reduction up to 34 km or 24%.Mean positional errors for 13 NIO storms are 38 km(T+0),69 km(T+24)and 107 km(T+48)based on 183,131 and 85 forecasts.This is the first study in which TC predictions of a regional model are simultaneously examined over the SCS,WNP and NIO basins through real-time experiments.
基金Supported by the National Natural Science Foundation of China(4130511 and U1233138)Safety Capability Enhancement Program of Civil Aviation Administration of China(TMSA1605)
文摘A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advec- tion fog event over Shanghai Pudong International Airport （ZSPD） with the Weather Research and Forecasting （WRF） model. Using the current operational settings at the Meteorological Center of East China Air Traffic Manage- ment Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are per- formed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation （both longwave and shortwave） processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, sug- gesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physi- cal processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.
文摘基于历史资料的模式距平积分预报订正(Anomaly Numerical-correction with Observations,ANO)方法,结合欧洲中期天气预报中心的ERA-interim再分析资料和0.1°×0.1°分辨率的中国地面自动站与CMORPH卫星反演降水资料融合逐时降水产品,对高分辨率非静力天气研究和预报(WRF)模式的数值预报结果进行订正试验,检验了ANO方法对灾害性天气、尤其是对持续性强降水预报的订正改进效果。对1983—2013年7月中旬四川地区订正前后数值预报结果与观测和再分析数据的比较表明,ANO方法不仅在环流场的预报订正试验中有较为显著的效果,对模式降水预报结果也有改进,能够有效提高模式对强降水的预报精度和评分,减小预报偏差。对2013年7月8—13日高分辨率预报结果的ANO订正试验发现,订正环流场各变量均有所改进,其中,位势高度距平相关系数平均提高了7.8%,均方根误差平均降低了55.7%,降水(特别是暴雨以上量级)的ETS评分和TS评分也有不同程度的提高,并得到多年独立样本的高分辨率数值预报订正结果的支持。
文摘鉴于云南观测信息相对不足、局地强降水突出的现状,利用WRF(Weather Research and Forecasting)模式及其变分同化系统进行雷达反射率因子和反演风场的三维变分同化试验。通过对2012年9月12日00:00—13日00:00发生在云南的一次强降水过程进行数值模拟和对比分析,结果表明,同时同化雷达反演风场和基本反射率因子,对区域模式同化系统中风矢量、相对湿度、位势高度几个基本分析量都有明显影响。雷达资料的同化,有利于区域模式初始场中强降水区域的上游中低层空气湿度增加、水汽输送增强和强降水发生区域的风场辐合加强,从而改善区域模式对强降水落区、强度的预报质量。对于切变线等天气尺度系统影响下的强降水过程,雷达资料的同化持续时间选取3 h、同化间隔为1 h较适宜。另外,雷达反演风场和基本反射率因子的同化均对降水预报改善有明显贡献,且多种资料的同化效果好于单一资料同化。
基金the National Key Project of China(No.GJXM92579)the Aero⁃nautic Science Foundation of China(No.2018ZA53014)the Shenyang Key Laboratory of Aircraft Icing and Ice Protection.
文摘为了研究海表面温度(sea surface temperature,SST)对低空大气波导数值模拟的影响,针对南海海域基于天气研究与预报(weather research and forecasting,WRF)模式开展了不同SST对低空大气波导数值模拟的影响研究.结果表明:精确的SST对低空大气波导数值模拟影响最大,其次是更新周期;美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)提供的最优插值SST给出的大气波导模拟结果最好,正确率为68.2%,且波导底高平均误差和标准差最小,这是由于其模拟的相对湿度和气温变化较为准确,其次为气候预报再分析系统(climate forecast system reanalysis,CFSR)给出的SST方案较好;此外不同嵌套网格方式对大气波导数值模拟也有影响,在最优方案中子网格模拟的大气波导正确率和发生概率分别提高了11.8%和10.4%,虚报率降低了2.4%.该研究可为南海低空大气波导的精确预报提供技术支撑.
文摘基于Babin模型并分析了海上蒸发波导对气象输入参数的敏感性,引入数值天气预报中集合预报的思路,提出了一种新的蒸发波导诊断方法——集合诊断方法(Babin_Ens法).运用它对中国近海4个岛屿站点的实测数据进行了波导诊断结果的对比验证,发现:与Babin模型(Babin法)相比,Babin_Ens法使波导高度与强度偏差的平均改进率分别达到了23.49%与19.29%.进一步尝试运用Babin_Ens法对WRF (Weather Research and Forecasting)模式的预报信息进行了蒸发波导的数值预报,波导高度与强度预报偏差的平均改进率分别提高了14.01%和16.92%.研究表明,集合诊断可以显著地提高波导信息的诊断准确度,是一种改进蒸发波导诊断准确度的可行途径.
