ISSN 1004-4965

CN 44-1326/P

用微信扫描二维码

分享至好友和朋友圈

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

夏季硫酸盐和黑碳气溶胶对中国云特性的影响

尚晶晶 廖宏 符瑜 杨青

尚晶晶, 廖宏, 符瑜, 杨青. 夏季硫酸盐和黑碳气溶胶对中国云特性的影响[J]. 热带气象学报, 2017, 33(4): 451-466. doi: 10.16032/j.issn.1004-4965.2017.04.003
引用本文: 尚晶晶, 廖宏, 符瑜, 杨青. 夏季硫酸盐和黑碳气溶胶对中国云特性的影响[J]. 热带气象学报, 2017, 33(4): 451-466. doi: 10.16032/j.issn.1004-4965.2017.04.003
Jing-jing SHANG, Hong LIAO, Yu FU, Qing YANG. THE IMPACT OF SULFATE AND BLACK CARBON AEROSOLS ON SUMMERTIME CLOUD PROPERTIES IN CHINA[J]. Journal of Tropical Meteorology, 2017, 33(4): 451-466. doi: 10.16032/j.issn.1004-4965.2017.04.003
Citation: Jing-jing SHANG, Hong LIAO, Yu FU, Qing YANG. THE IMPACT OF SULFATE AND BLACK CARBON AEROSOLS ON SUMMERTIME CLOUD PROPERTIES IN CHINA[J]. Journal of Tropical Meteorology, 2017, 33(4): 451-466. doi: 10.16032/j.issn.1004-4965.2017.04.003

夏季硫酸盐和黑碳气溶胶对中国云特性的影响

doi: 10.16032/j.issn.1004-4965.2017.04.003
基金项目: 

国家重点基础研究发展计划(973计划) 2014CB441200

详细信息
    通讯作者:

    廖宏,女,四川省人,研究员,博士,主要从事大气成分变化与气候变化之间的相互作用。E-mail:hongliao@mail.iap.ac.cn

  • 中图分类号: X513

THE IMPACT OF SULFATE AND BLACK CARBON AEROSOLS ON SUMMERTIME CLOUD PROPERTIES IN CHINA

  • 摘要: 利用WRF-Chem(Weather Research and Forecasting model coupled with Chemistry)模式研究2006年8月1日—9月1日中国区域硫酸盐和黑碳气溶胶对云特性的影响。模式验证利用了卫星和地面观测的气象要素、化学物质浓度、气溶胶光学特性和云微物理特性。模式性能评估表明该模式能较好地抓住气象要素(温度、降水、相对湿度和风速)的量级和空间分布特征。通过与地面观测和MODIS卫星数据对比发现,尽管模式模拟还存在偏差,但还是能较好模拟出气溶胶物种的地表浓度、气溶胶光学厚度(AOD)、云光学厚度(COD)、云量(CLDF)、云顶云滴有效半径(CER)和云水路径(LWP)。通过两个敏感性试验(分别增加二氧化硫和黑碳排放量至控制试验排放的3倍)与控制试验的对比发现硫酸盐比黑碳更易成为云凝结核,在中国东部云顶云滴数浓度和其它云特性参数对二氧化硫排放增加的响应均从北向南呈递增,这与地面湿度分布有关。云滴有效半径对硫酸盐气溶胶的响应符合气溶胶第一间接效应的定义,即硫酸盐气溶胶增多,云滴数浓度增加,云滴有效半径减少,但是对黑碳气溶胶的响应在各区域不尽相同。还发现黑碳对云量的影响远大于硫酸盐,主要原因是由于黑碳气溶胶直接辐射效应(对太阳光的吸收)导致的云的“燃烧”作用。

     

  • 图  1  2006年SO2(a,单位:ton S/year/grid)和BC(b,单位:ton C/year/grid)排放的空间分布

    灰色扇形区域为模式模拟研究区域。4个黑框表示4个重点关注子区域:华北平原(NCP,110~120 °E,34~40 °N)、中国中部(MC,110~120 °E,28~34 °N)、中国南方(SC,108~115 °E,21~28 °N)和中国东海(ECS,127~130 °E,23~33 °N)。

    图  2  2006年8月模拟和观测(重叠的彩色点)的平均地表温度(a,单位:℃)、降水(b,单位:mm/d)和相对湿度(c,单位:%)

    图  3  CTL试验模拟结果(a、c)、NCEP FNL数据(b、d)的地面和850 hPa高度月平均风场空间分布

    图  4  CTL试验模拟的2006年8月地表气溶胶浓度的月均值

    单位:μg/m3。a.细颗粒物;b.硫酸盐;c.硝酸盐;d.铵盐;e.有机碳;g.黑碳。

    图  5  模拟和观测的气溶胶(硫酸盐、硝酸盐、有机碳、黑碳)浓度(单位:μg/m3)2006年8月月均值的散点分布

    点线是1:1线;实线是线性拟合线。R是模拟值与观测值的相关系数。

    图  6  CTL试验模拟值(a)和MODIS观测值(b)的2006年8月平均AOD的空间分布

    图  7  2006年8月平均的CTL试验模拟(左)和MODIS观测(右)的云光学厚度(COD)(a、b)、云量(CLDF)(c、d)、云水路径(LWP,单位:g/m2)(e、f)和云顶云滴有效半径(CER,单位:μm)(g、h)的空间分布

    图  8  各种气溶胶的地表浓度对增强的SO2排放(3SO2,绿色)和黑碳排放(3BC,紫色)的响应单位:μg/m3

    Δ表示3SO2或3BC试验与控制试验之差。a~f分别是PM2.5、硫酸盐、硝酸盐、铵盐、有机碳和黑碳的响应。图上方的μCTL是CTL试验中各种气溶胶浓度在此区域的平均值。

    图  9  975 hPa处的积聚模态气溶胶数浓度(Nacc,单位:cm-3)(a)和过饱和度为0.1%的云凝结核数浓度(Nccn,单位:cm-3)(b)及气溶胶光学厚度(AOD)对增强的SO2排放(3SO2,绿色)和黑碳排放(3BC,紫色)的响应(c)

    图  10  云顶云滴的数浓度(Nd,单位:cm-3)(a)和有效半径(CER,单位:μm)(b)对增强的SO2排放(3SO2,绿色)和黑碳排放(3BC,紫色)的响应

    μCTL是指Nd(或CER)在CTL试验中选定的4个研究区域(NCP、MC、SC和ECS)的平均值。标在柱上的数值是气溶胶-云敏感因子,ΔY/(Yln(N_ccn)),其中Y是指云特性(Nd或CER)。

    图  11  云宏观物理特性的云水路径(LWP,单位:g/m3)(a)、云光学厚度(COD)(b)和云量(CLDF,单位:%)(c)对增强的SO2排放(3SO2,绿色)和黑碳排放(3BC,紫色)的响应

    图  12  CTL、3SO2、3BC试验中获得的4个区域气溶胶光学厚度(AOD)与云滴有效半径(CER,单位:μm)的关系

    a. NCP;b.MC;c. SC;d. ECS(横坐标与其它图的坐标不同)。

    表  1  模式的主要物理和化学方案的设置

    物理化学过程 参数化方案 参考文献
    长波辐射方案(Long-wave radiation) RRTM Mlawer等[50]
    短波辐射方案(Short-wave radiation) Goddard Chou等[51]
    陆地模式(Land-surface model) Noah Chen等[52]
    边界层方案(Boundary layer scheme) YSU Hong等[53]
    积云参数(Cumulus parameterization) New Grell scheme(G3) Grell等[54]
    云微物理过程(Cloud microphysics) Morrison Morrison等[55-56]
    光化学方案(Photolysis scheme) Fast-J Wild等[57]
    化学方案(Chemistry option) CBM-Z Zaveri等[58]
    气溶胶方案(Aerosol option) MOZAIC Zaveri等[47]
    下载: 导出CSV

    表  2  2006年气溶胶前体物和气溶胶的人为排放总量

    污染物 中国(90~135 °E, 20~54 °N) 中国东部(110~120 °E, 20~45 °N)
    NOx (Tg N yr-1) 7.2 4.4
    CO (Tg CO yr-1) 178.4 115.2
    SO2 (Tg S yr-1) 16.3 10.4
    NH3 (Tg N yr-1) 11.2 7.2
    BC (Tg C yr-1) 1.9 1.2
    OC (Tg C yr-1) 3.5 1.9
    下载: 导出CSV

    表  3  不同区域(NCP、MC和SC)的观测和不同模拟试验(CTL、3SO2和3BC)获得的地表温度、降水、相对湿度及地表风速的月平均值和标准偏差

    变量 观测/模拟 NCP MC SC
    平均(mean) 标准偏差(std) 平均(mean) 标准偏差(std) 平均(mean) 标准偏差(std)
    温度/℃ 观测 25.6 1.4 28.9 1.1 28.4 0.7
    CTL 24.4 2.6 26.7 1.1 26.1 1.2
    3SO2 24.5 2.6 26.7 1.1 26.0 1.2
    3BC 24.7 2.6 26.9 1.0 26.2 1.1
    降水/(mm/d) 观测 5.9 2.9 4.0 1.6 7.0 4.1
    CTL 1.1 1.0 0.9 0.3 1.9 1.2
    3SO2 1.1 1.0 0.6 0.2 1.9 1.4
    3BC 1.0 0.7 0.8 0.4 2.2 1.9
    相对湿度/% 观测 78.1 4.8 73.5 4.7 76.4 4.7
    CTL 61.6 8.7 67.0 6.2 79.0 4.5
    3SO2 62.1 8.6 68.4 7.1 79.7 2.9
    3BC 59.6 8.6 67.4 7.0 81.1 5.0
    地表风速/(m/s) 观测 1.7 0.5 1.9 0.5 1.8 0.7
    CTL 5.0 0.4 4.8 0.3 4.2 0.4
    3SO2 5.2 0.5 4.7 0.4 4.0 0.4
    3BC 5.2 0.4 4.5 0.3 3.8 0.3
    下载: 导出CSV

    表  4  控制试验(CTL)获得的气象要素、气溶胶浓度、气溶胶光学特性和云特性在中国区域(93~130 °E,20~53 °N)内与观测值比较的统计量

    变量 数据集 观测 模拟 平均偏差(MB) 归一化平均偏差(NMB)/%
    温度/℃ 站点 23.7 21.8 -1.9 -8.1
    降水/(mm/d) 站点 3.6 2.2 -1.4 -39.3
    相对湿度/% 站点 67.9 59.0 -8.9 -13.0
    地表风速/(m/s) FNL 1.1 2.3 1.2 107.4
    硝酸盐浓度/(μg/m3) 站点 4.9 9.0 4.1 85.1
    硫酸盐浓度/(μg/m3) 站点 16.2 8.4 -7.8 -48.5
    黑碳浓度/(μg/m3) 站点 2.6 2.5 -0.1 -2.2
    有机碳浓度/(μg/m3) 站点 9.3 4.5 -4.8 -54.0
    气溶胶光学厚度 MODIS 0.29 0.27 -0.02 -8.5
    云量/% MODIS 14.5 3.5 -11.0 -75.8
    云光学厚度 MODIS 0.17 0.33 0.16 91.2
    云水路径/(g/m2) MODIS 127.3 77.6 -49.7 -39.1
    云滴有效半径/ m MODIS 14.1 11.8 -2.2 -16.2
    下载: 导出CSV

    表  5  观测和模拟的中国地区14个观测站点2006年8月平均的硫酸盐、硝酸盐、有机碳和黑碳的地面浓度  单位:μg/m3。观测值来源于Zhang等[59],模拟值是CTL试验结果。

    站点 硫酸盐 硫酸盐 有机碳 黑碳
    观测 模拟 观测 模拟 观测 模拟 观测 模拟
    太阳山 19.7 14.0 3.3 16.6 8.4 6.9 1.6 3.8
    成都 25.2 12.4 7.8 6.8 21.9 8.4 6.3 3.8
    大连 13.4 6.9 7.3 8.2 8.8 3.7 2.6 2.2
    拉萨 1.3 1.7 1.1 0.1 11.3 0.3 2.0 0.1
    南宁 12.3 7.6 2.0 6.8 9.4 3.7 2.3 1.5
    番禺 11.3 8.2 4.0 12.0 9.3 3.3 3.3 1.4
    西安 34.5 8.6 9.7 3.6 3.0 4.4 1.0 2.9
    郑州 22.7 12.3 9.1 18.5 9.6 8.5 3.1 5.8
    古城 17.8 4.9 7.3 7.4 9.7 3.2 4.2 2.1
    金沙 14.3 12.3 2.0 14.2 7.3 6.2 1.4 3.5
    临安 12.3 9.5 3.6 12.0 8.2 4.0 2.4 2.4
    龙凤山 10.4 2.0 1.5 2.1 5.3 1.7 0.9 0.8
    下载: 导出CSV

    表  6  以前文献中给出的WRF-Chem模式和MODIS卫星云特性数据对比

    云参数 区域 时间/年 模式参数方案 平均偏差(MB) 归一化平均偏差(NMB,%) 相关系数 参考文献
    云光学厚度
    (COD)
    中国 2005 AR-G00 -8.1 -48.4 0.8 Zhang等[69]
    2005 FN Series -6.6 -39.6 0.8
    2010 AR-G00 -6.4 -40.1 0.1
    2010 FN Series -4.6 -29.3 0.8
    美国 2001 -11.9 -74.7 Zhang等[70]
    云量
    (CLDF)/%
    中国 2005 AR-G00 -0.1 10.4 0.8 Zhang等[69]
    2005 FN Series -0.1 -9.7 0.8
    2010 AR-G00 -0.1 -8.5 0.8
    2010 FN Series -0.1 -7.8 0.8
    美国 2001 -3.1 -5.6 Zhang等[70]
    云水含量
    (LWP)/(g/m2
    中国 2005 AR-G00 -61.9 -54.4 0.9 Zhang等[69]
    2005 FN Series -49.6 -43.7 0.8
    2010 AR-G00 -49.5 -47.3 0.9
    2010 FN Series -34.8 -33.3 0.8
    美国 2001 -23.5 -67.7 Zhang等[70]
    下载: 导出CSV
  • [1] CHARLSON R J, SCHWARTZ S E, HALES J M, et al. Climate forcing by anthropogenic aerosols[J]. Sci, 1992, 255(5043): 423-430. doi: 10.1126/science.255.5043.423
    [2] HAYWOOD J, BOUCHER O. Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: Areview[J]. Rev Geophys, 2000, 38(4): 513-543. doi: 10.1029/1999RG000078
    [3] MYHRE G, BERGLEN T F, HOYLE C R, et al. Modelled radiative forcing of the direct aerosol effect with multi-observation evaluation[J]. Atmosp Chemis Phy, 2009, 9(4):1365-1392. doi: 10.5194/acp-9-1365-2009
    [4] TWOMEY S. Pollution and the planetary albedo[J]. Atmos Environm, 2007, 8(12):1251-1256. http://www.sciencedirect.com/science/article/pii/0004698174900043
    [5] TWOMEY S. Aerosols, clouds and radiation[J]. Atmos Environm Part a-General Top, 1991, 25(11): 2435-2442. doi: 10.1016/0960-1686(91)90159-5
    [6] JONES A, ROBERTS D L, SLINGO A. A climate model study of indirect radiative forcing by anthropogenic sulphate aerosols[J]. Nature, 1994, 370(6489): 450-453. doi: 10.1038/370450a0
    [7] ALBRECHT B A. Aerosols, cloud microphysics, and fractional cloudiness[J]. Sci, 1989, 245(4923): 1227-1230. doi: 10.1126/science.245.4923.1227
    [8] TIAN H, MA J, LI W J, et al. Simulation of forcing of sulfate aerosol on direct radiation and its climate effect over middle and eastern China[J]. J Appll Metrolog Sci, 2005, 16(1): 322-333. http://en.cnki.com.cn/Article_en/CJFDTOTAL-YYQX200503006.htm
    [9] WU J, FU C, XU Y, XU Y et al. simulation of direct effects of black carbon aerosol on temperature and hydrological cycle in asia by a regional climate model[J]. Meteorol Atmos Phy, 2008, 100(1): 179-193. doi: 10.1007/s00703-008-0302-y
    [10] ZHUANG B L, JIANG F, WANG T J, et al. Investigation on the direct radiative effect of fossil fuel black-carbon aerosol over China[J]. Theor Appl Climatol, 2010, 104(3): 301-312. doi: 10.1007/s00704-010-0341-4
    [11] HAN Z W, XIONG Z, LI J W. Direct climatic effect of aerosols and interdecadal variations over East Asia investigated by a regional climate/chemistry model[J]. Atmos Oceanic Sci Lett, 2011, 4(6): 299-303. doi: 10.1080/16742834.2011.11446947
    [12] XIA X G. A critical assessment of direct radiative effects of different aerosol types on surface global radiation and its components[J]. J Quantit SpectroscRad Transf, 2014, 149(1): 72-80. http://www.sciencedirect.com/science/article/pii/S0022407314003264
    [13] IPCC. Climate change 2013: The physical science basis[M]. Cambridge: Cambridge Univ Press, 2013.
    [14] LOHMANN U, FEICHTER J. Global indirect aerosol effects: A review[J]. Atmos Chem Phy, 2005, 5(3): 715-737. doi: 10.5194/acp-5-715-2005
    [15] MAUGER G S, NORRIS J R. Meteorological bias in satellite estimates of aerosol-cloud relationships[J]. Geophys Res Lett, 2007, 34(16): L07815.
    [16] GAO Y, ZHAO C, LIU X H, et al. WRF-Chem simulations of aerosols and anthropogenic aerosol radiative forcing in East Asia[J]. Atmos Environm, 2014, 92(1): 250-266. http://www.sciencedirect.com/science/article/pii/S1352231014003100
    [17] CHANG W Y, LIAO H, WANG H J. Climate responses to direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and long-lived greenhouse gases in eastern China over 1951-2000[J]. Adv Atmos Sci, 2009, 26(4): 748-762. doi: 10.1007/s00376-009-9032-4
    [18] GUO L, HIGHWOOD E J, SHAFFREY L C, et al. The effect of regional changes in anthropogenic aerosols on rainfall of the East Asian Summer Monsoon[J]. Atmos Chem Phy, 2013, 13(3): 1521-1534. doi: 10.5194/acp-13-1521-2013
    [19] MENON S, HANSEN J, NAZARENKO L, et al. Climate effects of black carbon aerosols in China and India[J]. Sci, 2002, 297(5590): 2250-2253. doi: 10.1126/science.1075159
    [20] WU L T, SU H, JIANG H. Regional simulation of aerosol impacts on precipitation during the East Asian summer monsoon[J]. J Geophys Res-Atmos, 2013, 118(12): 6454-6467. doi: 10.1002/jgrd.50527
    [21] 沈新勇, 黄文彦, 陈宏波.气溶胶对东亚夏季风指数和爆发的影响及其机理分析[J].热带气象学报, 2015, 31(6): 733-743. http://www.itmm.gov.cn/rdqxxb/ch/reader/view_abstract.aspx?file_no=20150602&flag=1
    [22] 邓洁淳, 徐海明, 马红云, 等.中国东部地区人为气溶胶影响东亚夏季风爆发和推进过程的数值模拟[J].热带气象学报, 2014, 30(5): 952-962. http://www.itmm.gov.cn/rdqxxb/ch/reader/view_abstract.aspx?file_no=20140515&flag=1
    [23] TANG J, WANG P C, MICKLEY J, et al. Positive relationship between liquid cloud droplet effective radius and aerosol optical depth over Eastern China from satellite data[J]. Atmos Environ, 2014, 84(1): 244-253. http://www.sciencedirect.com/science/article/pii/S135223101300633X
    [24] 石睿, 王体健, 李树, 等.东亚夏季气溶胶-云-降水分布特征及其相互影响的资料分析[J].大气科学, 2015, 39(1): 12-22. doi: 10.3878/j.issn.1006-9895.1404.13276
    [25] 邓育鹏, 董晓波, 吕峰, 等.河北省降水性层状云宏微观物理特征[J].气象与环境学报, 2013, 29(3):29-34. http://www.cnki.com.cn/Article/CJFDTOTAL-LNQX201303006.htm
    [26] 李军霞, 银燕, 任刚, 等.山西云凝结核时空分布特征观测[J].中国环境科学, 2015, 35(8):2261-2271. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGHJ201508004.htm
    [27] 封秋娟, 李培仁, 丁建芳, 等. 山西地区一次层状云降水过程的微观特征观测分析[J]. 2013, 36(5): 537-545. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=njqx201305003&dbname=CJFD&dbcode=CJFQ
    [28] CHUANG C C, PENNER J E. Effects of anthropogenic sulfate on cloud drop nucleation and optical properties[J]. Tellus B, 1995, 47(5): 566-577. doi: 10.3402/tellusb.v47i5.16072
    [29] QIAN Y, GIORGI F. Interactive coupling of regional climate and sulfate aerosol models over eastern Asia[J]. J Geophys Res-Atmos, 1999, 104(D6): 6477-6499. doi: 10.1029/98JD02347
    [30] GIORGI F, BI X, QIAN Y. Indirect vsdirect effects of anthropogenic sulfate on the climate of East Asia as simulated with a regional coupled climate-chemistry/aerosol model[J]. Clim Change, 2003, 58(3): 345-376. doi: 10.1023/A:1023946010350
    [31] CHEN Y, YIN Y, XIAO H, et al. A numerical investigation of the impacts of anthropogenic sulfate aerosol on regional climate in East Asia[J]. Asia-Pacific J Atmos Sci, 2014, 50(3): 391-403. doi: 10.1007/s13143-014-0026-5
    [32] JIANG Y Q, LIU X H, YANF X Q, et al. A numerical study of the effect of different aerosol types on East Asian summer clouds and precipitation[J]. Atmos Environ, 2013, 70(1): 51-63. http://www.sciencedirect.com/science/article/pii/S135223101300006X
    [33] ZHUANG B L, LIU Q, WANG T J, et al. Investigation on semi-direct and indirect climate effects of fossil fuel black carbon aerosol over China[J]. Theoret ApplClimatol, 2013, 114(3): 651-672. http://adsabs.harvard.edu/abs/2013thapc.114..651z
    [34] MING J, CACHIER H, XIAO C, et al. Black carbon record based on a shallow Himalayan ice core and its climatic implications[J]. Atmos Chem Phy, 2008, 8(5): 1343-1352. doi: 10.5194/acp-8-1343-2008
    [35] XU B Q, CAO J J, HANSEN J, et al. Black soot and the survival of Tibetan glaciers[J]. Proceed Nat Acad Sci United States of Amer, 2009, 106(52): 22114-22118. doi: 10.1073/pnas.0910444106
    [36] MENON S, KOCH D, BEIG G, et al. Black carbon aerosols and the third polar ice cap[J]. Atmos Chem Phy, 2010, 10(10): 4559-4571. doi: 10.5194/acp-10-4559-2010
    [37] KOPACZ M, MAUZERALL D L, WANG J, et al. Origin and radiative forcing of black carbon transported to the Himalayas and Tibetan Plateau[J]. Atmos ChemPhy, 2010, 11(6): 158-166. http://adsabs.harvard.edu/abs/2010AGUFM.A33I..06K
    [38] WANG Z L, ZHNAG H, SHEN X S. Radiative forcing and climate response due to black carbon in snow and ice[J]. Adv Atmos Sci, 2011, 28(6):1336-1344. doi: 10.1007/s00376-011-0117-5
    [39] BAUER S E, MENNON S, KOCH T C, et al. A global modeling study on carbonaceous aerosol microphysical characteristics and radiative forcing[J]. Atmos Chem Phys, 2010, 10(15): 4543-4592. http://adsabs.harvard.edu/abs/2010ACPD...10.4543B
    [40] KOCH D, BAUER S E, DEL GENIO A, et al. Coupled aerosol-chemistry-climate twentieth-century transient model investigation: Trends in short-lived species and climate responses[J]. J Clim, 2011, 24(11): 2693-2714. doi: 10.1175/2011JCLI3582.1
    [41] FAST J D, GUSTAFSON W I, EASTER C, et al. 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, 2006, 111, D21305, doi: 10.1029/2005JD006721.
    [42] GUSTAFSON W I, CHAPMAN E G, GHAN S J, et al. Impact on modeled cloud characteristics due to simplified treatment of uniform cloud condensation nuclei during NEAQS 2004[J]. Geophysl Res Lett, 2007, 34(19): 255-268. http://adsabs.harvard.edu/abs/2007GeoRL..3419809G
    [43] CHAPMAN E D, GUSTAFSON W I, EASTEE R C, et al. Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources[J]. Atmos Chem Phy, 2009, 9(3): 945-964. doi: 10.5194/acp-9-945-2009
    [44] YANG Q, GUSTAFSON W I, FAST J D, et al. Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem[J]. Atmos Chem Phy, 2011, 11(23): 11951-11975. doi: 10.5194/acp-11-11951-2011
    [45] YANG Q, GUSTAFSON W I, FAST J D, et al. Impact of natural and anthropogenic aerosols on stratocumulus and precipitation in the Southeast Pacific: a regional modelling study using WRF-Chem[J]. Atmos Chem Phy, 2012, 12(18): 8777-8796. doi: 10.5194/acp-12-8777-2012
    [46] SAIDE P E, SPAK S N, CARMICHAEL G R, et al. Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-Rex[J]. Atmos Chem Phy, 2012, 12(6): 3045-3064. doi: 10.5194/acp-12-3045-2012
    [47] ZAVERI R A, EASTER R C, FAST J D, et al. Model for simulating aerosol interactions and chemistry (MOSAIC)[J]. J Geophys Res: Atmos(1984-2012), 2008, 113(D13): 1395-1400. http://adsabs.harvard.edu/abs/2008JGRD..11313204Z
    [48] EMMONS L, WALTERS S, HESS P, et al. Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4(MOZART-4)[J]. Geoscient Mod Developm, 2010, 3(1): 43-67. doi: 10.5194/gmd-3-43-2010
    [49] ZHANG Q, STREETS D, CARMICHAELG, et al. Asian emission in 2006 for the NASA INTEX-B mission[J]. Atmos Chem Phy, 2009, 9(3): 5131-5153. http://adsabs.harvard.edu/abs/2009acp.....9.5131z
    [50] MLAWER E J, TAUBMAN S J, BROWN P D, et al. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave[J]. J Geophys Res: Atmos(1984-2012), 1997, 102(D14): 16663-16682. doi: 10.1029/97JD00237
    [51] CHOU M D, SUAREZ M J. An efficient thermal infrared radiation parameterization for use in general circulation models[R]//NASA Technical Memorandum 104606, Vol3. 1994.
    [52] CHEN F, DUDHIA J. 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, 2001, 129(4): 569-585. doi: 10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2
    [53] HONG S Y, PAN H L. Nonlocal boundary layer vertical diffusion in a medium-range forecast model[J]. Mon Wea Rev, 1996, 124(10): 2322-2339. doi: 10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2
    [54] GRELL G A, DEVENYI D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques[J]. Geophys Res Lett, 2002, 29(14): 1-4. http://adsabs.harvard.edu/abs/2002GeoRL..29.1693G
    [55] MORRISON H, CURRY J A, KHVOROSTYANOV V I. A new double-moment microphysics parameterization for application in cloud and climate models, Part Ⅰ: Description[J]. J Atmos Sci, 2005, 62(6): 1665-1677. doi: 10.1175/JAS3446.1
    [56] MORRISON H, THOMPSON G, TATARSKII V. Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one-and two-moment schemes[J]. Mon Wea Rev, 2009, 137(3): 991-1007. doi: 10.1175/2008MWR2556.1
    [57] WILD O, ZHU X, PRATHER M J. Fast-J: Accurate simulation of in-and below-cloud photolysis in tropospheric chemical models[J]. J Atmos Chem, 2000, 37(3): 245-282. doi: 10.1023/A:1006415919030
    [58] ZAVERI R A, PETERS L K. A new lumped structure photochemical mechanism for large-scale applications[J]. J Geophys Res: Atmos(1984-2012), 1999, 104(D23): 30387-30415. doi: 10.1029/1999JD900876
    [59] ZHANG X Y, WANG Y Q, ZHANG X C, et al. Carbonaceous aerosol composition over various regions of China during 2006[J]. J Geophys Res, 2008, 113(D14). http://adsabs.harvard.edu/abs/2008JGRD..11314111Z
    [60] KAUFMAN Y J, TANRE D, GORDON H R, et al. Passive remote sensing of tropospheric aerosol and atmospheric correction for the aerosol effect[J]. J Geophys Res-Atmos, 1997, 102(D14): 16815-16830. doi: 10.1029/97JD01496
    [61] FEINGOLD G, REMER L A, RAMAPRASAD J et al. Analysis of smoke impact on clouds in Brazilian biomass burning regions: An extension of Twomey's approach[J]. J Geophys Res, 2001, 106(19): 22907-22922. http://adsabs.harvard.edu/abs/2001JGR...10622907F
    [62] ZHANG Y, LIU P, PUN B, et al. A comprehensive performance evaluation of MM5-CMAQ for the Summer 1999 Southern Oxidants Study episode, Part Ⅰ: Evaluation protocols, databases and meteorological predictions[J]. Atmos Environm, 2006, 40(26): 4825-4838. doi: 10.1016/j.atmosenv.2005.12.043
    [63] TUCCELLA P, CURCI G, VISCONTI G, et al. Modeling of gas and aerosol with WRF-Chem over Europe: Evaluation and sensitivity study[J]. J Geophys Res, 2012, 117(D3): 812-819. http://adsabs.harvard.edu/abs/2012JGRD..117.3303T
    [64] WANG Y X, ZHANG Q Q, HE K B, et al. Sulfate nitrate-ammonium aerosols over China: Response to 2000-2015 emission changes of sulfur dioxide, nitrogen oxides, and ammonia[J]. Atmos Chem Phys, 2012, 12(9): 24243-24285. doi: 10.5194/acpd-12-24243-2012
    [65] GAO Y, LIU X, ZHAO C, et al. Emission controls versus meteorological conditions in determining aerosol concentrations in Beijing during the 2008 Olympic Games[J]. Atmos Chem Phys, 2011, 11(23): 12437-12451. doi: 10.5194/acp-11-12437-2011
    [66] SHRIVASTAVA M, FAST J, EASTER R, et al. Modeling organic aerosols in a megacity: Comparison of simple and complex representations of the volatility basis set approach[J]. Atmos Chem Phys, 2011, 10(12): 6639-6662. http://adsabs.harvard.edu/abs/2010ACPD...1030205S
    [67] LI G, ZAVALA M, LEI W, et al. Simulations of organic aerosol concentrations in Mexico City using the WRF-CHEM model during the MCMA-2006/MILAGRO campaign[J]. Atmos Chem Phys, 2011, 11(8): 3789-3809. doi: 10.5194/acp-11-3789-2011
    [68] KUMAR R, BARTH M C, PFISTER G G, et al. WRF-Chem simulations of a typical pre-monsoon dust storm in northern India: influences on aerosol optical properties and radiation budget[J]. Atmos Chem Phys, 2014, 14(5): 2431-2446. doi: 10.5194/acp-14-2431-2014
    [69] ZHANG Y, ZHANG X, WANG K, et al. Incorporating an advanced aerosol activation parameterization into WRF-CAM5: Model evaluation and parameterization intercomparison[J]. J Geophys Res: Atmos, 2015, 120(14): 6952-6979. doi: 10.1002/2014JD023051
    [70] ZHANG Y, MCMURRY P H, YU F, et al. A comparative study of nucleation parameterizations: 1: Examination and evaluation of the formulations[J]. J Geophys Res: Atmos(1984-2012), 2010, 115(D20): 898-907. http://adsabs.harvard.edu/abs/2010JGRD..11520212Z
    [71] DUSEK U, REISCHL G P, HITZENBERGER R. CCN activation of pure and coated carbon black particles[J]. Environml Sci Technol, 2006, 40(4): 1223-1230. doi: 10.1021/es0503478
    [72] ROSE D, GUNTHE S S, SU H, et al. Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China, Part 2: Size-resolved aerosol chemical composition, diurnal cycles, and externally mixed weakly CCN-active soot particles[J]. Atmos Chem Phys, 2011, 11(6): 2817-2836. doi: 10.5194/acp-11-2817-2011
    [73] SCHWARTZ S E, HARSHVARDHAN, BENKOVITZ C M. Influence of anthropogenic aerosol on cloud optical depth and albedo shown by satellite measurements and chemical transport modeling[J]. Proceed Nati Acad Sci, 2002, 99(4): 1784-1789. doi: 10.1073/pnas.261712099
    [74] ZHANG Y, CHEM Y, SARWAR G, et al. Impact of gas-phase mechanisms on weather research forecasting model with chemistry(WRF/Chem) predictions: Mechanism implementation and comparative evaluation[J]. J Geophys Res: Atmos(1984-2012), 2012, 117(D1): 1301. http://adsabs.harvard.edu/abs/2012JGRD..117.1301Z
  • 加载中
图(12) / 表(6)
计量
  • 文章访问数:  861
  • HTML全文浏览量:  35
  • PDF下载量:  610
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-12-23
  • 修回日期:  2017-02-26
  • 刊出日期:  2017-08-01

目录

    /

    返回文章
    返回