摘要
针对2000年7月4～5日北京地区的一次特大暴雨过程(24 h降水量达240 mm),文中利用MM5/WRF三维变分系统和MM5非静力模式,对此次特大暴雨过程中的各种气象监测资料(地基GPS大气柱水汽含量、常规探空、高空测风、地面常规观测和地面自动气象站)的同化作用通过观测系统数值试验进行了评估.结果表明:与传统的客观分析方案相比较,MM5/WRF三维变分同化系统可直接引入非常规地基GPS大气柱水汽含量监测资料,提供更好的大气初始分析场.在三维变分同化方案下,各种大气监测资料均对改进此次特大暴雨模拟有不同程度的贡献,其中,常规探空和高空测风监测资料对改进预报结果的影响最大,地面常规观测和地面自动气象站观测资料作用次之,地基GPS大气柱水汽含量资料在与其他大气监测资料相互优势互补后,可很好地改善模式大气的分析质量,通过三维变分同化技术在区域数值天气预报模式初始场中引入地基GPS大气水汽监测网资料,使此次强降水个例的6 h和24 h测站降水预报的TS评分值在1,5,10和20 mm预报检验阈值下分别提高了1%～8%.研究结果对利用三维变分数值系统,评估气象监测网资料在改进高影响天气事件预报中的作用有借鉴意义.
In an effort to assess the impact of the individual components of meteorological observations （ground-based GPS precipitable water vapor, automatic and conventional meteorological observations） on the torrential rain event of 4 - 5 July 2000 in Beijing （with 24 h accumulated precipitation reaching 240 mm）, 24 hour observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the non-hydrostatic MM5 model. Results indicate that, because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system, better initial fields and 24h-simulation for the severe precipitation event are achieved than those under the MM5/Litter objective analysis scheme. Further analysis also shows that each of the individual components of meteorological observation network plays its special positive role on the improvement of initial-field analysis and forecasting skills. With or without radiosonde and pilot observation in 3DVAR scheme has the most significant influence on numerical simulation, automatic and conventional surface meteorological observations ranks into the second place. After ingested the supplement information from the other meteorological observations, the ground-based GPS precipitable water vapor data can play more obvious roles on initial-field assimilation and precipitation forecast. By incorporating the ground-based GPS precipitable water vapor data into the 3DVAR analyses at the initial time, the threat scores （TS） with thresholds of 1, 5, 10 and 20 mm are increased around 1% - 8 % for 6 and 24 hours accumulated precipitation observations. This work gives one helpful example that assesses the impact of individual components of the existing Meteorological Observation Network on high-influence weather event using 3DVAR numerical system.
出处
《气象学报》
CAS
CSCD
北大核心
2005年第6期922-932,共11页
Acta Meteorologica Sinica
基金
北京市科委项目(H010510120119
H020620250330
H013610330119)
国家科技部项目(2002BA904B05)
国家科技部与北京市科委"全球定位系统单双频地基水汽遥测技术研究"国际合作项目
关键词
三维变分资料同化
全球定位系统
暴雨
观测系统试验
数值预报
Three-dimensional variational data assimilation, Global position system, Severe rainfall, Observation system experiment, Numerical weather prediction
