| B08RDP区域集合预报温度场质量评估与综合偏差订正 |
| |
| 引用本文： | 马旭林,周勃旸,时洋,计燕霞,和杰.B08RDP区域集合预报温度场质量评估与综合偏差订正[J].大气科学学报,2016,39(5):643-652. |
| |
| 作者姓名： | 马旭林 周勃旸 时洋 计燕霞 和杰 |
| |
| 作者单位： | 南京信息工程大学 气象灾害教育部重点实验室, 江苏 南京 210044;南京信息工程大学 气象灾害教育部重点实验室, 江苏 南京 210044;南京信息工程大学 气象灾害教育部重点实验室, 江苏 南京 210044;广东省气象台, 广东 广州 510080;南京信息工程大学 气象灾害教育部重点实验室, 江苏 南京 210044;南京信息工程大学 气象灾害教育部重点实验室, 江苏 南京 210044 |
| |
| 基金项目： | 国家自然科学基金资助项目（41275111；91437113）；公益性行业（气象）科研专项（GYHY201506005） |
| |
| 摘 要： | 针对B08RDP(The Beijing 2008 Olympics Research and Development Project)5套区域集合预报资料,系统分析了各套集合预报温度场的预报质量。在此基础上运用集合预报的综合偏差订正方法对温度场进行偏差订正,并对其效果进行了分析讨论。结果显示:5套B08RDP区域集合预报中,美国国家环境预报中心(NCEP)区域集合预报温度场的整体预报质量最高,平均预报误差最小,离散度也最为合理,预报可信度和可辨识度均较优;而中国气象科学研究院(CAMS)的温度预报误差过大,预报质量最差。整体上看,除NCEP之外的4套集合预报的温度场均存在集合离散度偏小的问题;综合偏差订正能有效减小各集合预报温度场的集合平均均方根误差,改善集合离散度的质量,显示出综合偏差订正方案对集合预报温度场偏差订正的良好能力。
|
| 关 键 词： | 数值预报 集合预报 偏差订正 质量评估 B08RDP |
| 收稿时间： | 2014/11/24 0:00:00 |
| 修稿时间： | 2015/6/21 0:00:00 |
Evaluation and combined bias correction on temperature forecast of regional ensemble prediction system of B08RDP |
| |
| MA Xulin,ZHOU Boyang,SHI Yang,JI Yanxia and He Jie.Evaluation and combined bias correction on temperature forecast of regional ensemble prediction system of B08RDP[J].大气科学学报,2016,39(5):643-652. |
| |
| Authors: | MA Xulin ZHOU Boyang SHI Yang JI Yanxia and He Jie |
| |
| Institution: | Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Guangdong Meteorological Observatory, Guangzhou 510080, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China |
| |
| Abstract: | Five sets of regional ensemble forecasts with lead times of 36 h over two months from 24 June 2008 to 24 August 2008 from the Beijing 2008 Olympics Research and Development Project(B08RDP) are evaluated and analyzed.This is firstly done by means of standard probabilistic verification scores,including root-mean-square error(RMSE),ensemble spread,talagrand diagrams,reliability,and ROC(Relative Operating Characteristic) curves.Then,to improve the forecast quality,a combined decaying averaging bias correction scheme(BC) is applied to the ensemble forecasts of B08RDP to reduce the bias in the ensemble mean and to adjust the improper spread of ensembles with sufficient performance evaluation.The BC scheme is designed based on the original Kalman filter.It contains the first moment bias correction,mainly for correcting the bias in the ensemble mean to improve the reliability of the ensemble forecasts,and the second moment bias correction mainly for adjusting the ensemble spread to make the ensemble forecasts fully representative of the uncertainties in the observations.Lastly,the BC scheme''s capacity is evaluated and discussed by means of the verification scores mentioned above.Temperatures at 850 hPa are corrected and verified in this study,wherein ECMWF reanalysis data are used as the reference for the verification.The results show that,among the five sets of regional ensemble forecasts in B08RDP,the regional ensemble forecasts from NCEP possess the best forecast quality,with minimal bias,the most appropriate spread,and the best performance in terms of reliability,resolution and talagrand distributions.Meanwhile,the regional ensemble forecast from CAMS demonstrates the worst forecast quality,due to its largest forecast bias.On the whole,a relatively small spread is a common problem for several of the ensemble forecasts,except those from NCEP.In general,the combined bias correction scheme is proven to be efficient in reducing the RMSE of the ensemble mean,and in generating a more appropriate ensemble spread,for the five sets of ensemble forecasts,revealing its ability to improve the quality of ensemble forecasts,especially for ensemble forecasts of an already low quality. |
| |
| Keywords: | numerical weather prediction ensemble weather forecast combined bias correction performance evaluation B08RDP |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《大气科学学报》浏览原始摘要信息 |
| 点击此处可从《大气科学学报》下载免费的PDF全文 |
|
