低频天气图方法在湖南省雨季强降水过程预报中的应用  

Application of Low Frequency Synoptic Chart to Predicting Severe Precipitation Process in Hunan Province

作　　者：陈青[1,2] 廖玉芳[2] 杨书运[1] 赵辉[2] 

机构地区：[1]安徽农业大学,合肥230036 [2]湖南省气候中心,长沙410007

出　　处：《气象》2014年第2期223-228,共6页Meteorological Monthly

基　　金：湖南省科技重点项目(2012NK2020);中国气象局气候变化专项(CCSF201212)共同资助

摘　　要：利用2006—2010年4—6月NCEP/NCAR 500 hPa高度场和700 hPa风场逐日格点资料及湖南省97个地面气象观测站逐日降水观测资料,运用低频天气图方法,确定影响湖南强降水过程天气关键区,分析影响湖南强降水过程的低频天气系统活动周期、变化路径及低频天气系统与强降水过程的配置的基础上,建立了湖南省4—6月延伸期强降水过程预报模型,回报拟合率以4月最高,平均为64.4%;5月次之,平均为54.9%;6月最低,平均为50.7%;10、15、20、25和30 d等不同预报时效的准确率以提前30 d的回报准确率最高。应用于2011年4—6月强降水过程预报,准确率为70%,其中报对7次强降水过程,空报3次,无漏报。A predicting model, low frequency synoptic chart, is developed to forecast severe precipitation events in Hunan Region based on NCEP/NCAR reanalysis data of 500 hPa height and 700 hPa winds as well as the daily rainfall data from 97 observation stations in Hunan Province during 2006--2010. Mean- while, the synoptic key regions are determined and the characteristics of low-frequency waves are ana- lyzed. Using historic data for validation, the average fitting rate of hindcast is 64.4% in April, 54.9% in May and 50.7% in June. Compared with the lead time of 10 d, 15 d, 20 d and 25 d, the fitting rate of hindcasts increases to the maximum at the lead time of 30 d. Applying the data to the forecasting of the severe precipitation events from April to June 2011 gives a good prediction result with the accuracy rate reaching 70%, the vacancy rate being 30% and no missing rate.

关 键 词：低频天气图 强降水过程 预报模型 

分 类 号：P456[天文地球—大气科学及气象学]