一种新的城市SO_2污染统计预报方法及其应用  

A NEW STATISTIC FORECASTING METHOD OF SO_2 POLLUTION AND ITS APPLICATION

作　　者：杨文峰[1] 史宝忠[2] 

机构地区：[1]陕西省气象局,西安710014 [2]西安建筑科技大学市政与环境工程学院,西安710055

出　　处：《应用气象学报》2003年第2期223-229,共7页Journal of Applied Meteorological Science

摘　　要：针对目前采用的统计方法存在的不足 ,即在选择预报因子时没有考虑预报因子之间的相关性 ,挑选的预报因子由于非正交 ,使回归计算的结果不稳定 ,给计算带来一定的误差。该文提出把一元线性回归分析、自然正交函数 (EOF)和逐步回归方法结合起来 ,从而得到一种新的建立统计预报模型的方法。以西安市采暖期和夏季SO2 日均浓度为预报对象 ,使用该方法建立预报模型。拟合及预报试验表明 ,这些预报模型不但可以很好地拟合变化趋势 ,而且还能作出较准确的预报 ,采暖期预报的级别命中率为 72 .5 % ,夏季级别预报命中率为1 0 0 %。通过对比试验 ,此方法优于目前常用的逐步回归方法 ,具有很好的应用前景。Concerning the limits of the currently used statistic methods of air pollution (not considering correlation and non orthogonality among forecasting factors results in regression instability and more errors), the linear regression and empirical orthogonal function (EOF) are combined with the stepwise regression analysis method,and thus a new forecasting method in the building forecasting model is proposed. By using this method for forecasting SO 2 density in the heating period, the model fitting and forecasting show that these models can not only fit the changing tendency of SO 2 density,but also forecast SO 2 density quite well,e. g., the grade accuracy is 72.5 percent. In contrast with the stepwise regression analysis method, during the forecast experiment,the result of the new forecasting method is more accurate. The new forecasting method has good prospect in application.

关 键 词：统计方法 预报因子 正交函数 逐步回归方法 统计预报模型 城市空气污染 污染预报模型 二氧化硫 

分 类 号：P456[天文地球—大气科学及气象学]