设为首页
加入收藏
Macro and Micro Characteristics of a Fog Process in Changbai Mountain in Summer
-
摘要: 2021年夏季首次利用激光雾滴谱仪开展长白山主峰雾的观测研究。结合地面自动气象站、探空、葵花8号高分辨率卫星资料和ERA5再分析资料, 对2021年7月31日—8月1日长白山主峰出现的持续时间达19 h、最低能见度小于100 m的雾过程的宏微观特征分析表明:此次雾过程具有持续时间长、环境风速大、能见度低、有短暂消散, 且数浓度低、有效直径和液态水含量小等特征。雾滴有效直径平均值为5.7 μm, 数浓度平均值为246.4 cm-3, 液态水含量平均值为0.05 g·cm-3, 其微物理特征与海雾特征接近。雾过程开始为爬坡雾, 这是长白山主峰夏季典型的地形云雾, 随后由高空云层平流至长白山主峰而接地产生。在强浓雾的形成、发展和减弱阶段, 雾滴数浓度、液态水含量和有效直径的变化具有较好对应关系;在成熟阶段, 雾滴数浓度、液态水含量和有效直径变化的对应关系不明显。Abstract: In the summer of 2021, the fog droplet spectrum observation is carried out on the main peak of Changbai Mountain for the first time. From 31 July to 1 August, there is a fog process that lasts for 19 hours, and the minimum visibility in the extremely dense fog stage is less than 100 m. Using the observations of laser fog droplet spectrometer, combined with the ground automatic weather station, GPS balloon sounding, Himawari-8 satellite and ERA5 data, the macro and micro physical characteristics of the fog are studied, the causes of the fog are discussed, and the microphysical characteristics evolutions of the extremely dense fog period are analyzed.The results show that the fog process lasts for a long duration with occasional short dissipation, and during the process the ambient wind speed is high, the visibility is low, the number concentration of the droplets is low, with small effective diameter and low liquid water content. The wind speed is always high in the period of extremely dense fog, which is significantly different from that of plain fog. In the early stage the fog is arisen from windward slope, which is a typical topographical cloud and fog on the main peak of Changbai Mountain in summer. It is formed by the continuous southwest warm and humid airflow climbing along the terrain under the condition of stable temperature inversion stratification. While the latter process of the fog is generated by the advection to the main peak of Changbai Mountain. The temporary dissipation of fog is related to the intensity and movement of the jet core at 700 hPa. The average effective diameter of fog droplets is 5.7 μm, the average number concentration is 246.4 cm-3, and the average liquid water content is 0.05 g·cm-3. The microphysical characteristics are similar to those of sea fog.For the extremely dense fog, the minimum visibility is less than 100 m. The extremely dense fog is characterized by explosive enhancement. Due to the rapid expansion of the droplets through the turbulent collision process, a single peak structure is formed. The peak diameter of the droplet particles is 6.0 μm, which has a significant contribution to the formation of the summer fog on the main peak of Changbai Mountain. In the formation, development and weakening stages of the extremely dense fog, the changes of droplet number concentration, liquid water content and effective diameter have a good corresponding relationship, but it is not obvious in the mature stage.
-
图 1 2021年7月31日—8月1日700 hPa温度场(红色实线，单位：℃)、风场(矢量)及12 m·s-1以上全风速(填色)
Fig. 1 Temperature(the red solid line, unit:℃), wind(the vector) and full wind speed above 12 m·s-1(the shaded) at 700 hPa from 31 Jul to 1 Aug in 2021
图 2 2021年7月31日—8月1日长白山天池站温度和相对湿度的垂直分布
Fig. 2 Vertical distribution of temperature and relative humidity at Tianchi Weather Station of Changbai Mountain from 31 Jul to 1 Aug in 2021
图 3 2021年7月31日—8月1日临江站温度和相对湿度的垂直分布
Fig. 3 Vertical distribution of temperature and relative humidity at Linjiang Station from 31 Jul to 1 Aug in 2021
图 4 2021年7月31日13:00和17:00葵花8号卫星高分辨率自然彩色合成云图(△代表雾滴谱仪位置)
Fig. 4 High-resolution natural color composite cloud images of the Himawari-8 Satellite at 1300 BT and 1700 BT on 31 Jul 2021(△ denotes the location of fog droplet spectrometer)
图 5 2021年7月31日—8月1日物理量演变
Fig. 5 Evolution of physical quantities from 31 Jul to 1 Aug in 2021
图 6 2021年7月31日—8月1日雾滴谱分布
Fig. 6 Droplet spectral distribution from 31 Jul to 1 Aug in 2021
图 7 2021年7月31日12:09—16:59雾滴谱分布
Fig. 7 Droplet spectrum distribution from 1209 BT to 1659 BT on 31 Jul 2021
表 1 雾过程的物理量统计值
Table 1 Statistics of physical quantities in fog process
时段 统计量 气温/℃ 数浓度/cm-3 液态水含量/(g·cm-3) 有效直径/μm 最小值 10.1 0.14 5.94×10-7 2.0 全过程 最大值 13.5 1261.7 0.65 34.0 平均值 11.8 246.4 0.05 5.7 最小值 11.0 0.1 5.94×10-7 2.0 子过程1 最大值 13.5 1261.7 0.65 34.0 平均值 12.5 477.1 0.10 7.1 最小值 10.1 0.1 5.94×10-7 2.0 子过程2 最大值 12.1 296.6 0.08 20.4 平均值 11.2 35.3 0.20×10-2 4.5 
下载: 导出CSV
表 2 长白山主峰雾与其他地区雾的微物理特征比较
Table 2 Comparison of microphysical characteristics of fog on the main peak of Changbai Mountain and other areas
地点 海拔/m 时间 数浓度平均值/cm-3 有效直径平均值/μm 峰值直径/μm 液态水含量平均值/(g·cm-3) 长白山主峰 2623 2021-07-31—08-01 246.4 5.7 4.0 0.05 南岭大瑶山[18] 815 1998-12—1991-01
2001-02—03167.8 8.4 4.0 0.16 衡山[17] 1266 1962-05 359.3 12.1 8.0 0.40 庐山[13] 1500 1962-07—08 453.5 15.2 10.0 0.86 泰山[17] 1100 1981-02—04 395.5 11.7 9.0 0.66 济南[33] 2017-01-03—06 35.9 5.8 0.65×10-2 安徽寿县[34] 2019-01-07—08;2019-01-11—13 195.6 5.9 0.09 南京[35] 2006-12-24—27 488.7 5.8 0.35 厦门翔安[36] 2019-04-07 100.0 0.17
下载: 导出CSV
表 3 2021年7月31日12：09—16：59强浓雾期间各物理量演变
Table 3 Evolution of physical quantities during extremely dense fog from 1209 BT to 1659 BT on 31 Jul 2021
物理量 形成阶段
12:09—12:32发展阶段
12:32—13:45成熟阶段
13:45—16:00减弱阶段
16:00—16:59气温/℃ 13.4
(13.3~13.5)13.1
(13.0~13.4)13.0
(12.8~13.2)12.7
(12.3~12.9)数浓度/cm-3 482.7
(0.2~1125.2)712.6
(253.6~1228.6)655.4
(6.2~1261.7)405.6
(0.173~1095.9)液态水含量/(g·cm-3) 0.09
(5.97×10-6~0.46)0.20
(0.03~0.65)0.14
(2.00×10-4~0.53)0.10
(2.45×10-6~0.44)有效直径/μm 7.5
(3.6~22.5)9.2
(6.3~12.4)8.0
(4.4~10.5)7.6
(3.0~34.0)注：括号内数据表示不同阶段各物理量变化范围。
下载: 导出CSV
-
[1] 梁爱民,张庆红,申红喜,等.北京地区一次平流雾过程的分析和数值模拟.应用气象学报,2009,20(5):612-621. doi: 10.3969/j.issn.1001-7313.2009.05.013Liang A M, Zhang Q H, Shen H X, et al. The analysis and simulation of an advection fog event in Beijing. J Appl Meteor Sci, 2009, 20(5): 612-621. doi: 10.3969/j.issn.1001-7313.2009.05.013 [2] 严文莲, 刘端阳, 濮梅娟, 等. 南京地区雨雾的形成及其结构特征. 气象, 2010, 36(10): 29-36. doi: 10.7519/j.issn.1000-0526.2010.10.005Yan W L, Liu D Y, Pu M J, et al. Formation and structure characteristics of precipitation fog in Nanjing. Meteor Mon, 2010, 36(10): 29-36. doi: 10.7519/j.issn.1000-0526.2010.10.005 [3] 郭丽君, 郭学良. 北京2009—2013年期间持续性大雾的类型、垂直结构及物理成因. 大气科学, 2016, 40(2): 296-310. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK201602006.htmGuo L J, Guo X L. The type, vertical structure and physical formation mechanism of persistent heavy fog events during 2009-2013 in the Beijing region. Chinese J Atmos Sci, 2016, 40(2): 296-310. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK201602006.htm [4] 梁军, 张胜军, 隋洪起, 等. 大连地区大雾特征. 应用气象学报, 2009, 20(1): 28-35. doi: 10.3969/j.issn.1001-7313.2009.01.004Liang J, Zhang S J, Sui H Q, et al. Characteristics of heavy fog in Dalian. J Appl Meteor Sci, 2009, 20(1): 28-35. doi: 10.3969/j.issn.1001-7313.2009.01.004 [5] 李永平, 刘晓波, 葛伟强, 等. 一种基于卫星遥感和数值预报产品的雾预报方法. 应用气象学报, 2012, 23(3): 340-347. doi: 10.3969/j.issn.1001-7313.2012.03.010Li Y P, Liu X B, Ge W Q, et al. A fog nowcast method based on satellite remote sensing and numerical products from meso-scale atmospheric model. J Appl Meteor Sci, 2012, 23(3): 340-347. doi: 10.3969/j.issn.1001-7313.2012.03.010 [6] 李子华, 刘端阳, 杨军. 辐射雾雾滴谱拓宽的微物理过程和宏观条件. 大气科学, 2011, 35(1): 41-54. doi: 10.3878/j.issn.1006-9895.2011.01.04Li Z H, Liu D Y, Yang J. The microphysical processes and macroscopic conditions of the radiation fog droplet spectrum broadening. Chinese J Atmos Sci, 2011, 35(1): 41-54. doi: 10.3878/j.issn.1006-9895.2011.01.04 [7] 方春刚, 郭学良. 华北一次浓雾过程爆发性增强的微物理特征. 应用气象学报, 2019, 30(6): 700-709. doi: 10.11898/1001-7313.20190606Fang C G, Guo X L. The microphysical structure of a heavy fog event in North China. J Appl Meteor Sci, 2019, 30(6): 700-709. doi: 10.11898/1001-7313.20190606 [8] 苏正军, 郭学良, 诸葛杰, 等. 云雾物理膨胀云室研制及参数测试. 应用气象学报, 2019, 30(6): 722-730. doi: 10.11898/1001-7313.20190608Su Z J, Guo X L, Zhuge J, et al. Developing and testing of an expansion cloud chamber for cloud physics research. J Appl Meteor Sci, 2019, 30(6): 722-730. doi: 10.11898/1001-7313.20190608 [9] Stekl J, Podzimek J. Old mountain meteorological station Milesovka(Donnersberg) in Central Europe. Bull Amer Meteor Soc, 1993, 74(5): 831-834. doi: 10.1175/1520-0477(1993)074<0831:OMMSMI>2.0.CO;2 [10] Tag P M, Peak J E. Machine learning of maritime fog forecast rules. J Appl Meteor, 1996, 35: 714-724. doi: 10.1175/1520-0450(1996)035<0714:MLOMFF>2.0.CO;2 [11] Lee R R. Two case studies of wintertime cloud systems over the Colorado Rockies. J Atmos Sci, 1984, 41(5): 868-878. doi: 10.1175/1520-0469(1984)041<0868:TCSOWC>2.0.CO;2 [12] 郭学良, 方春刚, 卢广献, 等. 2008—2018年我国人工影响天气技术及应用进展. 应用气象学报, 2019, 30(6): 641-650. doi: 10.11898/1001-7313.20190601Guo X L, Fang C G, Lu G X, et al. Progresses of weather modification technologies and applications in China from 2008 to 2018. J Appl Meteor Sci, 2019, 30(6): 641-650. doi: 10.11898/1001-7313.20190601 [13] 郭学良, 付丹红, 郭欣, 等. 我国云降水物理飞机观测研究进展. 应用气象学报, 2021, 32(6): 641-652. doi: 10.11898/1001-7313.20210601Guo X L, Fu D H, Guo X, et al. Advances in aircraft measurements of clouds and precipitation in China. J Appl Meteor Sci, 2021, 32(6): 641-652. doi: 10.11898/1001-7313.20210601 [14] 俞香仁. 云雾对激光传播及能见度的影响. 气象, 1982, 8(5): 24-26. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX198205013.htmYu X R. Influence of cloud and fog on laser propagation and visibility. Meteor Mon, 1982, 8(5): 24-26. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX198205013.htm [15] 李子华. 中国近40年来雾的研究. 气象学报, 2001, 59(5): 616-624. doi: 10.3321/j.issn:0577-6619.2001.05.011Li Z H. Studies of fog in China over the past 40 years. Acta Meteor Sinica, 2001, 59(5): 616-624. doi: 10.3321/j.issn:0577-6619.2001.05.011 [16] Wu D, Deng X J, Mao J T, et al. Maocro- and micro-structures of heavy fogs and visibility in the Dayaoshan expressway. Acta Meteor Sinica, 2007, 21(3): 324-352. [17] 汪学军, 王新来, 姚叶青. 九华山雾日时间变化特征及其形成的气象条件分析. 暴雨灾害, 2012, 31(3): 287-292. https://www.cnki.com.cn/Article/CJFDTOTAL-HBQX201203013.htmWang X J, Wang X L, Yao Y Q. Aanlysis on the temporal change features and meteorological conditions of fog day in Jiuhua Mountain. Torrential Rain Disaster, 2012, 31(3): 287-292. https://www.cnki.com.cn/Article/CJFDTOTAL-HBQX201203013.htm [18] 詹丽珊, 陈万奎, 黄美元. 南岳和泰山云中微结构起伏资料的初步分析. 我国云雾降水微物理特征的研究. 北京: 科学出版社, 1965: 30-40.Zhan L S, Chen W K, Huang M Y. Preliminary Analysis of Microstructure Fluctuation Data in Nanyue and Taishan Clouds. Research on the Microphysical Characteristics of Cloud and Fog Precipitation of China. Beijing: Science Press-1965: 30-40. [19] 吴兑, 邓雪娇, 毛节泰, 等. 南岭大瑶山高速公路浓雾的宏微观结构与能见度研究. 气象学报, 2007, 65(3): 406-415. doi: 10.3321/j.issn:0577-6619.2007.03.009Wu D, Deng X J, Mao J T, et al. A study on macro- and micro-structures of heavy fog and visibility at freeway in the Nanling Dayaoshan Mountain. Acta Meteor Sinica, 2007, 65(3): 406-415. doi: 10.3321/j.issn:0577-6619.2007.03.009 [20] 银燕, 陈晨, 陈魁, 等. 黄山大气气溶胶微观特性的观测研究. 大气科学学报, 2010, 33(2): 129-136. doi: 10.3969/j.issn.1674-7097.2010.02.001Yin Y, Chen C, Chen K, et al. An observational study of the Microphysical properties of atmospheric aerosol at Mt. Huang. Trans Atmos Sci, 2010, 33(2): 129-136. doi: 10.3969/j.issn.1674-7097.2010.02.001 [21] 郭丽君, 郭学良, 楼小凤, 等. 庐山云雾及降水的日、季节变化和宏微观物理特征观测研究. 气象学报, 2019, 77(5): 923-937. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201905010.htmGuo L J, Guo X L, Lou X F, et al. An observational study of diurnal and seasonal variations, and macroscopic and microphysical properties of clouds and precipitation over Mount Lu, Jiangxi, China. Acta Meteor Sinica, 2019, 77(5): 923-937. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201905010.htm [22] 党张利, 桑建人, 常倬林, 等. 六盘山两次大雾过程宏微观物理特征分析. 宁夏工程技术, 2020, 19(3): 200-204;210. doi: 10.3969/j.issn.1671-7244.2020.03.003Dang Z L, Sang J R, Chang Z L, et al. Analysis of macro and microphysical characteristics of two heavy fog in Liupan Mountain Area. Ningxia Eng Tech, 2020, 19(3): 200-204;210. doi: 10.3969/j.issn.1671-7244.2020.03.003 [23] 吴兑, 邓雪娇, 叶燕翔, 等. 南岭大瑶山浓雾雾水的化学成分研究. 气象学报, 2004, 62(4): 476-485. doi: 10.3321/j.issn:0577-6619.2004.04.010Wu D, Deng X J, Ye Y X, et al. The study on fog-water chemical composition in Dayaoshan of Nanling Mountain. Acta Meteor Sinica, 2004, 62(4): 476-485. doi: 10.3321/j.issn:0577-6619.2004.04.010 [24] Rosenfeld D, Dai J, Yu X, et al. Inverse relations between amounts of air pollution and orographic precipitation. Science, 2007, 315(5817): 1396-1398. doi: 10.1126/science.1137949 [25] 程鹏, 罗汉, 常祎, 等. 祁连山一次地形云降水微物理特征飞机观测. 应用气象学报, 2021, 32(6): 691-705. doi: 10.11898/1001-7313.20210605Cheng P, Luo H, Chang Y, et al. Aircraft measurement of microphysical characteristics of a topographic cloud precipitation in Qilian Mountains. J Appl Meteor Sci, 2021, 32(6): 691-705. doi: 10.11898/1001-7313.20210605 [26] 常祎, 郭学良, 唐洁, 等. 青藏高原夏季对流云微物理特征和降水形成机制. 应用气象学报, 2021, 32(6): 720-734. doi: 10.11898/1001-7313.20210607Chang Y, Guo X L, Tang J, et al. Microphysical characteristics and precipitation formation mechanisms of convective clouds over the Tibetan Plateau. J Appl Meteor Sci, 2021, 32(6): 720-734. doi: 10.11898/1001-7313.20210607 [27] Hersbach H, Bell B, Berrisford P, et al. The ERA5 global reanalysis. Quart J Roy Meteor Soc, 2020, 146(730): 1999-2049. doi: 10.1002/qj.3803 [28] Takenaka H, Sakashita T, Higuchi A, et al. Development of geolocation correction for geostationary satellite observation by phase only correlation method using visible channel. Remote Sensing, 2020, 12(15): 2472. doi: 10.3390/rs12152472 [29] Yamamoto Y, Ichii K, Higuchi A, et al. Geolocation accuracy assessment of Himawari-8/AHI imagery for application to terrestrial monitoring. Remote Sensing, 2020, 12(9): 1372. doi: 10.3390/rs12091372 [30] 史晓丁, 伍波, 樊冬. 基于前向Mie散射的激光雾滴谱仪. 激光杂志, 2020, 41(4): 116-119. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202004023.htmShi X D, Wu B, Fan D. Laser fog droplet spectrometer based on forward Mie scattering. Laser J, 2020, 41(4): 116-119. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202004023.htm [31] 国家气象中心. 雾的预报等级GB/T 27964—2011. 北京: 中国标准出版社, 2012.National Meteorological Centre. Grade of Fog Forecast GB/T 27964-2011. Beijing: China Standard Press, 2012. [32] 王宏斌, 张志薇, 刘端阳, 等. 基于葵花8号新一代静止气象卫星的夜间雾识别. 高原气象, 2018, 37(6): 1749-1764. https://www.cnki.com.cn/Article/CJFDTOTAL-GYQX201806025.htmWang H B, Zhang Z W, Liu D Y, et al. Detection of fog at night by using the new geostationary satellite Himawari-8. Plateau Meteor, 2018, 37(6): 1749-1764. https://www.cnki.com.cn/Article/CJFDTOTAL-GYQX201806025.htm [33] 王庆, 李季, 樊明月, 等. 济南一次平流辐射雾的微物理结构及演变特征. 气象, 2019, 45(9): 1299-1309. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201909010.htmWang Q, Li J, Fan M Y, et al. Microphysical structure and evolution characteristics of an advection-radiation fog event in Jinan. Meteor Mon, 2019, 45(9): 1299-1309. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201909010.htm [34] 张浩, 石春娥, 杨军, 等. 寿县不同强度雾的微物理特征及其与能见度的关系. 大气科学, 2021, 45(6): 1217-1231. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK202106005.htmZhang H, Shi C E, Yang J, et al. Microphysical characteristics of fog with difference intensities and their relationship wih visibility in Shouxian County. Chinese J Atmos Sci, 2021, 45(6): 1217-1231. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK202106005.htm [35] 刘端阳, 濮梅娟, 杨军, 等. 2006年12月南京连续4天浓雾的微物理结构及演变特征. 气象学报, 2009, 67(1): 147-157. doi: 10.3321/j.issn:0577-6619.2009.01.015Liu D Y, Pu M J, Yang J, et al. Microphysical structure and evolution of four-day persistent fogs around Nanjing in December 2006. Acta Meteor Sinica, 2009, 67(1): 147-157. doi: 10.3321/j.issn:0577-6619.2009.01.015 [36] 张伟, 陈德花, 胡雅君, 等. 闽南沿海一次春季海雾过程微物理特征分析. 气象, 2021, 47(2): 157-169. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202102003.htmZhang W, Chen D H, Hu Y J, et al. Microphysical structure analysis of a spring sea fog event in southern coastal area of Fujian. Meteor Mon, 2021, 47(2): 157-169. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202102003.htm -
图(7) / 表(3)
计量
- 摘要浏览量: 1023
- HTML全文浏览量: 186
- PDF下载量: 144
- 被引次数: 0
