摘要
为提高城市空气质量预报的准确率,研制了针对数值预报模式CAPPS2的订正方法,对2001—2007年西安市逐日PM10、SO_2、NO_2浓度均值和相应的降水、风速作经验模态分解(EMD)分析,用最大熵谱方法检验各本征模态函数(IMF)周期,计算其方差贡献率,制定订正方法并进行数值试验。结果表明:PM10浓度波动以周尺度为主,有明显周末效应,与主要清除过程匹配较好;SO_2、NO_2浓度波动与主要清除过程不同步;基于周末效应的订正规则对PM10、SO_2订正效果较理想,对NO_2订正效果不确定。
The daily average concentrations of PM10,SO2,NO2 and meteorological factors（precipitation and wind） of the corresponding time from 2001 to 2007 in Xi＇an,Shaanxi Province,are analyzed with Empirical Mode Decomposition（EMD）.The periods are tested and the variance contribution rates are calculated of each intrinsic mode function（IMF） by the maximum entropy spectral analysis as well,for improving the accuracy rate of the urban air quality forecast system（CAPPS2） and instituting the correcting rules for the numerical forecast model.The results show：the main period of PM10 concentration fluctuation is about a week,has clear weekend-effect,and matches well with major scavenging process,but the concentration fluctuations of SO2 and NO2 do not synchronize the scavenging processes,suggesting that the pollution of Xi＇an is emission-guided,and the correction rules based on the weekend-effect are ideal for the improvement of PM10 and SO2 numerical forecast results,and uncertain for NO2.
出处
《气象科技》
北大核心
2010年第6期679-683,共5页
Meteorological Science and Technology
基金
陕西省气象局研究型业务基金科研项目(2010M-18)资助
关键词
空气质量预报
经验模态分解
订正
air quality forecast
correction
empirical mode decomposition
