1. 杭州市气象局, 浙江 杭州 310051; 2. 浙江省气象服务中心, 浙江 杭州 310017; 3. 浙江大学海洋学院, 浙江 舟山 316021; 4. 马里兰大学地理系, College ParkMD, United States 20472
Study on circulation classification based surface ozone concentration prediction model
LIANG Zhuo-ran1, GU Ting-ting2, YANG Xu-chao3, DU Rong-guang1, ZHONG Hong-lin4, Qi Bing1
1. Hangzhou Meteorological Bureau, Hangzhou 310051, China; 2. Zhejiang Meteorological Service Center, Hangzhou 310017, China; 3. Ocean College, Zhejiang University, Zhoushan 316021, China; 4. Department of Geographical Sciences, University of Maryland, College Park MD, 20742, United States
Abstract：In this study, a new surface ozone concentration level simulation model was developed by combining the Lamb-Jenkinson objective circulation classification method and the stepwise linear regression model, and successfully applied in Hangzhou. The influence of local meteorological factors and large-scale circulation factors, which are from large scale reanalysis data between 2011 and 2016, to the ozone concentration level are analysed first. Our results showed a strong seasonal trend of the surface ozone concentration in Hangzhou. Ozone concentration level was much higher during spring and summer, and frequently exceeded the national standard which caused ozone pollution events, especially in May. Local meteorological conditions had a significant impact on the ozone concentration level. Both solar radiation and daily maximum temperature are positively correlated to ozone concentration level, but the relative humidity and precipitation are negatively correlated to it. In addition, we also classified the local cyclonic circulation observations using Lamb-Jenkinson objective circulation classification method, and identified that different cyclonic circulation types had different impact to the ozone concentration. The anti-cyclonic circulation was the dominant type and accounted for 26.5% of all the cyclonic circulation in Hangzhou, while the circulation from northwest had the least frequency of 0.6%. Ozone pollution events happened most frequently (23.8%) under the south airflow controlled circulation condition, but had the lowest frequency under north airflow controlled circulation condition (3.7%). Our results proved that the performance of the ozone concentration level simulation model will improve greatly by considering the seasonal circulation types and the meteorological factors using the stepwise regression method, which could increase the correlation between model prediction and observations up to 0.87, and our new model also improves the simulation of the extreme high ozone concentration pollution events significantly, it successfully predicted 15ozone pollution events out of 24events that happened in 2016, with a high TS score of 52%.
Melkonyan A, Wanger P. Ozone and its projection in regard to climate change[J]. Atmospheric Environment, 2013,67:287-295.
[2]
Booker R, Muntifering R, McGrath M, et al. The ozone component of global change:potential effects on agricultural and horticultural plant yield, product quality and interactions with invasive species[J]. Journal of Integrative Plant Biology, 2009, 51:337-351.
[3]
Kharel K, Amgain L P. Assessing the impact of ambient ozone on growth and yield of crop at Rampur, Chitwan[J]. Journal of Agriculture and Environment, 2010,11:40-45.
Rai R, Agrawal M. Impact of tropospheric ozone on crop plants[J]. Proceeding of the National Academy of Sciences, India Section B:Biological Sciences, 2012,82(2):241-257.
[8]
Feng Z Z, Hu E Z, Wang X K, et al. Ground-level O3 pollution and its impacts on food crops in China:a review[J]. Environmental Pollution, 2015,199:42-48.
[9]
Xu X, Lin W, Wang T, et al. Long-term trend of surface ozone at a regional background station in eastern China 1991~2006:Enhanced variability[J]. Atmospheric Chemistry and Physics, 2008,8:2595-2607.
Zhang Y N, Xiang Y R, Chan L Y, et al. Procuring the regional urbanization and industrialization effect on ozone pollution in Pearl River Delta of Guangdong, China[J]. Atmospheric Environment, 2011,45(28):4898-4906.
Appel K W, Chemel C, Roselle S J, et al. Examination of the Community Multiscale Air Quality (CMAQ) model performance over the North American and European domains[J]. Atmospheric Environment, 2012,53:142-155.
[17]
Byun D, Schere K L. Review of the governing equations, computational algorithms, and other components of the models-3Community Multiscale Air Quality (CMAQ) modeling system[J]. Applied Mechanics Reviews, 2006,59(2):51-77.
Camalier L, Cox W, Dolwick P. The effects of meteorology on ozone in urban areas and their use in assessing ozone trends[J]. Atmospheric Environment, 2007,41:7127-7137.
Barrero M A, Grimalt, J O, Canton L. Prediction of daily ozone concentration maxima in the urban atmosphere[J]. Chemometrics and Intelligent Laboratory Systems, 2006,80:67-76.
[26]
Cobourn W G. Accuracy and reliability of an automated air quality forecast system for ozone in seven Kentucky metropolitan areas[J]. Atmospheric Environment, 2007,41:5863-5875.
[27]
Hooyberghs J, Mensink C, Dumont G, et al. A neural network forecast for daily average PM10 concentrations in Belgium[J]. Atmospheric Environment, 2005,39:3279-3289.
Cobourn W G, Dolcine L, French M, et al. A comparison of nonlinear regression and neural network models for ground-level ozone forecasting[J]. Journal of the Air & Waste Management Association, 2000,50:1999-2009.
[30]
Wilby R L, Wigley T. Downscaling general circulation model output:a review of methods and limitations[J]. Progress in Physical Geography, 1997,21:530-548.
[31]
Schjoldager J. Ambient ozone measurements in Norway 1975-1979[J]. JAPCA, 1981,31(11):1187-1191.
[32]
Van Dop H, Dentonkelaar J F, Briffa F E J. A modeling study of atmospheric transport and photochemistry in the mixed layer during anticyclonic episodes in europe meteorology and air trajectories[J]. J. Clim. Appl. Meteorol., 1987,26(10):1305-1316.
[33]
Russo A, Trigo R M, Martins H, et al. NO2, PM10 and O3 urban concentrations and its association with circulation weather types in Portugal[J]. Atmospheric Environment, 2014,89:768-785.
Huth R, Kliegrova S, Metelka L. Non-linearity in statistical downscaling:does it bring an improvement for daily temperature in Europe?[J]. International Journal of Climatology, 2008,28:465-477.
[41]
Huth R, Beck C, Philipp A, et al. Classifications of atmospheric circulation patterns:recent advances and applications (in Trends and Directions in Climate Research)[J]. Annals of the New York Academy of Sciences, 2008,1146:105-152.
[42]
Demuzere M, Nicole P M. A new method to estimate air-quality levels using a synoptic-regression approach. Part I:Present-day O3 and PM10 analysis[J]. Atmospheric Environment, 2010,44:1341-1355.
Jones P D, Hulme M, Briffa K R. A comparison of Lamb circulation types with an objective classification scheme[J]. International Journal of Climatology, 1993,13:655-663.
