CAJ | 학술논문

对2009年7月至2010年6月区域空气质量数值预报模式CAPPS3在福州市的应用进行效果检验,分析各季节CAPPS3预报福州市3种污染物SO2、NO2和PM10的等级预报准确率、转折性天气预报准确率及与监测值的相关系数以及综合评分。结果表明：夏秋季节CAPPS3模式3种污染物等级预报准确率较高,冬季NO2和春季PM10的等级预报准确率较低,错误等级预报多数偏高;转折性天气预报准确率夏秋季最高,春季最低,模式对天气形势的变化反应不灵敏,特别是污染物浓度突变时,预报能力较差,当天气形势稳定时,预报效果较好;CAPPS3模式浓度预报值较监测值有偏大和滞后的缺点;相关系数及综合评分结果夏秋季最高,春季最低。CAPPS3总体预报效果较好,可提供有价值的指导预报,适合业务运行。
대2009년7월지2010년6월구역공기질량수치예보모식CAPPS3재복주시적응용진행효과검험,분석각계절CAPPS3예보복주시3충오염물SO2、NO2화PM10적등급예보준학솔、전절성천기예보준학솔급여감측치적상관계수이급종합평분。결과표명：하추계절CAPPS3모식3충오염물등급예보준학솔교고,동계NO2화춘계PM10적등급예보준학솔교저,착오등급예보다수편고;전절성천기예보준학솔하추계최고,춘계최저,모식대천기형세적변화반응불령민,특별시오염물농도돌변시,예보능력교차,당천기형세은정시,예보효과교호;CAPPS3모식농도예보치교감측치유편대화체후적결점;상관계수급종합평분결과하추계최고,춘계최저。CAPPS3총체예보효과교호,가제공유개치적지도예보,괄합업무운행。
Forecasting results from a city air pollution numerical prediction system（CAPPS3） mode were validated in Fuzhou for a period of July 2009 to June 2010.The prediction accuracy of pollution level of SO2,NO2 and PM10,the prediction accuracy of transitional weather,correlation coefficient between forecasting value and observational value and synthesis scoring were analyzed in different seasons.The results show that the prediction accuracy of pollution level based on the CAPPS3 mode is higher in summer and autumn for three pollutants,while it is lower in winter for NO2 and in spring for PM10 and the pollution level of most error prediction is higher.The prediction accuracy of transitional weather is higher in summer and autumn and lower in spring.The CAPPS3 mode is insensitive to change of weather conditions.The prediction ability of the CAPPS3 mode is lower when pollutants concentrations change abruptly,while it is higher under stable weather conditions.The forecasting values of pollutants concentrations based on the CAPPS3 are higher than the observational values and lag behind the reality.The correlation coefficient between forecasting values and observational values and synthesis scoring are higher in summer and autumn and lower in spring.In general,forecasting results of the CAPPS3 mode are reasonable.Thus,the mode could provide valuable prediction and is suitable for use in the operational system.