摘要
降水精细化数值预报模式的发展是开展精细化降水预报业务的理想途径,而模式本地化中的误差评估是当前开展业务应用的重要环节。基于此,运用误差分析、晴雨预报准确率、降水TS评分方法评估陕西精细化数值预报攻关团队提供的2016年5月1日~9月30日安康水电站降水预报。结果表明:随着降水时效的增长,降水的预报准确率呈减小趋势;大雨以上的降水过程预报较好且未出现漏报,但量值与实况有差异,预报值小于实况值; 20时起报的预报准确率大于08时起报的准确率且夜间的高于白天;降水日数多的月份TS评分预报准确率高于降水日数少的月份。比较安康和石泉的结果发现,安康的预报准确率明显优于石泉,主要原因是安康降水日数比石泉多,且大的降水过程比石泉少。逐1 h、3 h的72 h以内的降水预报可以为安康水电厂水利调度提供参考。
The development of numerical precipitation forecasting model in high resolution is an ideal way to carry out the refined precipitation forecast service.However,the bias evaluation in model localization is an important process of the current application service.In this study,the bias analysis,clear-rain forecast accuracy,and precipitation TS scoring method were used to evaluate the precipitation forecast at Ankang hydropower Station,Shaanxi Province,China in the flood season from May 1to September 30,2016which was provided by the Shaanxi refined numerical forecasting team.The results indicated that the forecast accuracy rate of precipitation is declining with the increase of precipitation forecast aging.The prediction of heavy rain has a high accuracy rate without omission,while the prediction values are less than the actual values.The forecast accuracy rate initialized in 20:00is higher than that in 08:00,and the accuracy rate at night is higher than that of daytime.Months with more rainfall days have a higher forest accuracy rate according to TS scoring than that of months with less rainfall.The forecast accuracy rate of the Ankang is better than that of Shiquan.The main reason is that the precipitation days (precipitation amount) of Ankang is more than those of Shiquan.These hourly and 3-hourly (within 72hours)precipitation forecasts can provide a reference for the water dispatching service of Ankang hydroelectric power station.
作者
高红燕
席秋义
王丹
张宏芳
浩宇
GAO Hong-yan;XI Qiu-yi;WANG Dan;ZHANG Hong-fang;HAO Yu(Meteorological Service Center of Shaanxi Province,Xi'an 710014,Shaanxi,China;State Grid Shaanxi Electric Power Research Institute,Xi'an 710100,Shaanxi,China)
出处
《干旱区地理》
CSCD
北大核心
2018年第6期1169-1177,共9页
Arid Land Geography
基金
陕西省科技发展计划项目(2012K12-03-02)
国网陕西省电力公司(5226AS150004)
陕西省气象局重点科研项目(2016Z-1)
关键词
数值预报
检验评估
降水预报
numerical forecast
test and assessment
precipitation forecast