上海城市空气质量预报分类统计模型  

Classified Statistic Model of Urban Ambient Air Quality Forecasting in Shanghai

作　　者：阴俊 谈建国 

机构地区：[1]上海市城市环境研究中心,上海200030

出　　处：《气象科技》2004年第6期410-413,共4页Meteorological Science and Technology

基　　金：中国气象局"十五"基本建设项目"上海城市环境气象业务服务系统建设"资助

摘　　要：上海城市空气质量预报的分类统计模型利用上海地区 2 0 0 0年 6月至 2 0 0 2年 12月的空气污染浓度资料及常规气象资料建立模型 ,用 2 0 0 3年全年资料检验模型。模型采用方差分析方法区分不同污染浓度高低的气象条件 ,按季节、地面风向和雨量 3项指标对浓度样本分类 ,季节分类划分冬、夏半年子样本 ,风向分类划分偏西风向、非西风向子样本 ,雨量分类划分有雨、无雨子样本 ,共计 3层分类 ,18个分类子样本 ,样本分类的高值区和低值区与实际污染浓度的季节、地面风向和雨量的分布是一致的。最后 ,采用线性逐步回归方法对各分类子样本建立起一组预报模型。模型的检验评分结果显示 :分类统计模型较全样本统计模型实际业务预报精度有所提高 ,在城市空气质量预报中是切实可行的。The classified statistic model of urban ambient air quality forecasting was established by means of pollutant concentration data from June 2000 to December 2002 in Shanghai, and its forecast capability was tested by 1-year (2003) data. Variance analysis was selected to classify the samples, empirically taking season, surface wind direction and precipitation as 3 indicators: winter-half-year and summer-half-year sub-samples (season), west wind and non-west wind sub-samples (wind direction), and rainfall and non-rainfall sub-samples (precipitation). After the 3-layer classification, the whole sample was divided into 18 sub-samples. The high and low concentration sections of the sample classification are practically in accordance with the season, surface wind direction and precipitation distributions of pollutant concentrations. Finally the classified sub-samples were processed to establish a set of forecasting models by the linear successive regression technique. In the capability testing, the classified statistic model has proved feasible in the urban ambient air quality forecasting with higher prediction accuracy compared to the total sample statistic model.

关 键 词：风向 雨量 空气质量预报 地面风 气象资料 逐步回归方法 预报精度 季节 浓度 上海地区 

分 类 号：P457[天文地球—大气科学及气象学] P425.4