摘要:针对当前单模式系统臭氧（O3）预报的不确定性问题，提出了一种基于活动区间的多模式超级集成的、高效的预报方法。本研究基于长江三角洲（长三角）地区多模式空气质量预报系统，将改进后的超级集成预报方法（AR-SUP）运用到2015年长三角地区的O3预报中，并与滑动训练期的超级集成预报（R-SUP）、多模式集成平均预报（EMN）、消除偏差的集成平均预报（BREM）对比，结果表明AR-SUP对预报效果的改善最明显，其在暖季和冷季的均方根误差（RMSE）较最优单模式平均下降了20%和23%。将AR-SUP运用到48 h和72 h预报中发现，当预报时效增加时该方法依旧保持较高的预报技巧。多项统计数据均证明AR-SUP在研究时段内所有站点均能显著减小O3预报误差、提高整体相关性和一致性，有效提高当前短期（三天）预报准确率。
关键词:臭氧/
多模式系统/
超级集成预报/
活动区间
Abstract:Aiming at existing problems in current O3 single model forecast, an efficient superensemble forecast based on running active range (AR-SUP) is proposed and applied to the EMS-YRD (multi-model ensemble air quality forecast system for the Yangtze River Delta) O3 forecast during the study period in 2015. The performance of the newly proposed method is compared with those of R-SUP (Running Training Period Superensemble), EMN (Ensemble Mean), and BREM (Bias-Removed Ensemble Mean). The results show that compared with the other three ensemble methods, the AR-SUP exhibits significant improvement in daily O3 forecast with the RMSE reduced by 20% and 23% from that of the best single model in cool and warm seasons respectively. Further application of the AR-SUP in O3 ensemble forecast also shows high forecasting skills when the predicting time is extended to 48 h and 72 h. A number of statistical measures (i.e., reduced errors, increased correlation coefficients, and index of agreement) show that the forecasting skill has been improved at all the locations within the study region during all seasons, which indicates this method can be used to help improve the accuracy and reliability of short-term forecasts.
Key words:O3/
Ensemble air quality multi-model forecast system/
Superensemble forecast/
Running active range
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