北京地区一次空气重污染过程的目标观测分析
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摘要
针对北京市2016年12月16～21日的空气重污染过程进行了回报试验,探讨了该次事件预报的目标观测敏感区。使用新一代高分辨率中尺度气象模式(Weather Research Forecasting,WRF)和嵌套网格空气质量模式(Nested Air Quality Prediction Model System,NAQPMS),针对初始气象场的不确定性,通过4套初始场资料识别了影响北京地区细颗粒物(PM2.5)预报水平的目标观测敏感变量及其敏感区。结果表明:当综合考虑初始气象场的风场、温度、比湿不确定性的影响时,发现改善黑龙江区域上述气象要素的初始场精度,对北京地区PM2.5预报不确定的减小最显著;当分别考察风场、温度、比湿的不确定性的影响时,发现初始风场精度的改善,尤其是黑龙江区域风场精度的改善,能够更大程度地减小北京地区PM2.5的预报误差,对北京东南地区的PM2.5预报误差的减小甚至可达到40%以上。因此,优先对黑龙江区域的气象场,尤其是该区域的风场进行目标观测,并将其同化到预报模式的初始场中,将会有效提高初始气象场的质量,进而大大减小北京地区PM2.5浓度的预报误差,提高北京地区空气质量的预报技巧。初始风场代表了北京地区该次空气重污染事件预报的目标观测变量,而黑龙江地区则是该目标观测的敏感区域。
A hindcast experiment is conducted for the heavy air pollution event in Beijing that occurred during 16-21 December 2016 and the sensitive area for target observation that can help to improve initialization are explored using the Weather Research Forecasting(WRF) model and the Nested Air Quality Prediction Model System(NAQPMS). To address the uncertainty of meteorological initial field, the sensitive variables and areas for the prediction of PM2.5 concentration in Beijing are identified by adopting four sets of initial analysis fields. The results show that when considering the initial uncertainties of wind, temperature, and specific humidity, their reductions in Heilongjiang region can most significantly decrease the forecast error of the PM2.5 concentration in Beijing. Furthermore, it is found that the improvement of the accuracy of initial wind fields, especially that in Heilongjiang region, decreases the forecast error of the PM2.5 concentration in Beijing to a great extent, and the decrease can be up to more than 40% in southwestern Beijing. Therefore, increasing more meteorological(especially wind) observations in Heilongjiang region and assimilating these observations into the initial field of the WRF model will significantly improve the quality of the initial meteorological condition and thus greatly reduce the PM2.5 forecast error of the air pollution event in Beijing. The model forecast skill will be greatly improved. It is concluded that the wind component in the initial field represents the physical variable and Heilongjiang region is the sensitive area for target observation associated with the forecast of the heavy air pollution event in Beijing that is selected for the present study.
A hindcast experiment is conducted for the heavy air pollution event in Beijing that occurred during 16-21 December 2016 and the sensitive area for target observation that can help to improve initialization are explored using the Weather Research Forecasting(WRF) model and the Nested Air Quality Prediction Model System(NAQPMS). To address the uncertainty of meteorological initial field, the sensitive variables and areas for the prediction of PM2.5 concentration in Beijing are identified by adopting four sets of initial analysis fields. The results show that when considering the initial uncertainties of wind, temperature, and specific humidity, their reductions in Heilongjiang region can most significantly decrease the forecast error of the PM2.5 concentration in Beijing. Furthermore, it is found that the improvement of the accuracy of initial wind fields, especially that in Heilongjiang region, decreases the forecast error of the PM2.5 concentration in Beijing to a great extent, and the decrease can be up to more than 40% in southwestern Beijing. Therefore, increasing more meteorological(especially wind) observations in Heilongjiang region and assimilating these observations into the initial field of the WRF model will significantly improve the quality of the initial meteorological condition and thus greatly reduce the PM2.5 forecast error of the air pollution event in Beijing. The model forecast skill will be greatly improved. It is concluded that the wind component in the initial field represents the physical variable and Heilongjiang region is the sensitive area for target observation associated with the forecast of the heavy air pollution event in Beijing that is selected for the present study.
引文
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Mu M.2013.Methods,current status,and prospect of targeted observation[J].Science ChinaEarth Sciences,56(12):1997-2005,doi:10.1007/s11430-013-4727-x.
任万辉,苏枞枞,赵宏德.2010.城市环境空气污染预报研究进展[J].环境保护科学,36(3):9-11.RenWanhui,Su Congcong,Zhao Hongde.2010.Research progress of air pollution forecasting in urban area[J].Environmental Protection Science(in Chinese),36(3):9-11,doi:10.3969/j.issn.1004-6216.2010.03.004.
Riehl H,Haggard W H,Sanborn R W.1956.On the prediction of 24-hour hurricane motion[J].J.Meteor.,13(5):415-420,doi:10.1175/1520-0469(1956)013<0415:OTPOHH>2.0.CO;2.
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隋珂珂,王自发,杨军,等.2007.北京PM10持续污染及与常规气象要素的关系[J].环境科学研究,20(6):77-82.Sui Keke,Wang Zifa,Yang Jun,et al.2007.Beijing persistent PM10 pollution and its relationship with general meteorological features[J].Research of Environmental Sciences(in Chinese),20(6):77-82.
唐晓,王自发,朱江,等.2010.蒙特卡罗不确定性分析在O3模拟中的初步应用[J].气候与环境研究,15(5):541-550.Tang Xiao,Wang Zifa,Zhu Jiang,et al.2010.Preliminary application of Monte Carlo uncertainty analysis in O3 simulation[J].Climatic and Environmental Research(in Chinese),15(5):541-550,doi:10.3878/j.issn.1006-9585.2010.05.02.
Tang X,Zhu J,Wang Z F,et al.2011.Improvement of ozone forecast over Beijing based on ensemble Kalman filter with simultaneous adjustment of initial conditions and emissions[J].Atmospheric Chemistry and Physics,11(24):12901-12916,doi:10.5194/acp-11-12901-2011.
唐孝炎,张远航,邵敏.2006.大气环境化学(2版)[M].北京:高等教育出版社,49-62.Tang Xiaoyan,Zhang Yuanhang,Shao Min.2006.Atmospheric Environmental Chemistry(2nd ed)(in Chinese)[M].Beijing:Higher Education Press,49-62.
佟彦超.2006.中国重点城市空气污染预报及其进展[J].中国环境监测,22(2):69-71.Tong Yanchao.2006.Air quality forecast and development in major cities of China[J].Environmental Monitoringin China(in Chinese),22(2):69-71,doi:10.3969/j.issn.1002-6002.2006.02.022.
王威,李杰,朱莉莉.2016.9·3阅兵期间京津冀及周边地区污染源减排贡献模拟分析[C]//2016中国环境科学学会学术年会论文集(第一卷).海口:中国环境科学学会,38-45.Wang Wei,Li Jie,Zhu Lili.2016.9·3simulation analysis of contribution of pollutants to emission reduction in Beijing-Tianjin-Hebeiregion and peripheral areas during parade[C]//Annual Conference of Chinese Society of Environmental Sciences(in Chinese).Haikou:Chinese Society for Environmental Sciences,38-45.
Wang Z,Maeda T,Hayashi M,et al.2001.A nested air quality prediction modeling system for urban and regional scales:Application for highozone episode in Taiwan[J].Water,Air,and Soil Pollution,130(1-4):391-396,doi:10.1023/A:1013833217916.
王哲,王自发,李杰,等.2014.气象-化学双向耦合模式(WRF-NAQPMS)研制及其在京津冀秋季重霾模拟中的应用[J].气候与环境研究,19(2):153-163.Wang Zhe,Wang Zifa,Li Jie,et al.2014.Development of a meteorology-chemistry two-way coupled numerical model(WRF-NAQPMS)and its application in a severe autumn haze simulation over the Beijing-Tianjin-Hebei area,China[J].Climatic and Environmental Research(in Chinese),19(2):153-163,doi:10.3878/j.issn.1006-9585.2014.13231.
王自发,谢付莹,王喜全,等.2006.嵌套网格空气质量预报模式系统的发展与应用[J].大气科学,30(5):778-790.Wang Zifa,XieFuying,Wang Xiquan,et al.2006.Development and application of Nested Air Quality Prediction Modeling System[J].Chinese Journal of Atmospheric Sciences(in Chinese),30(5):778-790,doi:10.3878/j.issn.1006-9895.2006.05.07.
吴其重,王自发,徐文帅,等.2010.多模式模拟评估奥运赛事期间可吸入颗粒物减排效果[J].环境科学学报,30(9):1739-1748.Wu Qizhong,Wang Zifa,Xu Wenshuai,et al.2010.Multi-model simulation of PM10 during the 2008 Beijing Olympic Games:Effectiveness of emission restrictions[J].Acta Scientiae Circumstantiae(in Chinese),30(9):1739-1748.
杨兴川,赵文吉,熊秋林,等.2017.2016年京津冀地区PM2.5时空分布特征及其与气象因素的关系[J].生态环境学报,26(10):1747-1754.Yang Xingchuan,Zhao Wenji,Xiong Qiulin,et al.2017.Spatio-temporal distribution of PM2.5 in Beijing-Tianjin-Hebei(BTH)area in 2016 and its relationship with meteorological factors[J].Ecology and Environment Sciences(in Chinese),26(10):1747-1754,doi:10.16258/j.cnki.1674-5906.2017.10.014.
周菲凡.2009.条件非线性最优扰动方法在台风目标观测中的应用研究[D].中国科学院大气物理研究所博士学位论文,136pp.Zhou Feifan.2009.Application of the optimal nonlinear perturbation method to typhoon target observation[D].Ph.D.dissertation(in Chinese),Institute of Atmospheric Physics,Chinese Academy of Sciences,136pp.
Zhou F F,Mu M.2012.The time and regime dependencies of sensitive areas for tropical cyclone prediction using the CNOP method[J].Advances in Atmospheric Sciences,29(4):705-716,doi:10.1007/s00376-012-1174-0.
Chen Z Y,XieX M,Cai J,et al.2018.Understanding meteorological influences on PM2.5 concentrations across China:A temporal and spatial perspective[J].Atmospheric Chemistry and Physics,18(8):5343-5358,doi:10.5194/acp-2017-376.
程兴宏.2008.空气质量模式“源同化”模型及排放源影响效应研究[D].中国科学院研究生院博士学位论文,149pp.Cheng Xinghong.2008.Research on inverse modeling of SO2 and NOx emissions coupled with air quality model using adaptive nudging scheme and its application on regulation of surrounding emission sources[D].Ph.D.dissertation(in Chinese),Graduate Universityof Chinese Academy of Sciences,149pp.
程兴宏,徐祥德,丁国安,等.2009.MM5/WRF气象场模拟差异对CMAQ空气质量预报效果的影响[J].环境科学研究,22(12):1411-1419.Cheng Xinghong,Xu Xiangde,Ding Guoan,et al.2009.Differences in MM5 and WRF meteorological field simulations and impact on air quality forecasting by CMAQ Model[J].Research of Environmental Sciences(in Chinese),22(12):1411-1419.
丑纪范,郜吉东.1995.长期数值天气预报(2版)[M].北京:气象出版社,353pp.Chou Jifan,Gao Jidong.1995.Long-Term Numerical Weather Prediction(2nd ed.)(in Chinese)[M].Beijing:China Meteorological Press,353pp.
高怡,张美根.2014.2013年1月华北地区重雾霾过程及其成因的模拟分析[J].气候与环境研究,19(2):140-152.Gao Yi,Zhang Meigen.2014.Numerical simulation of a heavy fog-haze episode over the North China Plain in January 2013[J].Climatic and Environmental Research(in Chinese),19(2):140-152,doi:10.3878/j.issn.1006-9585.2014.13135.
Gilliam R C,Hogrefe C,Godowitch J M,et al.2015.Impact of inherent meteorology uncertainty on air quality model predictions[J].J.Geophys.Res.,120:12259-12280,doi:10.1002/2015JD023674.
Kalnay E.2003.Atmospheric Modeling,Data Assimilation and Predictability[M].The Edinburgh Building,New York:Cambridge University Press,341pp.
Li J,Wang Z,Zhuang G.et al.2012.Mixing of Asian mineral dust with anthropogenic pollutants over East Asia:A model case study of a superduststorm in March 2010[J].Atmospheric Chemistry and Physics,12(16):7591-7607,doi:10.5194/acp-12-7591-2012.
Lorenz E N.1963.Deterministic nonperiodic flow[J].J.Atmos.Sci.,20(2):130-141,doi:10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2.
Meng G,Carmichael G R,Saide P E,et al.2016.Response of winter fine particulate matter concentrations to emission and meteorology changes in North China[J].Atmospheric Chemistry and Physics,16(18):11837-11851,doi:10.5194/acp-2016-429.
Morss R E,Battisti D S.2004.Evaluating observing requirements for ENSO prediction:Experiments with an intermediate coupled model[J].J.Climate,17(16):3057-3073,doi:10.1175/1520-0442(2004)017<3057:EORFEP>2.0.CO;2.
穆穆,秦晓昊,周菲凡,等.2012.加强目标观测,服务防灾减灾[J].成都信息工程学院学报,27(1):20-26.Mu Mu,Qin Xiaohao,Zhou Feifan,et al.2012.Developing the adaptive observations,reducing the disasters[J].Journal of Chengdu University of Information Technology(in Chinese),27(1):20-26,doi:10.3969/j.issn.1671-1742.2012.01.002.
Mu M.2013.Methods,current status,and prospect of targeted observation[J].Science ChinaEarth Sciences,56(12):1997-2005,doi:10.1007/s11430-013-4727-x.
任万辉,苏枞枞,赵宏德.2010.城市环境空气污染预报研究进展[J].环境保护科学,36(3):9-11.RenWanhui,Su Congcong,Zhao Hongde.2010.Research progress of air pollution forecasting in urban area[J].Environmental Protection Science(in Chinese),36(3):9-11,doi:10.3969/j.issn.1004-6216.2010.03.004.
Riehl H,Haggard W H,Sanborn R W.1956.On the prediction of 24-hour hurricane motion[J].J.Meteor.,13(5):415-420,doi:10.1175/1520-0469(1956)013<0415:OTPOHH>2.0.CO;2.
Snyder C.1996.Summary of an informal workshop on adaptive observations and FASTEX[J].Bull.Amer.Meteor.Soc.,77(5):953-961,doi:10.1175/1520-0477-77.5.953.
隋珂珂,王自发,杨军,等.2007.北京PM10持续污染及与常规气象要素的关系[J].环境科学研究,20(6):77-82.Sui Keke,Wang Zifa,Yang Jun,et al.2007.Beijing persistent PM10 pollution and its relationship with general meteorological features[J].Research of Environmental Sciences(in Chinese),20(6):77-82.
唐晓,王自发,朱江,等.2010.蒙特卡罗不确定性分析在O3模拟中的初步应用[J].气候与环境研究,15(5):541-550.Tang Xiao,Wang Zifa,Zhu Jiang,et al.2010.Preliminary application of Monte Carlo uncertainty analysis in O3 simulation[J].Climatic and Environmental Research(in Chinese),15(5):541-550,doi:10.3878/j.issn.1006-9585.2010.05.02.
Tang X,Zhu J,Wang Z F,et al.2011.Improvement of ozone forecast over Beijing based on ensemble Kalman filter with simultaneous adjustment of initial conditions and emissions[J].Atmospheric Chemistry and Physics,11(24):12901-12916,doi:10.5194/acp-11-12901-2011.
唐孝炎,张远航,邵敏.2006.大气环境化学(2版)[M].北京:高等教育出版社,49-62.Tang Xiaoyan,Zhang Yuanhang,Shao Min.2006.Atmospheric Environmental Chemistry(2nd ed)(in Chinese)[M].Beijing:Higher Education Press,49-62.
佟彦超.2006.中国重点城市空气污染预报及其进展[J].中国环境监测,22(2):69-71.Tong Yanchao.2006.Air quality forecast and development in major cities of China[J].Environmental Monitoringin China(in Chinese),22(2):69-71,doi:10.3969/j.issn.1002-6002.2006.02.022.
王威,李杰,朱莉莉.2016.9·3阅兵期间京津冀及周边地区污染源减排贡献模拟分析[C]//2016中国环境科学学会学术年会论文集(第一卷).海口:中国环境科学学会,38-45.Wang Wei,Li Jie,Zhu Lili.2016.9·3simulation analysis of contribution of pollutants to emission reduction in Beijing-Tianjin-Hebeiregion and peripheral areas during parade[C]//Annual Conference of Chinese Society of Environmental Sciences(in Chinese).Haikou:Chinese Society for Environmental Sciences,38-45.
Wang Z,Maeda T,Hayashi M,et al.2001.A nested air quality prediction modeling system for urban and regional scales:Application for highozone episode in Taiwan[J].Water,Air,and Soil Pollution,130(1-4):391-396,doi:10.1023/A:1013833217916.
王哲,王自发,李杰,等.2014.气象-化学双向耦合模式(WRF-NAQPMS)研制及其在京津冀秋季重霾模拟中的应用[J].气候与环境研究,19(2):153-163.Wang Zhe,Wang Zifa,Li Jie,et al.2014.Development of a meteorology-chemistry two-way coupled numerical model(WRF-NAQPMS)and its application in a severe autumn haze simulation over the Beijing-Tianjin-Hebei area,China[J].Climatic and Environmental Research(in Chinese),19(2):153-163,doi:10.3878/j.issn.1006-9585.2014.13231.
王自发,谢付莹,王喜全,等.2006.嵌套网格空气质量预报模式系统的发展与应用[J].大气科学,30(5):778-790.Wang Zifa,XieFuying,Wang Xiquan,et al.2006.Development and application of Nested Air Quality Prediction Modeling System[J].Chinese Journal of Atmospheric Sciences(in Chinese),30(5):778-790,doi:10.3878/j.issn.1006-9895.2006.05.07.
吴其重,王自发,徐文帅,等.2010.多模式模拟评估奥运赛事期间可吸入颗粒物减排效果[J].环境科学学报,30(9):1739-1748.Wu Qizhong,Wang Zifa,Xu Wenshuai,et al.2010.Multi-model simulation of PM10 during the 2008 Beijing Olympic Games:Effectiveness of emission restrictions[J].Acta Scientiae Circumstantiae(in Chinese),30(9):1739-1748.
杨兴川,赵文吉,熊秋林,等.2017.2016年京津冀地区PM2.5时空分布特征及其与气象因素的关系[J].生态环境学报,26(10):1747-1754.Yang Xingchuan,Zhao Wenji,Xiong Qiulin,et al.2017.Spatio-temporal distribution of PM2.5 in Beijing-Tianjin-Hebei(BTH)area in 2016 and its relationship with meteorological factors[J].Ecology and Environment Sciences(in Chinese),26(10):1747-1754,doi:10.16258/j.cnki.1674-5906.2017.10.014.
周菲凡.2009.条件非线性最优扰动方法在台风目标观测中的应用研究[D].中国科学院大气物理研究所博士学位论文,136pp.Zhou Feifan.2009.Application of the optimal nonlinear perturbation method to typhoon target observation[D].Ph.D.dissertation(in Chinese),Institute of Atmospheric Physics,Chinese Academy of Sciences,136pp.
Zhou F F,Mu M.2012.The time and regime dependencies of sensitive areas for tropical cyclone prediction using the CNOP method[J].Advances in Atmospheric Sciences,29(4):705-716,doi:10.1007/s00376-012-1174-0.