利用多模式最优集成方法预报上海PM_(2.5)
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摘要
采用多模式最优集成方法(OCF),对PANDA项目中国和欧洲7个空气质量模式的PM_(2.5)预报结果进行集成释用.2016年6月—2017年5月对上海逐日预报试验结果表明:和最优单模式预报结果相比,OCF预报的PM_(2.5)日均质量浓度的均方根误差降低1.9μg·m-3,相关系数提高0.04,日均质量浓度的精度评分TI提高了2.4,污染TS评分提高了0.28,污染空报率降低了20%,显著提高了PM_(2.5)污染等级预报、趋势预报和精度预报的技巧.对长三角合肥、南京、苏州、杭州、宁波5个城市的预报试验也得到类似的结果,为城市空气质量预报提供了新的方法和思路.但OCF对客观预报的改进幅度在夏季不如冬季显著,在降雨日相对较低.
In this study,the OCF method was applied to conduct the daily PM_(2.5) ensemble forecasts in Shanghai during June 2016 to May 2017 based on the outputs from 7 PANDA air quality models. The results showed that the PM_(2.5) forecast performance in Shanghai was significantly increased by OCF compared with any of the PANDA models. The RMSE of daily averaged PM_(2.5) mass concentration decreased by 1.9 μg·m-3,the correlation coefficient increased by 0.04,and the false detection rate for pollution days reduced by 20%. Furthermore,both TS and TI marks which were used to evaluate the forecast accuracy for PM_(2.5) pollution day and the PM_(2.5) mean daily mass concentration were both advanced by 0.28 and 2.4 respectively. Similar positive results were achieved by OCF experiments for other 5 cities in YRD region. Thus it could be concluded that OCF can be regarded as an efficient ensemble method for current urban air quality forecast operations. Nevertheless the advantage of OCF was less effective in winter than in summer,and less skillful under rain day conditions.
In this study,the OCF method was applied to conduct the daily PM_(2.5) ensemble forecasts in Shanghai during June 2016 to May 2017 based on the outputs from 7 PANDA air quality models. The results showed that the PM_(2.5) forecast performance in Shanghai was significantly increased by OCF compared with any of the PANDA models. The RMSE of daily averaged PM_(2.5) mass concentration decreased by 1.9 μg·m-3,the correlation coefficient increased by 0.04,and the false detection rate for pollution days reduced by 20%. Furthermore,both TS and TI marks which were used to evaluate the forecast accuracy for PM_(2.5) pollution day and the PM_(2.5) mean daily mass concentration were both advanced by 0.28 and 2.4 respectively. Similar positive results were achieved by OCF experiments for other 5 cities in YRD region. Thus it could be concluded that OCF can be regarded as an efficient ensemble method for current urban air quality forecast operations. Nevertheless the advantage of OCF was less effective in winter than in summer,and less skillful under rain day conditions.
引文
Boylan J,Russell A.2006.PM and light extinction model performance metrics,goals,and criteria for three-dimensional air quality models[J].Atmospheric Environment,40(26):4946-4959
白永清,祁海霞,刘琳,等.2016.华中区域环境气象数值预报系统及其初步应用[J].高原气象,35(6):1671-1682
曹国良,张小曳,龚山陵,等.2011.中国区域主要颗粒物及污染气体的排放源清单[J].科学通报,56(3):261-268
陈焕盛,王自发,吴其重,等.2013.空气质量多模式系统在广州应用及对PM10预报效果评估[J].气候与环境研究,18(4):427-435
Grell G,Peckham S,Schmitz R,et al.2005.Fully coupled“online”chemistry within the WRF model[J].Atmospheric Environment,39:6957-6975
侯雪伟,朱彬,康汉青,等.2013.MOZART-4大气化学模式模拟东亚季风对对流层污染物的影响:模式验证[J].高原气象,32(2):2387-2401
胡鸣,赵倩彪,伏晴艳.2015.上海环境空气质量预报考核评分方法研究和应用[J].中国环境监测,31(4):54-57
黄思,唐晓,徐文帅,等.2015.利用多模式集合和多元线性回归改进北京PM10预报[J].环境科学学报,35(1):56-64
黄晓波,殷晓鸿,黄志炯,等.2016.不同模式对珠三角地区细颗粒物污染模拟效果对比评估[J].环境科学学报,36(10):3505-3514
Jeffery A,Clifford F.2005.Performance of national weather service forecasts compared to operational,consensus,and weighted model output statistics[J].Weather and Forecasting,20:1034-1407
Pasch A N,Macdonald C P,Gilliam R C,et al.2011.Meteorological characteristics associated with PM2.5air pollution in Cleveland,Ohio,during the 2009-2010 Cleveland multiple air pollutants study[J].Atmospheric Environment,45(39):7026-7035
漆梁波,曹晓岗,夏立,等.2007.上海区域要素客观预报方法效果检验[J].气象,33(9):9-18
王自发,吴其重,等.2009.北京空气质量多模式集成预报系统的建立及初步应用[J].南京信息工程大学学报(自然科学版),1(1):19-26
吴剑斌,肖林鸿,晏平仲,等.2017.最优化集成方法在城市臭氧数值预报中的应用研究[J].中国环境监测,33(4):213-220
吴蒙,吴兑,范绍佳.2015.基于风廓线仪等资料的珠江三角洲污染气象条件研究[J].环境科学学报,35(3):619-629
Wang Z F,Xie F Y,Wang X Q,et al.2006.Development and application of nested air quality prediction modeling system[J].Chinese Journal of Atmospheric Sciences-Chinese Edition,30(5):680-689
Woodcock F,Engel C.2005.Operational Consensus Forecast[J].Weather and Forecasting,20:101-111
许建明,常炉予,马井会,等.2016.上海秋冬季PM2.5污染天气形势的客观分型研究[J].环境科学学报,36(12):4303-4314
许建明,高伟,瞿元昊.2017.上海地区降雨清除PM2.5的观测研究[J].环境科学学报,37(9):3271-3279
于燕,廖礼,崔雪东,等.2017.不同人为源排放清单对大气污染物浓度数值模拟的影响:以浙江省为例[J].气候与环境研究,22(5):519-537
张伟,王自发,安俊岭,等.2010.利用BP神经网络提高奥运会空气质量实时预报系统预报效果[J].气候与环境研究,15(5):595-601
赵海波,郑楚光.2005.降雨过程中气溶胶湿沉降的数值模拟[J].环境科学学报,25(12):1590-1596
赵敬国,王式功,张天宇,等.2015.兰州市大气重污染气象成因分析[J].环境科学学报,35(5):1547-1555
钟方潜,苏琪骅,周任君,等.2017.秸秆焚烧对区域城市空气质量影响的模拟分析[J].气候与环境研究,22(2):149-161
周广强,高伟,谷怡萱,等.2017.WRF-Chem模式降水对上海PM2.5预报的影响[J].环境科学学报,37(12):4476-4482
周广强,谢英,吴剑斌,等.2016.基于WRF-Chem模式的华东区域PM2.5预报及偏差原因[J].中国环境科学,36(8):2251-2259
朱占云,陈光宇,姜瑜君,等.2016.浙江省六大水库流域面雨量模式预报效果检验[J].气象与环境学报,32(3):28-33
白永清,祁海霞,刘琳,等.2016.华中区域环境气象数值预报系统及其初步应用[J].高原气象,35(6):1671-1682
曹国良,张小曳,龚山陵,等.2011.中国区域主要颗粒物及污染气体的排放源清单[J].科学通报,56(3):261-268
陈焕盛,王自发,吴其重,等.2013.空气质量多模式系统在广州应用及对PM10预报效果评估[J].气候与环境研究,18(4):427-435
Grell G,Peckham S,Schmitz R,et al.2005.Fully coupled“online”chemistry within the WRF model[J].Atmospheric Environment,39:6957-6975
侯雪伟,朱彬,康汉青,等.2013.MOZART-4大气化学模式模拟东亚季风对对流层污染物的影响:模式验证[J].高原气象,32(2):2387-2401
胡鸣,赵倩彪,伏晴艳.2015.上海环境空气质量预报考核评分方法研究和应用[J].中国环境监测,31(4):54-57
黄思,唐晓,徐文帅,等.2015.利用多模式集合和多元线性回归改进北京PM10预报[J].环境科学学报,35(1):56-64
黄晓波,殷晓鸿,黄志炯,等.2016.不同模式对珠三角地区细颗粒物污染模拟效果对比评估[J].环境科学学报,36(10):3505-3514
Jeffery A,Clifford F.2005.Performance of national weather service forecasts compared to operational,consensus,and weighted model output statistics[J].Weather and Forecasting,20:1034-1407
Pasch A N,Macdonald C P,Gilliam R C,et al.2011.Meteorological characteristics associated with PM2.5air pollution in Cleveland,Ohio,during the 2009-2010 Cleveland multiple air pollutants study[J].Atmospheric Environment,45(39):7026-7035
漆梁波,曹晓岗,夏立,等.2007.上海区域要素客观预报方法效果检验[J].气象,33(9):9-18
王自发,吴其重,等.2009.北京空气质量多模式集成预报系统的建立及初步应用[J].南京信息工程大学学报(自然科学版),1(1):19-26
吴剑斌,肖林鸿,晏平仲,等.2017.最优化集成方法在城市臭氧数值预报中的应用研究[J].中国环境监测,33(4):213-220
吴蒙,吴兑,范绍佳.2015.基于风廓线仪等资料的珠江三角洲污染气象条件研究[J].环境科学学报,35(3):619-629
Wang Z F,Xie F Y,Wang X Q,et al.2006.Development and application of nested air quality prediction modeling system[J].Chinese Journal of Atmospheric Sciences-Chinese Edition,30(5):680-689
Woodcock F,Engel C.2005.Operational Consensus Forecast[J].Weather and Forecasting,20:101-111
许建明,常炉予,马井会,等.2016.上海秋冬季PM2.5污染天气形势的客观分型研究[J].环境科学学报,36(12):4303-4314
许建明,高伟,瞿元昊.2017.上海地区降雨清除PM2.5的观测研究[J].环境科学学报,37(9):3271-3279
于燕,廖礼,崔雪东,等.2017.不同人为源排放清单对大气污染物浓度数值模拟的影响:以浙江省为例[J].气候与环境研究,22(5):519-537
张伟,王自发,安俊岭,等.2010.利用BP神经网络提高奥运会空气质量实时预报系统预报效果[J].气候与环境研究,15(5):595-601
赵海波,郑楚光.2005.降雨过程中气溶胶湿沉降的数值模拟[J].环境科学学报,25(12):1590-1596
赵敬国,王式功,张天宇,等.2015.兰州市大气重污染气象成因分析[J].环境科学学报,35(5):1547-1555
钟方潜,苏琪骅,周任君,等.2017.秸秆焚烧对区域城市空气质量影响的模拟分析[J].气候与环境研究,22(2):149-161
周广强,高伟,谷怡萱,等.2017.WRF-Chem模式降水对上海PM2.5预报的影响[J].环境科学学报,37(12):4476-4482
周广强,谢英,吴剑斌,等.2016.基于WRF-Chem模式的华东区域PM2.5预报及偏差原因[J].中国环境科学,36(8):2251-2259
朱占云,陈光宇,姜瑜君,等.2016.浙江省六大水库流域面雨量模式预报效果检验[J].气象与环境学报,32(3):28-33