摘要
基于WRF模式三维同化(3DVar)建立每3 h快速更新循环同化系统(简称RUC),循环同化地面常规观测资料、探空资料、船舶资料和飞机报,并以此为基础建立预报系统,对2011年6月4日20时—5日20时江西一次大暴雨过程进行模拟检验,初步研究RUC在江西暴雨预报中的应用。结果表明:(1)RUC有效改进了初始场风场结构,尤其对低层风场的改进明显。(2)RUC改善了初始场大气层结结构,增加中低层大气层结不稳定能量积累,有利于暴雨发生。(3)预报系统更好地模拟了此次大暴雨落区、走向、中心降水强度和降水时段。(4)对比大暴雨中心逐6 h累计雨量,预报系统模拟的4个时段累计降水与同时段实况累计降水相吻合,预报出逐6 h累计降水的量级和变化趋势。
Based on the WRF 3DVar module, per 3-hour Rapid Update Cycle （RUC） assimilation and forecast system is established. The assimilation data include ground conventional observation data, sounding data, ship observation data and airplane report data, which are obtained by the global telecommunication exchange system. In order to analyze the precipitation forecasting performance,in this paper, a heavy rainfall process between 4th 20：00-5th 20：00 June 2011 in the northern Jiangxi is simulated by using the RUC analysis and forecast system. The results indicate that： （1） RUC effectively improves the low boundary wind structure of the first guess, which tends to be more reasonable and is more likely to induce the precipitation at the rainstorm area. （2） RUC improves the atmospheric unstable stratification structure, increases the atmospheric stratification unstable energy at the middle and high level of the air. （3） RUC makes a precise forecast of the area and intensity of heavy rainfall, especially the intensity between Dongxiang--YuJiang （the center of the cloud burst）, presents slight deviation at the western area of Yichun and Shangrao. （g） Through the intercomparison of the 6-hour accumulation rainfall at the cloud burst center （Dongxiang）, RUC predicts more accurate precipitation at the time-interval, which reflects the intensity and the changing tendency of the 6-hour accumulation precipitation. This indicates that RUC has a certain ability to make the weather forecasting.
出处
《气象与减灾研究》
2011年第3期24-29,共6页
Meteorology and Disaster Reduction Research
基金
中国气象局武汉暴雨研究所开放基金项目(编号I:HR2009K03)
江西省科技厅科技支撑计划项目(编号:20111BBG70031-4)
江西省气象局重点科研项目(编号:JXQX2009Z03JXQX2010Z03)
关键词
数值预报
RUC
WRF
暴雨过程
Numerical forecast, Rapid Update Cycle, Mesoscale, Heavy rainfall.
