摘要
利用2015年8月至2017年7月长兴岛站和交流岛站日最高气温、日最低气温实况资料,对ECMWF细网格2 m温度预报值和日本FSFE02(24 h地面形势场预报)、FSFE03(36 h地面形势场预报)进行了检验。结果表明:根据历史回归统计检验,ECMWF细网格模式24 h的2 m最高气温、最低气温预报效果显著,通过了0. 05信度显著性检验。对各月做相关分析,相关性均较好。利用前一日ECMWF细网格2 m温度预报值与长兴岛站实况差值,根据统计的ECMWF细网格2 m温度预报订正值,做出长兴岛站未来24 h的气温预报。交流岛站温度预报是在长兴岛站温度预报的基础上订正做出,经统计分析,交流岛站和长兴岛站的气温差值与地面形势场和风场有较好的对应关系,根据不同类型的地面形势场和风场订正值,做出交流岛站的温度预报。应用Matlab计算机语言的开发功能,提取ECMWF细网格2 m温度预报的最高、最低气温值,并录入当日长兴岛站和交流岛站最高、最低气温实况值,自动预报各站未来24 h最高气温、最低气温。创建可视化预报工作界面,实现乡镇温度预报自动化。
Using the observation data of daily maximum and minimum temperature in Changxing island and Jiaoliu island weather stations from August 2015 to July 2017,the 2 m fine ECMWF grid temperature forecast value,the Japanese FSFE02 (24 h ground situation forecast) and FSFE03 (36 h ground situation forecast) were verified.The results show that on the basis of the historical regression statistical test method,the forecasted 24 hours maximum and minimum temperatures at 2 m using the ECMWF fine grid model have significant forecast effects and pass the 0.05 confidence test.A close correlational relationship between the prediction and observation for each month is obtained. Making use of the difference of the 2 m temperature between the observation and the forecast value from ECMWF fine mesh the day before in Changxing island,integrating the statistical correction of the 2 m temperature forecast values from the ECMWF fine grid,the temperature for the next 24 hours at Changxing island stations is forecasted.The temperature forecast of Jiaoliu island station is produced based on that of Changxing island station.On the basis of the statistical analysis,the temperature difference between Jiaoliu island and Changxing island station is closely related to the ground situation and wind field.Based on the corrections of different ground conditions and wind field,the temperature at Jiaoliu island station is forecasted.Applying development function of the Matlab computer language to extract the maximal and minimal temperature at 2 m from the ECMWF fine mesh and to input their real values at Changxing and Jiaoliu island stations,the maximum and minimum temperatures in the next 24 hours are automatically forecasted.Besides,a visual forecast working platform is built to realize the automation of villages and towns temperature forecast.
作者
吴春英
刘多文
钟博
蒋婷婷
于蕙箐
陈佳美
高燕
WU Chun-ying;LIU Duo-wen;ZHONG Bo;JIANG Ting-ting;YU Hui-jing;GAO Yan(Meteorological Service of Changxing Island Economic Zone of Dalian,Dalian 116317,China;Fushun ofDalian Meteorological Service,Fushun 113006,China;Dalian Meteorological Service,Dalian 116001,China;Pulandian Meteorological Service,Pulandian 116200,China)
出处
《气象与环境学报》
2019年第1期108-112,共5页
Journal of Meteorology and Environment
基金
大连市气象局业务应用开发项目(DLQX201522)资助
关键词
数值预报
温度预报
模式检验
Numerical forecast
Temperature prediction
Model test
