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Characteristics of Aerosol and Cloud over the Central Plain of North China in Summer
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摘要: 气溶胶与云的垂直分布特征是气溶胶间接气候效应关注的重点。基于2018年7—8月华北中部6架次飞机观测数据,研究气溶胶和云滴的垂直和水平分布特征。结果表明:华北中部780~5687 m高度内气溶胶数浓度( Na )平均值为821.36 cm-3,最大量级可达到104 cm-3,云中气溶胶数浓度(Nacc)占总颗粒浓度的80%以上,表明细颗粒占大多数,气溶胶粒子算术平均直径( Dm )平均值为0.12~0.52 μm；大气层结对气溶胶垂直分布影响较大,逆温阻挡气溶胶垂直输送,高空(高度2000 m以上) Dm 的垂直分布受到相对湿度影响较大； Na 和 Dm 在垂直方向波动较大,水平方向波动较小；低层云中云滴数浓度(Nc)较大、液态水含量(L)较小,而中层和高层云中Nc较小、L较大,Nc和云滴有效半径(Re)的概率密度函数均为双峰型分布,L的概率密度函数为单峰型分布；气溶胶数浓度谱基本呈现多峰型分布,而云滴数浓度谱多呈现单峰型分布。Abstract: The vertical distribution of aerosols and clouds is a key issue in the indirect climate effects of aerosols. Based on the aerosol and cloud droplet number concentration data observed by 6 aircrafts over the central plain of North China from July to August in 2018, the vertical distribution and spectral characteristics of aerosols and clouds are studied. The results show that the mean value of aerosol number concentration ( Na ) of this area is higher than that in Central China, the in-cloud aerosol number concentration (Nacc) accounts for over 80% of the total concentration, and the mean particle diameter ( Dm ) is between 0.12 and 0.52 μm, which means fine particles contribute the largest proportion. The aerosol number concentration decreases with the height. The total aerosol number concentration is higher with middle and high stratus comparing to low-level stratus. The vertical distribution of Na is significantly affected by atmospheric stratification, as inversion temperature layer block the vertical transport of aerosols. The vertical distribution of mean diameter below 3500 m is relatively stable, with an average of 0.23 μm, while increases with the height above 3500 m. The vertical distribution of aerosol particle mean diameter at high altitude (above 2000 m) is greatly affected by relative humidity. Compared with the vertical distribution of aerosol number concentration and mean diameter, the horizontal variety is smaller. In low-level stratus, the cloud droplet number concentration (Nc) is large, and the liquid water content (L) is small. In middle and high stratus, the cloud droplet number concentration is small, and the liquid water content is large. The probability distribution function of cloud droplet number concentration and liquid water content are bimodal distribution, and the probability distribution function of cloud droplet effective radius (Re) show a single mode. The distribution of aerosol number concentration spectrum shows multi-peak distribution, and the average aerosol spectrum show three-peak distribution. The distribution of cloud droplet number concentration spectrum shows a single peak, which appears at the scale of 9-16 μm, and the spectral width of cloud droplets is 50 μm. The parameter characteristics of aerosol spectral distribution obtained by fitting aerosol spectral distribution can provide an important in situ measurement basis for improving the parameterized schemes such as regional climate model and aerosol-cloud model.
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图 2 2018年7月31日F3观测的温湿廓线(a)和气溶胶数浓度、算术平均直径的垂直分布(b)
Fig. 2 Vertical distributions of temperature and relative humidity(a), Na and Dm (b) during F3 on 31 Jul 2018
图 3 2018年8月22日F4两次垂直观测的温湿廓线及气溶胶数浓度、算术平均直径的垂直分布
(a)起飞过程温湿廓线,(b)起飞过程 Na 和 Dm 垂直分布,(c)降落过程温湿廓线,(d)降落过程 Na 和 Dm 垂直分布
Fig. 3 Vertical distributions of temperature, relative humidity, Na and Dm during F4 on 22 Aug 2018
(a)temperature, relative humidity during take off, (b) Na and Dm during take off, (c)temperature, relative humidity during landing, (d) Na and Dm during landing
图 4 2018年7月26日F2观测不同高度的气溶胶数浓度和算术平均直径的水平分布
Fig. 4 Horizontal distributions of Na and Dm during F2 on 26 Jul 2018
图 6 6架次飞机观测的气溶胶粒子平均谱分布
Fig. 6 Mean size distributions of aerosol particles during six flights
图 8 F3穿云期间的飞行高度、云滴数浓度和液态水含量
(9朵云用Ⅰ~Ⅸ表示)
Fig. 8 Time series of Nc and L during F3
(the nine clouds are marked byⅠ-Ⅸ)
图 10 云滴数浓度、液态水含量和云滴有效半径概率密度函数
Fig. 10 The probability distribution functions of Nc, L and Re
表 1 观测飞行概况
Table 1 Summary of six flights
编号 日期 飞行观测时间 垂直高度范围/m 天气条件 F1 2018-07-21 11:48—13:00 786~5044 中-低层云 F2 2018-07-26 16:09—17:10 780~3778 中-高层云 F3 2018-07-31 17:26—18:52 782~4410 高层云 F4 2018-08-22 10:50—12:14 788~4685 中-高层云 F5 2018-08-22 16:36—17:40 785~4691 中-低层云 F6 2018-08-30 13:53—15:26 786~5687 中-低层云 
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表 2 气溶胶参量统计值
Table 2 Statistics of observed aerosol parameters
架次 Na /cm-3 Dm /μm 平均值 最大值 标准差 Nacc 平均值 最大值 标准差 F1 114.97 1275.69 195.93 98.83 0.43 2.65 0.43 F2 821.36 10493.30 911.91 663.36 0.12 0.53 0.01 F3 198.27 3001.23 280.91 176.64 0.43 2.72 0.40 F4 86.83 730.10 118.30 74.71 0.50 2.45 0.49 F5 127.02 1008.35 165.99 109.45 0.52 2.89 0.44 F6 130.98 1004.96 179.52 114.09 0.46 3.00 0.47
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[1] Ramanathan V, Crutzen P J, Kiehl J T, et al. Aerosols, climate, and the hydrological cycle. Science, 2002, 294(5549): 2119-2124. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=5884898&site=ehost-live [2] Ramanathan V, Crutzen P J, Lelieveld J, et al. Indian Ocean experiment: An integrated analysis of the climate forcing and effects of the great Indo-Asian haze. J Geophys Res Atmos, 2001, 106(D22): 28371-28398. doi: 10.1029/2001JD900133 [3] Solomon S, Qin D, Manning M, et al. IPCC. Climate Change 2007: The Physical Science Basis. Cambridge: Cambridge University Press, 2007. [4] Li J X, Yin Y, Li P R, et al. Aircraft measurements of the vertical distribution and activation property of aerosol particles over the Loess Plateau in China. Atmos Res, 2015, 155: 73-86. doi: 10.1016/j.atmosres.2014.12.004 [5] 梁苑新, 车慧正, 王宏, 等. 北京一次污染过程气溶胶光学特性及辐射效应. 应用气象学报, 2020, 31(5): 583-594. doi: 10.11898/1001-7313.20200506Liang Y X, Che H Z, Wang H, et al. Aerosol optical properties and radiative effects during a pollution episode in Beijing. J Appl Meteor Sci, 2020, 31(5): 583-594. doi: 10.11898/1001-7313.20200506 [6] 杨先逸, 车慧正, 陈权亮, 等. 天空辐射计观测反演北京城区气溶胶光学特性. 应用气象学报, 2020, 31(3): 373-384. doi: 10.11898/1001-7313.20200311Yang X Y, Che H Z, Chen Q L, et al. Retrieval of aerosol optical properties by skyradiometer over urban Beijing. J Appl Meteor Sci, 2020, 31(3): 373-384. doi: 10.11898/1001-7313.20200311 [7] Han Z, Montague D C, Snider J R. Airborne measurements of aerosol extinction in the lower and middle troposphere over Wyoming, USA. Atmos Environ, 2003, 37(6): 789-802. doi: 10.1016/S1352-2310(02)00952-4 [8] Li J X, Li P R, Ren G, et al. Aircraft measurements of aerosol distribution, warm cloud microphysical properties, and their relationship over the Eastern Loess Plateau in China. Tellus Ser B, Chem Phys Meteor, 2019, 71(1): 1-18. doi: 10.1080/16000889.2019.1623639 [9] Chen X T, Kang S C, Yang J H, et al. Investigation of black carbon climate effects in the Arctic in winter and spring. Sci Total Environ, 2020, 751: 142-145. http://www.sciencedirect.com/science/article/pii/S0048969720356746 [10] Liu Q, Jia X C, Quan, J N, et al. New positive feedback mechanism between boundary layer meteorology and secondary aerosol formation during severe haze events. Sci Rep, 2018, 8(1): 6095. doi: 10.1038/s41598-018-24366-3 [11] 肖辉, 舒未希, 付丹红, 等. 声波对气溶胶和云雾粒子聚并影响研究进展. 应用气象学报, 2021, 32(3): 257-271. doi: 10.11898/1001-7313.20210301Xiao H, Shu W X, Fu D H, et al. A review on the effect of sound waves upon the coalescence of aerosol and cloud and fog particles. J Appl Meteor Sci, 2021, 32(3): 257-271. doi: 10.11898/1001-7313.20210301 [12] Zhang W J, Zhang X Y, Zhong J T, et al. The effects of the "two-way feedback mechanism" on the maintenance of persistent heavy aerosol pollution over areas with relatively light aerosol pollution in northwest China. Sci Total Environ, 2019, 688: 642-652. doi: 10.1016/j.scitotenv.2019.06.295 [13] 李东宸, 林慈哲, 银燕. 强对流天气对O3和CO的垂直输送作用. 应用气象学报, 2019, 30(1): 82-92. doi: 10.11898/1001-7313.20190108Li D C, Lin C Z, Yin Y. The vertical transport of the ozone and carbon monoxide by severe convective weather. J Appl Meteor Sci, 2019, 30(1): 82-92. doi: 10.11898/1001-7313.20190108 [14] 王黉, 李英, 文永仁. 川藏高原一次混合型强对流天气的观测特征. 应用气象学报, 2021, 32(5): 567-579. doi: 10.11898/1001-7313.20210505Wang H, Li Y, Wen Y R. Observational characteristics of a hybrid severe convective event in the Sichuan-Tibet Region. J Appl Meteor Sci, 2021, 32(5): 567-579. doi: 10.11898/1001-7313.20210505 [15] 矫健, 贾小芳, 颜鹏, 等. 2016-2017年中国中东部本底地区PM10化学特性. 应用气象学报, 2021, 32(1): 65-77. doi: 10.11898/1001-7313.20210106Jiao J, Jia X F, Yan P, et al. Chemical characteristics of PM10 at background stations of central and eastern China in 2016-2017. J Appl Meteor Sci, 2021, 32(1): 65-77. doi: 10.11898/1001-7313.20210106 [16] Wang Y, Khalizov A, Levy M, et al. New directions: Light absorbing aerosols and their atmospheric impacts. Atmos Environ, 2013, 81: 713-715. doi: 10.1016/j.atmosenv.2013.09.034 [17] 段婧, 楼小凤, 陈勇, 等. 基于航测的珠三角气溶胶垂直分布及活化特性. 应用气象学报, 2019, 30(6): 677-689. doi: 10.11898/1001-7313.20190604Duan J, Lou X F, Chen Y, et al. Aircraft measurements of aerosol vertical distributions and its activation efficiency over the Pearl River Delta. J Appl Meteor Sci, 2019, 30(6): 677-689. doi: 10.11898/1001-7313.20190604 [18] 杨怡曼, 周毓荃, 蔡兆鑫. 气溶胶垂直分布及活化特性的飞机观测个例研究. 气象, 2020, 46(9): 1199-1209. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202009007.htmYang Y M, Zhou Y Q, Cai Z X. A case study of aircraft observation of aerosol vertical distribution and activation characteristics. Meteor Mon, 2020, 46(9): 1199-1209. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202009007.htm [19] 沙桐, 马晓燕, 银燕, 等. 石家庄地区气溶胶和CCN垂直廓线的飞机观测分析. 大气科学学报, 2019, 42(4): 521-530. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX201904005.htmSha T, Ma X Y, Yin Y, et al. Aircraft measurements and analysis of the vertical distribution of aerosol particles and CCN over the Shijiazhuang area. Transactions of Atmospheric Sciences, 2019, 42(4): 521-530. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX201904005.htm [20] 游积平, 高建秋, 黄梦宇, 等. 珠江三角洲地区大气气溶胶特征的飞机观测分析. 热带气象学报, 2015, 31(1): 71-77. https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201501008.htmYou J P, Gao J Q, Huang M Y, et al. Analysis of the characteristics of the aircraft-observed atmospheric aerosols in Pearl River Delta. Journal of Tropical Meteorology, 2015, 31(1): 71-77. https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201501008.htm [21] 范烨, 郭学良, 付丹红, 等. 北京及周边地区2004年8、9月间大气气溶胶分布特征观测分析. 气候与环境研究, 2007, 12(1): 49-62. doi: 10.3969/j.issn.1006-9585.2007.01.006Fan Y, Guo X L, Fu D H, et al. Observational studies on aerosol distribution during August to September in 2004 over Beijing and its surrounding areas. Climatic and Environmental Research, 2007, 12(1): 49-62. doi: 10.3969/j.issn.1006-9585.2007.01.006 [22] 胡向峰, 秦彦硕, 段英, 等. 基于航测数据的河北中南部雾霾天气气溶胶及云凝结核研究. 干旱气象, 2016, 34(3): 481-493. https://www.cnki.com.cn/Article/CJFDTOTAL-GSQX201603011.htmHu X F, Qin Y S, Duan Y, et al. Aircraft study of aerosol and CCN under foggy/hazy weather condition in autumn over the central and southern Hebei. Journal of Arid Meteorology, 2016, 34(3): 481-493. https://www.cnki.com.cn/Article/CJFDTOTAL-GSQX201603011.htm [23] Liu P F, Zhao C S, Zhang Q, et al. Aircraft study of aerosol vertical distributions over Beijing and their optical properties. Tellus Ser B, Chem Phys Meteor, 2009, 61(5): 756-767. doi: 10.1111/j.1600-0889.2009.00440.x [24] 石立新, 段英. 华北地区云凝结核的观测研究. 气象学报, 2007, 65(4): 644-652. doi: 10.3321/j.issn:0577-6619.2007.04.016Shi L X, Duan Y. Observations of cloud condensation nuclei in North China. Acta Meteor Sinica, 2007, 65(4): 644-652. doi: 10.3321/j.issn:0577-6619.2007.04.016 [25] 孙霞, 银燕, 韩洋, 等. 石家庄地区雾霾天气下云滴和云凝结核的分布特征. 中国环境科学, 2012, 32(7): 1165-1170. doi: 10.3969/j.issn.1000-6923.2012.07.003Sun X, Yin Y, Han Y, et al. Distribution of cloud particles and cloud condensation nuclei during haze/fog events in Shijiazhuang. China Environmental Science, 2012, 32(7): 1165-1170. doi: 10.3969/j.issn.1000-6923.2012.07.003 [26] 孙玉稳, 孙霞, 银燕, 等. 华北平原湿地上空气溶胶的分布特征研究. 兰州大学学报(自然科学版), 2010, 46(增刊Ⅰ): 96-101. https://www.cnki.com.cn/Article/CJFDTOTAL-LDZK2010S1058.htmSun Y W, Sun X, Yin Y, et al. Aerosol distribution over wetlands on north China Plain. Journal of Lanzhou University(Nat Sci Ed), 2010, 46(Suppl Ⅰ): 96-101. https://www.cnki.com.cn/Article/CJFDTOTAL-LDZK2010S1058.htm [27] 李军霞, 银燕, 李培仁, 等. 山西夏季气溶胶空间分布飞机观测研究. 中国环境科学, 2014, 34(8): 1950-1959. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGHJ201408007.htmLi J X, Yin Y, Li P R, et al. Aircraft measurements of aerosol spetial distribution properties in Shanxi Province in summer. China Environmental Science, 2014, 34(8): 1950-1959. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGHJ201408007.htm [28] 栾天, 郭学良, 张天航, 等. 不同降水强度对PM2.5的清除作用及影响因素. 应用气象学报, 2019, 30(3): 279-291. doi: 10.11898/1001-7313.20190303Luan T, Guo X L, Zhang T H, et al. The scavenging process and physical removing mechanism of pollutant aerosols by different precipitation intensities. J Appl Meteor Sci, 2019, 30(3): 279-291. doi: 10.11898/1001-7313.20190303 [29] 梁智豪, 王东海, 梁钊明. 探空观测的边界层高度时空变化特征. 应用气象学报, 2020, 31(4): 447-459. doi: 10.11898/1001-7313.20200407Liang Z H, Wang D H, Liang Z M. Spatio-temporal characteristics of boundary layer height derived from soundings. J Appl Meteor Sci, 2020, 31(4): 447-459. doi: 10.11898/1001-7313.20200407 [30] 闫世明, 王雁, 郭伟, 等. 太原市秋冬季大气污染特征和输送路径及潜在源区分析. 环境科学, 2019, 40(11): 4801-4809. https://www.cnki.com.cn/Article/CJFDTOTAL-HJKZ201911007.htmYan S M, Wang Y, Guo W, et al. Characteristics, transportation, pathways, and potential sources of air pollution during autumn and winter in Taiyuan. Environmental Science, 2019, 40(11): 4801-4809. https://www.cnki.com.cn/Article/CJFDTOTAL-HJKZ201911007.htm [31] 李义宇, 杨鸿儒, 王楠, 等. 太原市一次重污染天气过程的成因分析. 气象与环境学报, 2018, 34(2): 11-18. doi: 10.3969/j.issn.1673-503X.2018.02.002Li Y Y, Yang H R, Wang N, et al. Formation analysis of a severe air pollution event in Taiyuan. Journal Meteorology and Environment, 2018, 34(2): 11-18. doi: 10.3969/j.issn.1673-503X.2018.02.002 [32] Bai X Y, Tian H Z, Liu X Y, et al. Spatial-temporal variation characteristics of air pollution and apportionment of contributions by different sources in Shanxi province of China. Atmos Environ, 2021, 244, 117926. doi: 10.1016/j.atmosenv.2020.117926 [33] Kleinman L I, Daum P H, Lee Y N, et al. Aerosol concentration and size distribution measured below, in, and above cloud from the DOEG-1 during VOCALS-REx. Atmos Chem Phys, 2012, 12(1): 207-223. doi: 10.5194/acp-12-207-2012 [34] Yang J M, Li J X, Li P R, et al. Spatial distribution and impacts of aerosols on clouds under Meiyu frontal weather background over central China based on aircraft observations. J Geophys Res Atmos, 2020, 125(15), e2019JD031915. doi: 10.1029/2019JD031915 [35] Hao J, Yin Y, Kuang X, et al. Aircraft measurements of the aerosol spatial distribution and relation with clouds over eastern China. Aerosol Air Qual Res, 2017, 17(12): 3230-3243. doi: 10.4209/aaqr.2016.12.0576 [36] Sun X, Yin Y, Sun W Y, et al. Seasonal and vertical variations in aerosol distribution over Shijiazhuang, China. Atmos Environ, 2013, 81: 245-252. doi: 10.1016/j.atmosenv.2013.08.009 [37] Johnson D W, Osborne S, Wood R, et al. Observations of the evolution of the aerosol, cloud and boundary-layer characteristics during the 1st ACE-2 Lagrangian experiment. Tellus Ser B Chem Phys Meteor, 2016, 52(2): 348-374. http://www.researchgate.net/profile/Karsten_Suhre/publication/227733129_Observations_of_the_evolution_of_the_aerosol_cloud_and_boundary-layer_characteristics_during_the_1st_ACE-2_Lagrangian_experiment/links/0046352f072916a118000000.pdf [38] Li J X, Liu X G, Yuan L, et al. Vertical distribution of aerosol optical properties based on aircraft measurements over the Loess Plateau in China. J Environ Sci, 2015, 34(8): 44-56. http://www.sciencedirect.com/science/article/pii/S0169809514004311 [39] 王鹏飞, 李子华. 微观云物理学. 北京: 气象出版社, 1989.Wang P F, Li Z H. Microscopic Cloud Physics. Beijing: China Meteorological Press, 1989. [40] Lü Y H, Lei H, Yang J. Aircraft measurements of cloud-aerosol interaction over East Inner Mongolia. Adv Atmos Sci, 2017, 34(8): 983-992. doi: 10.1007/s00376-017-6242-z [41] Zhao C F, Qiu Y M, Dong X B, et al. Negative aerosol-cloud re relationship from aircraft observations over Hebei, China. Earth and Space Science, 2018, 5(1): 19-29. doi: 10.1002/2017EA000346 -
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