一次基于风廓线雷达观测的北京夏季降水的垂直观测研究

黄钰; 郭学良; 罗秀明; 陈羿辰; 张邢; 杜远谋; 刘海龙

doi:10.3878/j.issn.1006-9895.2106.20245

一次基于风廓线雷达观测的北京夏季降水的垂直观测研究

doi: 10.3878/j.issn.1006-9895.2106.20245

黄钰^{1, 2, 3,},
郭学良⁴,
罗秀明⁵,
陈羿辰^{1, 2, 3},
张邢^{1, 2, 3},
杜远谋^{1, 2, 3},
刘海龙⁶

1.
北京市人工影响天气办公室，北京 100089
2.
云降水物理研究与云水资源开发北京市重点实验室，北京 100089
3.
中国气象局华北云降水野外科学试验基地，北京 100089
4.
中国科学院大气物理研究所，北京 100029
5.
广德市气象局，安徽广德 242200
6.
95820部队飞行管制室，北京102211

基金项目: 国家重点研发计划项目2017YFC1501405，国家自然科学基金项目41805112

详细信息

作者简介:
黄钰，女，1985年出生，博士、高工，主要从事雷达和人工影响天气研究。E-mail: yhuang1128@163.com

中图分类号: P458.3
计量
- 文章访问数: 198
- HTML全文浏览量: 65
- PDF下载量: 135
- 被引次数: 0
出版历程
- 收稿日期: 2020-12-11
- 录用日期: 2021-09-26
- 网络出版日期: 2021-07-18
- 刊出日期: 2022-03-16

Vertical Observation Study of Summer Rainfall in Beijing Based on Wind Profiler Radar

Yu HUANG^{1, 2, 3
,},
Xueliang GUO⁴,
Xiuming LUO⁵,
Yichen CHENG^{1, 2, 3},
Xing ZHANG^{1, 2, 3},
Yuanmou DU^{1, 2, 3},
Hailong LIU⁶

1.
Beijing Weather Modification Office, Beijing 100089
2.
Beijing Key Laboratory of Cloud, Precipitation and Water Resources, Beijing (Municipal) Meteorological Service, Beijing 100089
3.
Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing 100089
4.
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
5.
Guangde Meteorology Bureau, Guangde, Anhui 242200
6.
Flight Control Office of the 95820 Army, Beijing 102211

Funds: National Key Research and Development Program of China (Grant 2017YFC1501405), National Natural Science Foundation of China (Grant 41805112)

摘要

摘要: 本文利用风廓线雷达数据反演了降水云体的大气垂直速度、雨滴下落末速度等云动力特征和云水混合比、雨水混合比等云微物理参数，并结合天气雷达、探空、自动站、雨滴谱仪和微波辐射计等数据对2020年5月7～8日发生在北京市海淀区的一次夏季降水过程进行垂直综合观测。结果表明：垂直探测仪器观测及其反演的数据可以获得降水云体的详细动力参数和微物理特征。站点位于主体降水回波边缘，降水为层状云类型，整体回波较弱（主要在0～20 dBZ），4 km高度的水平风垂直切变贯穿整个降水过程，降水分为两个阶段：前期7日20时（北京时，下同）至8日02时低层存在浅对流结构，云顶较高（平均高度8207 m），低层水平风切变促进了对流发展，10～20 dBZ的回波比重较大，粒子谱较窄，直径＜1 mm，雨强较弱，但粒子数浓度值大，最大值26305 m⁻³，2～3 km处存在暖平流，水汽和液水值大，雨水混合比0.02～0.15 g/kg，云水混合比0.5～2 g/kg，且强值区域大，雨滴下落末速度3.2～4.2 m/s，大气垂直速度在±0.6 m/s之间，上升气流和下沉气流变换明显；后期8日02～10时转为典型层状云降水，云顶较低（平均高度7831 m），＜10 dBZ的回波比重较大，3100 m处形成亮带的强值中心，粒子谱展宽，最大直径接近1.5 mm，粒子数浓度值减小，最大值＜3000 m⁻³，雨水和云水值比对流期小了一个量级，且强值范围变窄，雨滴下落末速度减小为2.8～3.6 m/s，大气垂直速度也比对流时期小了一个量级，并且在亮带高度以下（2.5～2.8 km）范围内出现明显横向带状的上升和下沉气流区。
- 风廓线雷达 /
- 云微物理场 /
- 云垂直动力场 /
- 夏季降水 /
- 垂直综合观测
Abstract: Wind profiler radar data was used to retrieve cloud dynamic characteristics, including vertical velocity, droplet terminal velocity, and microphysical parameters such as cloud and rain water mixing ratios. Summer precipitation in Haidian District of Beijing on 7–8 May 2020, was observed and analyzed by retrieval results using weather radar, sounding, automated meteorological readings, disdrometer, and microwave radiometer. Results indicated that the vertically scanning instruments and retrieval results obtained precipitation dynamic and microphysical information that can be used for further studies. The station was near the edge of the main precipitation reflectivity factor and had stratiform cloud precipitation. The overall precipitation reflectivity factor was weak (mainly at 0–20 dBZ), with the vertical shear of horizontal wind at 4 km running through total precipitation. The precipitation was divided into two stages. The earlier stage [2000 BJT (Beijing time) 7 to 0200 BJT 8 May 2020] had shallow convective structures at a lower height, and the convective precipitation cloud top was relatively high (average height 8207 m). Horizontal wind shear at low-level aided the development of convection, and the proportion of 10–20 dBZ was large. The particle spectrum was narrow, with a diameter ＜1 mm, and the rain rate was weak. However, the number concentration was large, reaching a maximum of 26305 m⁻³. Warm advection was present at 2–3 km, water vapor and liquid water values were high, and the rain water mixing ratio range was 0.02–0.15 g/kg. The cloud water mixing ratio range was 0.5–2 g/kg, with a large value and wide distribution. Droplet terminal velocity was 3.2–4.2 m/s, with vertical velocity in the range of ±0.6 m/s, and updraft and downdraft alternated. The later stage (0200–1000 BJT 8 May 2020) became typical stratiform cloud precipitation, with a relatively low cloud top (average height 7831 m). The proportion of ＜10 dBZ was large, the strong value center of the bright band was formed at 3100 m, the particle spectrum broadened, and the maximum diameter was close to 1.5 mm. However, the number concentration decreased, with a maximum value ＜3000 m⁻³. The rain and cloud water values were one order of magnitude lower than that of the convective stage. The intensity range was narrow, the droplet terminal velocity was reduced to 2.8–3.6 m/s, and the vertical velocity was reduced by an order of magnitude compared to the convective stage. There was obvious horizontal orientation upward and downward areas below the height of the bright band (2.5–2.8 km).
- Wind profiler radar /
- Cloud micro-physical field /
- Cloud vertical dynamic field /
- Summer rainfall /
- Vertical comprehensive observation

HTML全文

图 1 2020年5月7日20时（北京时，下同）至8日14时北京市海淀区雷达站（39.98°N，116.28°E）（a）SA雷达、（b）风廓线雷达（WPR）观测的反射率因子时间序列

Figure 1. Time series of reflectivity factor observed by (a) Doppler Radar in SA band, (b) WPR (wind profile radar) at radar station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT (Beijing time) 7 May 2020 to 1400 BJT 8 May 2020

下载: 全尺寸图片幻灯片

图 2 2020年5月7日20时至8日13时北京市海淀区雷达站（39.98°N，116.28°E）SA雷达观测的降水组合反射率因子PPI（plan position indicator）的时间演变，箭头所指位置为风廓线雷达位置

Figure 2. Time evolution of PPI (plan position indicator) of reflectivity factor for precipitation observed by SA radar at radar station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1300 BJT 8 May 2020. The position indicated by the arrow is the location of WPR

下载: 全尺寸图片幻灯片

图 3 2020年5月7日20时至8日14时北京市海淀区自动站（39.98°N，116.28°E）小时降水量（单位：mm）、温度（单位：°C）的时间演变

Figure 3. Time evolution of hourly precipitation (units: mm) and temperature (units: °C) observed by automatic weather station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1400 BJT 8 May 2020

下载: 全尺寸图片幻灯片

图 4 2020年5月7日20时至8日14时北京市海淀区雷达站（39.98°N，116.28°E）风廓线雷达观测的水平风矢量

Figure 4. Horizontal wind vectors observed by WPR at radar station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1400 BJT 8 May 2020

下载: 全尺寸图片幻灯片

图 5 2020年5月7日20时至8日14时北京市海淀区雷达站（39.98°N，116.28°E）风廓线雷达观测的反射率因子时间序列

Figure 5. Time series of reflectivity factor by WPR at radar station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1400 BJT 8 May 2020

下载: 全尺寸图片幻灯片

图 6 2020年5月7日20时至8日12时北京市海淀区雷达站（39.98°N，116.28°E）风廓线雷达观测的（a）云顶高度、（b）反射率因子分档比例、（c）反射率因子平均值

Figure 6. (a) Height of cloud top, (b) reflectivity factor ratio at each stage, (c) average reflectivity factor at each stage by WPR at radar station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1200 BJT 8 May 2020

下载: 全尺寸图片幻灯片

图 7 2020年5月7日20时至8日14时北京市海淀区雨滴谱仪（39.98°N，116.28°E）观测的（a）总的粒子数浓度（N_t）、（b）雨强（R）、（c）滴谱时间序列。图c中的N和D分别表示粒子数浓度和直径

Figure 7. Time series of (a) particle number total concentration (N_t), (b) rain rate, (c) size spectrum observed by disdrometer (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1400 BJT 8 May 2020. In Fig. 7c, N and D represent number concentration and diameter of particle, respectively

下载: 全尺寸图片幻灯片

图 8 2020年5月7日20时至8日14时微波辐射计（39.98°N，116.28°E）观测的（a）液态水含量（单位：g m⁻³）、（b）水汽密度（单位：g m⁻³）、（c）温度（单位：°C）、（d）相对湿度的时间序列

Figure 8. Time series of (a) liquid water content (units: g m⁻³), (b) vapor density (units: g m⁻³), (c) temperature (units: °C), (d) relative humidity observed by microwave radiometer (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1400 BJT 8 May 2020

下载: 全尺寸图片幻灯片

图 9 2020年5月7日20时至8日14时北京市海淀区雷达站（39.98°N，116.28°E）风廓线雷达反演的（a）雨水混合比（单位：g/kg）、（b）云水混合比（单位：g/kg）、（c）雨滴下落末速度（单位：m/s）、（d）垂直速度（单位：m/s）时间序列

Figure 9. Time series of (a) rain water mixing ratio (units: g/kg), (b) cloud water mixing ratio (units: g/kg), (c) droplet terminal velocity (units: m/s), (d) vertical velocity (units: m/s) from WPR at radar station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1400 BJT 8 May 2020

下载: 全尺寸图片幻灯片

图 10 2020年5月7日20时至8日10时北京市海淀区雷达站（39.98°N，116.28°E）风廓线雷达反演的降水前期（橙色线）、后期（蓝色线）（a）云水混合比、（b）雨水混合比、（c）雨滴下落末速度、（d）空气垂直速度的平均值

Figure 10. Average of (a) cloud water mixing ratio, (b) rain water mixing ratio, (c) droplet terminal velocity, (d) air vertical velocity at earlier stage (orange lines) and later stage (blue lines) for precipitation observed by WPR at radar station (39.98°N, 116.28°E) in Haidian District of Beijing from 2000 BJT 7 May to 1000 BJT 8 May 2020

下载: 全尺寸图片幻灯片

表 1 风廓线雷达参数表

Table 1. Parameters of wind profile radar

雷达参数	具体参数值
采样频率/MHz	60
发射波长/mm	220
发射峰值功率/kW	10
采样周期/min	4.5
脉冲宽度/µs	12.8（高模）/6.4（中模）/0.8（低模）
相干积累次数	32（高模）/48（中模）/96（低模）
非相干积累次数	4（高模）/4（中模）/4（低模）
谱变换数	512（高模）/512（中模）/512（低模）
谱平均数	4（高模）/4（中模）/4（低模）
距离库长/m	240（高模）/120（中模）/120（低模）
采样起始高度/m	3150（高模）/1110（中模）/150（低模）
采样终止高度/m	10110（高模）/4590（中模）/3630（低模）

下载: 导出CSV

参考文献(26)

[1]	Deng M, Mace G G. 2006. Cirrus microphysical properties and air motion statistics using cloud radar Doppler moments. Part I: Algorithm description [J]. J. Appl. Meteor. Climatol., 45(12): 1690−1709. doi: 10.1175/JAM2433.1
[2]	Frisch A S, Fairall C W, Snider J B. 1995. Measurement of stratus cloud and drizzle parameters in ASTEX with a K_α-band Doppler radar and a microwave radiometer [J]. J. Atmos. Sci., 52(16): 2788−2799. doi:10.1175/1520-0469(1995)052<2788:MOSCAD>2.0.CO;2
[3]	傅云飞. 2014. 利用卫星双光谱反射率算法反演的云参数及其应用 [J]. 气象学报, 72(5): 1039−1053. doi: 10.11676/qxxb2014.087 Fu Y F. 2014. Cloud parameters retrieved by the bispectral reflectance algorithm and associated applications [J]. Acta Meteorologica Sinica (in Chinese), 72(5): 1039−1053. doi: 10.11676/qxxb2014.087
[4]	Gossard E E. 1994. Measurement of cloud droplet size spectra by Doppler radar [J]. J. Atmos. Oceanic Technol., 11(3): 712−726. doi:10.1175/1520-0426(1994)011<0712:MOCDSS>2.0.CO;2
[5]	Gossard E E, Sinder J B, Clothiaux E E, et al. 1997. The potential of 8-mm radars for remotely sensing cloud drop size distributions [J]. J. Atmos. Oceanic Technol., 14(1): 76−87. doi:10.1175/1520-0426(1997)014<0076:TPOMRF>2.0.CO;2
[6]	何平, 朱小燕, 阮征, 等. 2009. 风廓线雷达探测降水过程的初步研究 [J]. 应用气象学报, 20(4): 465−470. doi: 10.3969/j.issn.1001-7313.2009.04.011 He P, Zhu X Y, Ruan Z, et al. 2009. Preliminary study on precipitation process detection using wind profiler radar [J]. Journal of Applied Meteorological Science (in Chinese), 20(4): 465−470. doi: 10.3969/j.issn.1001-7313.2009.04.011
[7]	胡志晋, 严采蘩. 1987. 层状云微物理过程的数值模拟(二)——中纬度气旋云系的微物理过程 [J]. 气象科学研究院院刊, 2(2): 133−142. Hu Z J, Yan C F. 1987. Numerical simulation of microphysical processes of stratiform clouds (II)—Microphysical processes in middle-latitude cyclone cloud systems [J]. Journal of Academy of Meteorological Science (in Chinese), 2(2): 133−142.
[8]	胡志晋, 刘公波, 朱彤. 1996. 暴雨数值预报中云降水方案的研究[M]. 北京: 气象出版社, 593–602 Hu Z J, Liu G B, Zhu T. 1996. Study of Cloud Precipitation Scheme in Storm Numerical Forecast (in Chinese) [M]. Beijing: China Meteorological Press, 593–602.
[9]	黄钰, 阮征, 葛润生, 等. 2011. 风廓线雷达探测零度层亮带的试验研究 [J]. 高原气象, 30(5): 1376−1383. Huang Y, Ruan Z, Ge R S, et al. 2011. Study on bright band detection using wind profiler radar [J]. Plateau Meteorology (in Chinese), 30(5): 1376−1383.
[10]	黄钰, 阮征, 罗秀明, 等. 2015. 垂直探测雷达的降水云分类方法在北京地区的应用 [J]. 高原气象, 34(3): 815−824. doi: 10.7522/j.issn.1000-0534.2014.00014 Huang Y, Ruan Z, Luo X M, et al. 2015. Application in classification of precipitation clouds using vertical sounding radar in Beijing [J]. Plateau Meteorology (in Chinese), 34(3): 815−824. doi: 10.7522/j.issn.1000-0534.2014.00014
[11]	黄钰, 郭学良, 毕凯, 等. 2020. 北京延庆山区降雪云物理特征的垂直观测和数值模拟研究 [J]. 大气科学, 44(2): 356–370. Huang Y, Guo X L, Bi K, et al. 2020. Vertical observation and numerical simulation of the clouds physical characteristics of snow-producing over Yanqing mountain area in Beijing [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(2): 356−370. doi: 10.3878/j.issn.1006-9895.1903.18258
[12]	Kessler E. 1969. On the distribution and continuity of water substance in atmospheric circulations [M]//Kessler E. On the Distribution and Continuity of Water Substance in Atmospheric Circulations. Boston: American Meteorological Society, 1–84. doi: 10.1007/978-1-935704-36-2_1
[13]	李永平, 袁招洪, 王晓峰. 2004. 用多普勒雷达反射率调整模式大气的云微物理变量 [J]. 应用气象学报, 15(6): 658−664. doi: 10.3969/j.issn.1001-7313.2004.06.003 Li Y P, Yuan Z H, Wang X F. 2004. Microphysical adjustments using reflectivity of Doppler radar for meso-scale model [J]. Journal of Applied Meteorological Science (in Chinese), 15(6): 658−664. doi: 10.3969/j.issn.1001-7313.2004.06.003
[14]	刘红亚, 徐海明, 胡志晋, 等. 2007a. 雷达反射率因子在中尺度云分辨模式初始化中的应用. Ⅰ: 云微物理量和垂直速度的反演 [J]. 气象学报, 65(6): 896−905. doi: 10.3321/j.issn:0577-6619.2007.06.007 Liu H Y, Xu H M, Hu Z J, et al. 2007a. Application of radar reflectivity to initialization of cloud resolving mesoscale model. Part I: Retrieval of microphysical parameters and vertical velocity [J]. Acta Meteorologica Sinica (in Chinese), 65(6): 896−905. doi: 10.3321/j.issn:0577-6619.2007.06.007
[15]	刘红亚, 徐海明, 薛纪善, 等. 2007b. 雷达反射率因子在中尺度云分辨模式初始化中的应用. Ⅱ: 数值模拟试验 [J]. 气象学报, 65(6): 906−918. doi: 10.11676/qxxb2007.085 Liu H Y, Xu H M, Xue J S, et al. 2007b. Application of radar reflectivity to initialization of cloud resolving mesoscale model. Part II: Numerical simulation experiments [J]. Acta Meteorologica Sinica (in Chinese), 65(6): 906−918. doi: 10.11676/qxxb2007.085
[16]	刘黎平, 宗蓉, 齐彦斌, 等. 2012. 云雷达反演层状云微物理参数及其与飞机观测数据的对比 [J]. 中国工程科学, 14(9): 64−71. doi: 10.3969/j.issn.1009-1742.2012.09.008 Liu L P, Zong R, Qi Y B, et al. 2012. Microphysical parameters retrieval by cloud radar and comparing with aircraft observation in stratiform cloud [J]. Engineering Science (in Chinese), 14(9): 64−71. doi: 10.3969/j.issn.1009-1742.2012.09.008
[17]	Miller M J, Pearce R P. 1974. A three-dimensional primitive equation model of cumulonimbus convection [J]. Quart. J. Roy. Meteor. Soc., 100(424): 133−154. doi: 10.1002/qj.49710042402
[18]	Rémillard J, Kollias P, Szyrmer W. 2013. Radar-radiometer retrievals of cloud number concentration and dispersion parameter in nondrizzling marine stratocumulus [J]. Atmos. Meas. Tech., 6(7): 1817−1828. doi: 10.5194/amt-6-1817-2013
[19]	阮征, 葛润生, 吴志根. 2002. 风廓线仪探测降水云体结构方法的研究 [J]. 应用气象学报, 13(3): 330−338. doi: 10.3969/j.issn.1001-7313.2002.03.008 Ruan Z, Ge R S, Wu Z G. 2002. Method for detecting rain cloud structure with wind profilers [J]. Journal of Applied Meteorological Science (in Chinese), 13(3): 330−338. doi: 10.3969/j.issn.1001-7313.2002.03.008
[20]	Ruan Z, Ming H, Ma J L, et al. 2014. Analysis of the microphysical properties of a stratiform rain event using an L-Band profiler radar [J]. J. Meteor. Res., 28(2): 268−280. doi: 10.1007/s13351-014-3091-x
[21]	Shupe M D, Kollias P, Poellot M, et al. 2008. On deriving vertical air motions from cloud radar Doppler spectra [J]. J. Atmos. Oceanic Technol., 25(4): 547−557. doi: 10.1175/2007JTECHA1007.1
[22]	苏德斌, 孙成云, 余东昌, 等. 2010. 短临交互预报系统VIPS设计开发与应用 [J]. 气候与环境研究, 15(5): 571−578. doi: 10.3878/j.issn.1006-9585.2010.05.05 Su D B, Sun C Y, Yu D C, et al. 2010. The development and application of a very-short-range interactive prediction system [J]. Climatic and Environmental Research (in Chinese), 15(5): 571−578. doi: 10.3878/j.issn.1006-9585.2010.05.05
[23]	Sun J Z, Crook N A. 1997. Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its Adjoint. Part I: Model development and simulated data experiments [J]. J. Atmos. Sci., 54(12): 1642−1661. doi:10.1175/1520-0469(1997)054<1642:DAMRFD>2.0.CO;2
[24]	陶祖钰, 谢安. 1989. 天气过程诊断分析原理和实践[M]. 北京: 北京大学出版社, 215pp. Tao Z Y, Xie A. 1989. The Weather Process Diagnosis Analysis Theory and Practice (in Chinese) [M]. Beijing: Peking University Press, 215pp.
[25]	王晓蕾, 阮征, 葛润生, 等. 2010. 风廓线雷达探测降水云体中雨滴谱的试验研究 [J]. 高原气象, 29(2): 498−505. Wang X L, Ruan Z, Ge R S, et al. 2010. A study of drop-size distribution in precipitation cloud from wind profile radar [J]. Plateau Meteorology (in Chinese), 29(2): 498−505.
[26]	Williams C R. 2016. Reflectivity and liquid water content vertical decomposition diagrams to diagnose vertical evolution of raindrop size distributions [J]. J. Atmos. Oceanic Technol., 33(3): 579−595. doi: 10.1175/JTECH-D-15-0208.1