本文应用WRF-Chem(Weather Research and Forecasting—Chemistry)模式研究中国东部地区气溶胶及其部分组分(硫酸盐、硝酸盐和黑碳气溶胶)在天气尺度下的辐射强迫和对地面气温的影响。5个无明显降水时间段(2006年8月23～25日、2008年11月10～12日、2008年12月16～18日、2009年1月15～17日和2009年4月27～29日)的模拟显示,气溶胶浓度呈现显著的白天低,夜间高的日变化特征,且北方区域(29.8°～42.6°N,110.2°～120.3°E)平均PM2.5近地面浓度(40～80 μg m-3)高于南方区域(22.3°～29.9°N,109.7°～120.2°E,30～47 μg m-3)。气溶胶对地面2 m温度(地面气温)有明显的降温效果,在早上08:00(北京时,下同)和下午17:00左右最为显著,最高可降低约0.2～1 K,同时气溶胶的参与改善了模式对地面气温的模拟。本文还通过对2006年8月23～25日一次个例的模拟,定量分析了气溶胶及其部分组分(硫酸盐、硝酸盐和黑碳气溶胶)的总天气效应(直接效应+间接效应)、直接效应和间接效应分别对到达地面的短波辐射和地面气温的影响。北方区域平均气溶胶直接效应所造成的短波辐射强迫要高于南方区域,分别为-11.3 W m-2和-5.8 W m-2,导致地面气温分别降低了0.074 K和0.039 K。南方区域平均气溶胶间接效应所产的短波辐射强迫高于北方区域,分别为-14.4 W m-2和-12.4 W m-2,引起的地面气温的改变分别为-0.094 K和-0.035 K。对于气溶胶组分,硫酸盐气溶胶的直接效应和间接效应的作用相当,其总效应在北方和南方区域平均短波辐射强迫分别为-7.0 W m-2和-10.5 W m-2,对地面气温的影响为-0.062 K和-0.074 K,而硝酸盐气溶胶的作用略小。黑碳气溶胶使得北方和南方区域平均到达地表的太阳短波辐射分别减少了6.5 W m-2和5.8 W m-2,而地表气温则分别增加了0.053 K和0.017 K,相比于间接效应,黑碳气溶胶的直接效应的影响更加显著
References
[1]
Bond T, Doherty S, Fahey D, et al. 2013. Bounding the role of black carbon in the climate system: A scientific assessment [J]. J. Geophys. Res., 118 (11): 5380-5552.
[2]
蔡子颖, 韩素芹, 黄鹤, 等. 2011. 天津夏季黑碳气溶胶及其吸收特性的观测研究 [J]. 中国环境科学, 31 (5): 719-723. Cai Ziying, Han Suqin, Huang He, et al. 2011. Observational study on black carbon aerosols and their absorption properties in summer in Tianjin [J]. China Environmental Science (in Chinese), 31 (5): 719-723.
[3]
Chapman E G, Gustafson W I, Easter R C, et al. 2009. Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources [J]. Atmos. Chem. Phys., 9 (3): 945-964.
[4]
Chen F, Dudhia J. 2001. Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity [J]. Mon. Wea. Rev., 129 (4): 569-585.
[5]
Ek M B, Mitchell K E, Lin Y, et al. 2003. Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model [J]. J. Geophys. Res., 108 (D22), doi:10.1029/2002JD003296.
[6]
Fahey K M, Pandis S N. 2001. Optimizing model performance: Variable size resolution in cloud chemistry modeling [J]. Atmos. Environ., 35 (26): 4471-4478.
[7]
Fast J D, Gustafson W I Jr, Easter R C, et al. 2006. Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model [J]. J. Geophys. Res., 111 (D21), doi:10.1029/2005JD006721.
[8]
Giorgi F, Bi X Q, Qian Y. 2002. Direct radiative forcing and regional climatic effects of anthropogenic aerosols over East Asia: A regional coupled climate-chemistry/aerosol model study [J]. J. Geophys. Res., 107 (D20), doi:10.1029/2001JD001066.
[9]
Grell G A, Dévényi D. 2002. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques [J]. Geophys. Res. Lett., 29 (14): 38-1-38-4.
[10]
Grell G A, Peckham S E, Schmitz R, et al. 2005. Fully coupled “online” chemistry within the WRF model [J]. Atmos. Environ., 39 (37): 6957-6975.
[11]
Guenther A, Zimmerman P, Wildermuth M. 1994. Natural volatile organic compound emission rate estimates for US woodland landscapes [J]. Atmos. Environ., 28 (6): 1197-1210.
[12]
Guenther A B, Zimmerman P R, Harley P C, et al. 1993. Isoprene and monoterpene emission rate variability-model evaluations and sensitivity analyses [J]. J. Geophys. Res.-Atmospheres, 98 (D7): 12609-12617.
[13]
Gustafson W I, Chapman E G, Ghan S J, et al. 2007. Impact on modeled cloud characteristics due to simplified treatment of uniform cloud condensation nuclei during NEAQS 2004 [J]. Geophys. Res. Lett., 34 (19), doi:10.1029/2007GL030021.
[14]
Highwood E J, Kinnersley R P. 2006. When smoke gets in our eyes: The multiple impacts of atmospheric black carbon on climate, air quality and health [J]. Environ. Inter., 32 (4): 560-566.
[15]
Hong S Y, Noh Y, Dudhia J. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes [J]. Mon. Wea. Rev., 134 (9): 2318-2341.
[16]
Hou B, Zhuang G S, Zhang R, et al. 2011. The implication of carbonaceous aerosol to the formation of haze: Revealed from the characteristics and sources of OC/EC over a mega-city in China [J]. J. Hazard. Mater., 190 (1-3): 529-536.
[17]
IPCC. 2007. The Physical Science Basis of Climate Change: Changes in Atmospheric Constituents and in Radiative Forcing [M]. New York: Cambridge University Press.
[18]
Jacobson M Z. 2001. Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols [J]. Nature, 409 (6821): 695-697. Jia X C, Guo X L. 2012. Impacts of secondary aerosols on a persistent fog event in northern China [J]. Atmos. Oceanic Sci. Lett., 5 (5): 401-407.
[19]
Kristjánsson J E. 2002. Studies of the aerosol indirect effect from sulfate and black carbon aerosols [J]. J. Geophys. Res., 107 (D15), doi:10.1029/2001JD000887.
[20]
Li S, Wang T J, Zhuang B L, et al. 2009. Indirect radiative forcing and climatic effect of the anthropogenic nitrate aerosol on regional climate of China [J]. Adv. Atmos. Sci., 26 (3): 543-552.
[21]
李杨, 曹军骥, 张小曳, 等. 2005. 2003 年秋季西安大气中黑碳气溶胶的演化特征及其来源解析 [J]. 气候与环境研究, 10 (2): 229-237. Li Yang, Cao Junji, Zhang Xiaoye, et al. 2005. The variability and source apportionment of black carbon aerosol in Xi\'an atmosphere during the autumn of 2003 [J]. Climatic and Environmental Research (in Chinese), 10(2): 229-237.
[22]
Liao H, Seinfeld J H. 1998. Effect of clouds on direct aerosol radiative forcing of climate [J]. J. Geophys. Res., 103 (D4): 3781-3788.
[23]
Liao H, Seinfeld J H, Adams P J, et al. 2004. Global radiative forcing of coupled tropospheric ozone and aerosols in a unified general circulation model [J]. J. Geophys. Res., 109 (D24), doi:10.1029/2003JD004456.
[24]
Lin Y L, Farley R D, Orville H D. 1983. Bulk parameterization of the snow field in a cloud model [J]. J. Climate Appl. Meteor., 22 (6): 1065-1092.
[25]
Matsui H, Koike M, Kondo Y, et al. 2009. Spatial and temporal variations of aerosols around Beijing in summer 2006: Model evaluation and source apportionment [J]. J. Geophys. Res., 114, doi:10.1029/2008JD010906.
[26]
Mlawer E J, Taubman S J, Brown P D, et al. 1997. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave [J]. J. Geophys. Res., 102 (D14): 16663-16682.
[27]
Morin S, Sander R, Savarino J. 2011. Simulation of the diurnal variations of the oxygen isotope anomaly (△17O) of reactive atmospheric species [J]. Atmos. Chem. Phys., 11 (8): 3653-3671.
[28]
Pérez C, Nickovic S, Pejanovic G, et al. 2006. Interactive dust-radiation modeling: A step to improve weather forecasts [J]. J. Geophys. Res., 111 (D16), doi:10.1029/2005JD006717.
[29]
Rodwell M J, Jung T. 2008. Understanding the local and global impacts of model physics changes: An aerosol example [J]. Quart. J. Roy. Meteor. Soc., 134 (635): 147渹椭挱?匹挷椮???放瑔瑡????????????ぺ??????戠牅?婯桲慩渠杓?夠??圠敡湬?堠′夰?‵?愠湓杩???????のㄠは慦??卬楩浭畡汴慥琠楲湥杳?捯桮敳浥椠獴瑯爠祡?慲敯牳潯獬漠汤?捲汥潣畴搠??牤愠摩楮慤瑩楲潥湣?挠汥楦浦慥瑣整?映敷敩摴扨愠捡步獲?潳癯敬爠?瑲桡敮?捰潯湲瑴椭渠敲湡瑤慩污?啩??匠??畤獥楬渠杛?瑝栮攠?漮渠汇楥湯数?捹潳甮瀠汒敥摳?圬攠愱琱栰攠爨?刲攩猬攠慤牯捩栺??漮爱攰挲愹猯琲椰渰朴??漰搰攵氰′眹椮琼桢?挾桔敡浹楬獯瑲爠祋??圮删???栱攮洠??孭?嵡???瑩浮潧猠???湴癩楰牬潥渠???????㈠???????????????扭牡?婣桥愠湩杮?奡??偩慮湧?奥??坩慡湧杲????敛瑊?愮氠??㈠ぇ?は扰??坳刮???桳攮洬????删?????渠挷漱爸瀳漭爷愱琹椲漮渼?潲显?慡湮?愠敃爠潅献漠氲‰洰漴搮甠汁攠?楯湤瑥潬?坮剧???桵敤浹?慯湮搠?楨瑥猠?楬湩業瑡楴慥氠?慭灰灡汣楴捳愠瑯楦漠湢?瑡潣?琠档敡?呢敯确?兡卥?はびは?敳瀠楛獊潝搮攠?嬮?嵇??????攮漠灒桥祳献??刱攰猹????ㄩ?????????搱漰椲?????????日????????????g Y, Che H Z, Ma J Z, et al. 2009. Aerosol radiative forcing under clear, hazy, foggy, and dusty weather conditions over Beijing, China [J]. Geophys. Res. Lett., 36, doi:10.1029/2009GL037181.
[30]
Wild O, Zhu X, Prather M J. 2000. Fast-j: Accurate simulation of in- and below-cloud photolysis in tropospheric chemical models [J]. J. Atmos. Chem., 37 (3): 245-282.
[31]
Wu Q Z, Wang Z F, Gbaguidi A, et al. 2011. A numerical study of contributions to air pollution in Beijing during CAREBeijing-2006 [J]. Atmos. Chem. Phys., 11 (12): 5997-6011.
[32]
Xu Y, Gao X J, Shen Y, et al. 2009. A daily temperature dataset over China and its application in validating a RCM simulation [J]. Adv. Atmos. Sci., 26 (4): 763-772.
[33]
Zaveri R A, Peters L K. 1999. A new lumped structure photochemical mechanism for large-scale applications [J]. J. Geophys. Res., 104 (D23): 30387-30415.
[34]
Zaveri R A, Easter R C, Fast J D, et al. 2008. Model for simulating aerosol interactions and chemistry (MOSAIC) [J]. J. Geophys. Res., 113 (D13), doi:10.1029/2007JD008782.
[35]
Zhang T, Cao J J, Tie X X, et al. 2011. Water-soluble ions in atmospheric aerosols measured in Xi\'an, China: Seasonal variations and sources [J]. Atmos. Res., 102 (1-2): 110-119.
[36]
Zhang Y. 2008. Online-coupled meteorology and chemistry models: History, current status, and outlook [J]. Atmos. Chem. Phys., 8 (11): 2895-2932.
[37]
Zhang Y, Liao H, Zhu K F, et al. 2009. Role of black carbon-induced changes in snow albedo in predictions of temperature and precipitation during a snowstorm [J]. Atmos. Ocea
[38]
Ackerman A S, Toon O B, Stevens D E, et al. 2000. Reduction of tropical cloudiness by soot [J]. Science, 288 (5468): 1042-1047.
