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作 者:李典[1] 柴晓玲[1] 李崇[1] 鲁杨[1] 吴宇童 崔景琳
机构地区:[1]沈阳市气象局,辽宁沈阳110168
出 处:《气象与环境学报》2018年第1期11-21,共11页Journal of Meteorology and Environment
基 金:中国气象局预报员专项(CMAYBY2015-016);辽宁省暴雨专家型预报员团队共同资助
摘 要:利用实况气象观测资料、欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)细网格预报产品、东北中尺度数值模式(Weather Research and Forecasting,WRF)资料和雷达探测产品,从降水系统演变、短期及短时预报和数值模式产品应用等方面对2016年6月30日沈阳地区局地暴雨过程进行了分析。结果表明:此次沈阳地区强降水过程短期可预报性特征明显,但不满足过去总结的辽宁省暴雨预报阈值指标。ECMWF模式集合预报产品的降水量90%分位值和EFI对此次强降水过程的极端性预报具有指示意义。辽宁省南部地区较大的垂直风切变使对流云团移动路径发生转折。多种数值模式均预报出沈阳地区降水的分布特征,但降水落区预报存在偏差。不同起报时次ECMWF模式预报的不确定性较大,最新起报时次的参考意义最好。中尺度WRF模式可用于重点分析对流云团的演变特征。The conventional observation data, the European Centre for Medium-Range Weather Forecasting( ECMWF)numerical weather prediction products, the Weather Research and Forecasting Model( WRF) data,and radar detection products were used to study a local heavy rain process happening on June 30,2016, in Shenyang. The evolution of the precipitation system, short-term and very short-term predictability,and model production application were analyzed. The results show that this heavy rain has clear characteristics for short-term prediction,but it does not meet the threshold values obtained from the past rainfall forecasts in Liaoning province. The 90% percentile of accumulated precipitation and EFI( Extreme Forecast Index) forecasted by the ECMWF ensemble model indicate the extreme feature of this heavy rain process. The large vertical wind shear happening in the southern Liaoning results in sudden changing and recurring convective cloud clusters. All models analyzed in this study can predict the distribution characteristics of rainfall,but the location of precipitation needs improving. The ECMWF forecasts from different start times have relatively large uncertainties. The forecast result from the last starting time has a good reference value. The WRF model can be used to analyze the evolution characteristics of convective cloud clusters and therefore we should focus on the investigation of evolution processes of convective clouds using the WRF model.
分 类 号:P458.3[天文地球—大气科学及气象学]
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