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作 者:万晓敏 韩威 田伟红 何晓欢 WAN Xiaomin;HAN Wei;TIAN Weihong;HE Xiaohuan(National Meteorological Centre,Beijing 100081,China)
机构地区:[1]国家气象中心,北京100081
出 处:《高原气象》2018年第4期1083-1093,共11页Plateau Meteorology
基 金:中国气象局数值天气预报(GRAPES)专项(GRAPES-FZZX-2017-05);公益性行业(气象)科研专项(GYHY201506002)
摘 要:采用2016年7月国家卫星气象中心提供的加密FY-2G资料,选用美国国家环境预报中心的FNL全球分析资料(Final Operational Global Analysis)为参考场,根据不同质量标识码QI(Quality Indicator)对其进行质量评估,并基于GRAPES(Global and Regional Assimilation and Prediction System)模式的GRAPES_RAFS(Rapid Analysis and Forecast System)系统分别进行了个例试验和连续试验。结果表明,QI≥80的加密FY-2G资料质量最好,相较于其他QI阈值,其偏差和均方根误差最小;对比业务使用的FY-2G红外通道云导风资料,加密FY-2G红外通道云导风的U分量偏差更接近正态分布。对2016年7月2 3日强降水个例进行了三组对比试验,结果表明:同化加密FY-2G红外通道云导风资料对850 h Pa高度场和风场分析有一定的调整作用,对24 h降水强度和落区预报有一定改善。连续试验结果表明同化加密FY-2G红外通道云导风资料对高层风场改善明显,24 h降水预报检验反映出全国区域中雨到暴雨级别的降水ETS评分提高。Atmospheric Motion Vectors( AMVs) can supply plenty of useful information for numerical weather prediction. Statistical results demonstrate that the quality of intensive FY-2 GAtmospheric Motion Vectors( AM-Vs) is best when the quality indicator( QI) is greater than 80. Therefor,it is necessary to evaluate intensive FY-2 GAMVs for the analysis field and precipitation forecast in GRAPES( Global/Regional Assimilation Prediction System) at CMA. In this study,by using GRAPESRAFS( Rapid Analysis and Forecast System),three contrast tests had been researched based on one rainstorm occurred from 2 to 3 July 2016. The results show that assimilation of intensive FY-2 GAMVs have weak positive impacts on the 850 h Pa wind and height analysis field. The 24 hours precipitation forecast results show positive contribution to rainfall intensity and location prediction when using intensive FY-2 GAMVs. One-month experiments were conducted to examine the impact of assimilating intensive FY-2 GAMVs,the results indicate that assimilating intensive FY-2 GAMVs improves the wind analysis field,especially in high levels,and the precipitation forecasting scores for moderate rain to heavy rain are improved with using intensive FY-2 GAMVs.
关 键 词:加密FY-2G云导风资料 GRAPES数值模式 资料同化 影响试验
分 类 号:P456.7[天文地球—大气科学及气象学]
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