基于 MODIS 和 CloudSat 的京津冀降水冰云季节分布特征

doi:10.12118/j.issn.1000-6060.2020.06.05

摘要/Abstract

摘要： 利用 2008 年 9 月~2016 年 8 月 Aqua MODIS 和 CloudSat 卫星数据，筛选出京津冀地区的降水冰云，同时将其分为 4 个区域讨论，得到关于该地区降水冰云 4 个季节的分布特征，为该地区的人工影响天气提供依据。结果表明：京津冀整个地区的降水冰云在夏季的发生率都较高，且发生率有上升的趋势。从整个地区看来，京津冀地区的降水冰云的云顶高度在冬季最低、夏季最高，云顶温度的最小值在冬季最高、夏季最低；京津冀地区的降水冰云在春夏秋 3 季均以单层云为主，而在冬季则以双层云为主；京津冀地区的降水冰云的类型按春夏秋冬分别为 7 种、7 种、6 种和 5 种，且在夏季该地区的降水冰云以深对流云为主（占 48.3%），而其他季节以雨层云为主；京津冀地区降水冰云微物理量（包括冰水含量、粒子数浓度、粒子有效半径）主要分布高度分别为 0~13.5 km（春季）、 3.5~17.0 km（夏季）、1.0~14.0 km（秋季）、0~11.0 km（冬季）。冰水含量、粒子有效半径和粒子数浓度的分布高度和最大值均在夏季最高，但粒子有效半径在秋季最低，冰水含量和粒子数浓度在冬季最低。这 3 种微物理量随高度的分布特征夏季在京津冀各分区较为一致，都呈单峰结构，在其他季节差异较大。

关键词: 京津冀, 降水, 冰云, 季节特征, CloudSat

Abstract: Beijing-Tianjin-Hebei is a region where water resources are scarce. Studying nonprecipitating and precipitating ice clouds is helpful for understanding the artificial precipitation enhancement potential and precipitation mechanism. Using the cloud product of CloudSat and Aqua MODIS from September 2008 to August 2016, the Beijing- Tianjin- Hebei region was divided into four sub- areas to study the distribution of precipitating ice clouds, including the occurrence probability, cloud top height and cloud top temperature, the number of cloud layers, cloud type, ice water content, particle concentration, and particle effective radius in the Beijing- Tianjin- Hebei region. Results show that the occurrence probability of precipitating ice clouds in Beijing-Tianjin-Hebei region is higher in summer with increasing incidence rate. The occurrence probability of precipitating ice clouds in 2012 is observed to be the highest, while the occurrence probability of precipitating ice clouds after 2012 is higher than that of the precipitating ice clouds before 2012. The cloud top height of the precipitating ice clouds cloud top in Beijing- Tianjin- Hebei is lowest in winter and the highest in summer. The minimum clout top temperature of the precipitating ice clouds in Beijing- Tianjin- Hebei is the highest in winter and the lowest in summer. The types of precipitation ice clouds in the Beijing-Tianjin-Hebei area are 7, 6, 6, and 5 in spring, summer, autumn, and winter, respectively. The precipitating ice clouds in this area are mainly deep convective clouds in summer (48.3%), while others are dominanted by nimbostratus. The main distribution height of the precipitating ice clouds’microphysical quantities (including ice water content, particle concentration, and particle effective radius) are 0- 13.5 km, 3.5- 17.0 km, 1.0- 14.0 km, and 0- 11.0 km according to the four seasons. The distribution height and the maximum value of ice water content and particle concentration are the lowest in winter and the highest in summer. The maximum height is the lowest in winter and highest in summer, and the maximum particle effective radius is the lowest in autumn and the highest in summer. In addition, in summer, the distribution characteristics of these three microphysical quantities with height are relatively consistent in Beijing-Tianjin-Hebei in summer with all having a single-peak structure.

Key words: Beijing-Tianjin-Hebei, precipitation, ice clouds, seasonal characteristics, CloudSat

郑倩, 郑有飞, 王立稳, 高雅 . 基于 MODIS 和 CloudSat 的京津冀降水冰云季节分布特征[J]. 干旱区地理, 2020, 43(6): 1446-1455.

ZHENG Qian, ZHENG You-fei, WANG Li-wen, Gao Ya. Seasonal distribution characteristics of precipitating ice clouds in Beijing- Tianjin-Hebei region based on MODIS and CloudSat[J]. Arid Land Geography, 2020, 43(6): 1446-1455.

参考文献 32

[1]	周毓荃, 蔡淼, 欧建军, 等. 云特征参数与降水相关性的研究[J]. 大气科学学报, 2011, 34(6): 641- 652. [ZHOU Yuquan, CAI Miao, OU Jianjun, et al. Correlation between cloud characteristic parameters and precipitation[J]. Transactions of Atmospheric Sci⁃ ences, 2011, 34(6): 641-652. ]
[2]	刘健, 董超华, 朱元竞, 等. FY-1C 资料在云顶粒子热力学相态分析中的应用研究[J]. 大气科学, 2003, 27(5): 901-908. [LIU Ji⁃ an, DONG Chaohua, ZHU Yuanjing, et a1. Thermodynamic phase analysis of cloud particles with FY-1C data[J]. Chinese Journal of Atmospheric Sciences, 2003, 27(5): 901-908. ]
[3]	李特, 郑有飞, 王立稳, 等. 基于 MODIS 产品的中国陆地冰云季节变化特征 [J]. 应用气象学报, 2017, (6): 724- 736. [LI Te, ZHENG Youfei, WANG Liwen, et al. Ice cloud distribution and sea⁃ sonal migration over land area of China based on MODIS data[J]. Journal of Applied Meterological Science, 2017, (6): 724-736. ]
[4]	MEYER K, YANG P, GAO B C. Tropical ice cloud optical depth, ice water path, and frequency fields inferred from the MODIS lev⁃ el-3 data[J]. Atmospheric Research, 2007, 85(2): 171-182.
[5]	曹亚楠, 魏合理, 徐青山. 基于 MODIS 云产品的北京地区卷云特性统计分析[J]. 大气与环境光学学报, 2013, 8(4): 271-281. [CAO Yanan, WEI Heli, XU Qingshan. Statistics analysis of cirrus properties in Beijing region based on MODIS cloud products[J]. Journal of Atmospheric and Environmental Optics, 2013, 8(4): 271-281. ]
[6]	赵姝慧. 利用 TRMM 卫星和 CloudSat 卫星对不同类型云系的中微尺度结构的研究分析[D]. 南京: 南京信息工程大学, 2008. [ZHAO Shuhui. A study on the mesoscale and microscale struc⁃ ture in different types of clouds by TRMM satellite and Cloudsat satellite[D]. Nanjing: Nanjing University of Information Science and Technology, 2008. ]
[7]	STEIN T H M, DELANË J, HOGAN R, et al. A comparison among four different retrieval methods for ice-cloud properties using data from CloudSat, CALIPSO, and MODIS[J]. Journal of Applied Mete⁃ orology and Climatology, 2011, 50(9): 1952-1969
[8]	KUEHNLEIN M, APPELHANS T, THIES B, et al. An evaluation of a semi- analytical cloud property retrieval using MSG SEVIRI, MODIS and CloudSat[J]. Atmospheric Research, 2013, 122 (MAR. ): 111-135.
[9]	HONG Y, LIU G. Global ice cloud properties based on CALIPSO and CloudSat measurements and their radiative effect[C]//AGU Fall Meeting Abstracts, 2013.
[10]	赵宇, 朱皓清, 蓝欣, 等. 基于 CloudSat 资料的北上江淮气旋暴雪云系结构特征[J]. 地球物理学报, 61(12): 4789-4804. [ZHAO Yu, ZHU Haoqing, LAN Xin, et al. Structure of the snowstorm cloud associated with northward Jiang-Huai cyclone based on Cloudsat sat⁃ ellite data[J]. Chinese Journal of Geophysics, 2018, 61(12): 4789- 4804. ]
[11]	刘屹岷, 燕亚菲, 吕建华, 等. 基于 CloudSat/CALIPSO 卫星资料的青藏高原云辐射及降水的研究进展[J]. 大气科学, 2018, 42 (4): 847- 858. [LIU Yimin, YAN Yafei, LYU Jianhua, et al. Re⁃ view of current investigations of cloud, radiation and rainfall over the Tibetan Plateau with the CloudSat/CALIPSO dataset[J]. Chi⁃ nese Journal of Atmospheric Sciences, 2018, 42(4): 847-858. ]
[12]	尚博. 利用 CloudSat 对华北、江淮云垂直结构及降水云特征的研究 [D]. 南京: 南京信息工程大学, 2011. [SHANG Bo. Re⁃ search on vertical structure of cloud and precipitation feature of CloudSat data in north China and Jianghuai[D]. Nanjing: Nanjing University of Information Science and Technology, 2011. ]
[13]	刘旸, 赵姝慧, 蔡波, 等. 基于 CloudSat 资料的东北地区降水云及非降水云垂直结构特征对比分析 [J]. 气象, 2017, 43(11): 1374-1382. [LIU Wei, ZHAO Shuhui, CAI Bo, et al. Comparison of vertical structure between precipitation cloud and non-precipita⁃ tion cloud based on CloudSat data over northeast China[J]. Meteo⁃ rology, 2017, 43(11): 1374-1382. ]
[14]	ROSS A, HOLZ R E, ACKERMAN S A. Correlations of oriented ice and precipitation in marine midlatitude low clouds using collo⁃ cated CloudSat, CALIOP, and MODIS observations[J]. Journal of Geophysical Research: Atmospheres, 2017, 122(15): 8056-8070.
[15]	李晨蕊, 王天河, 吕巧谊, 等. 基于 CloudSat 的东亚和南亚季风区降水云特征分析[J]. 兰州大学学报(自然科学版), 2018, 54 (3): 345- 355. [LI Chenrui, WANG Tianhe, LYU Qiaoyi, et al. Characteristics of precipitating cloud over East and South Asian monsoon region based on CloudSat[J]. Journal of Lanzhou Univer⁃ sity: Natural Sciences, 2018, 54(3): 345-355. ]
[16]	郑倩, 郑有飞, 王立稳, 等. 京津冀夏季强降水下冰云宏微观特征[J]. 干旱区地理, 2019, 42(1): 67-76. [ZHENG Qian, ZHENG Youfei, WANG Liwen, et al. The macrophysical and microphysi⁃ cal properties of ice clouds during heavy rainfalls in Beijing-Tian⁃ jin-Hebei region in summer[J]. Arid Land Geography, 2019, 42(1): 67-76. ]
[17]	鲍超, 贺东梅. 京津冀城市群水资源开发利用的时空特征与政策启示[J]. 地理科学进展, 2017, 36(1): 58-67. [BAO Chao, HE Dongmei. Spatiotemporal characteristics of water resources exploita⁃ tion and policy implications in the Beijing-Tianjin-Hebei urban ag⁃ glomeration[J]. Progress in Geography, 2017, 36(1): 58-67. ]
[18]	周著华, 白洁, 刘健文, 等. MODIS 多光谱云相态识别技术的应用研究 [J]. 应用气象学报, 2005, 16(5): 678- 684. [ZHOU Zhuhua, BAI Jie, LIU Jianwen, et al. The application of cloud phase recognition by MODIS spectral data[J]. Journal of Applied Meterological Science, 2005, 16(5): 678-684. ]
[19]	郑倩, 郑有飞, 王立稳, 等. 京津冀地区夏季降水冰云和非降水冰云云特征对比分析 [J]. 气候与环境研究, 2020, 25(1): 77-89. [ZHENG Qian, ZHENG Youfei, WANG Liwen, et al. Comparative analysis of the features of precipitating and nonprecipitating ice clouds in the Beijing-Tianjin-Hebei region in summer[J]. Climatic and Environmental Research, 2020, 25(1): 77-89. ]
[20]	林彤, 郑有飞, 李特, 等. 基于卫星资料的中国西北地区冰云特征分析 [J]. 高原气象, 2018, 37(4): 1051- 1060. [LIN Tong, ZHENG Youfei, LI Te, et al. The characteristics of ice cloud prop⁃ erties derived from satellite data in northwest China[J]. Plateau Meteorology, 2018, 37(4): 1051-1060. ]
[21]	温煦. 京津冀地区暖季降水特征分析 [D]. 兰州: 兰州大学, 2016. [WEN Xu. Characteristics of warm-season precipitation over Beijing-Tianjin-Hebei [D]. Lanzhou: Lanzhou University, 2016. ]
[22]	梁苏洁, 程善俊, 郝立生, 等. 1970—2015 年京津冀地区暖季小时降水变化特征[J]. 暴雨灾害, 2018, 37(2): 105-114. [LIANG Sujie, CHENG Shanjun, HAO Lisheng, et al. Analysis on the char⁃ acteristics of hourly precipitation variations in Beijing-Tianjin-He⁃ bei region during 1970—2015 [J]. Torrential Rain and Disasters, 2018, 37(2): 105-114. ]
[23]	尚博, 周毓荃, 刘建朝, 等. 基于 Cloudsat 的降水云和非降水云垂直特征 [J]. 应用气象学报, 2012, 23(1): 1- 9. [SHANG Bo, ZHOU Yuquan, LIU Jianchao, et al. Comparing vertical structure of precipitation cloud and non- precipitation cloud using Cloudsat [J]. Journal of Applied Meterological Science, 2012, 23(1): 1-9. ]
[24]	WANG J H, ROSSOW W B. Effects of cloud vertical structure on atmospheric circulation in the GISS GCM[J]. Journal of Climate, 1998, 11: 3010-3029.
[25]	游景炎, 段英, 游来光. 云降水物理和人工增雨技术研究[M]. 北京: 气象出版社, 1994. [YOU Jingyan, DUAN Ying, YOU Lai⁃ guang. The research of cloud and precipitation physics and weath⁃ er modification[M]. Beijing: China Meteorological Press, 1994. ]
[26]	邓军英. 云卫星在降水云研究中的应用[D]. 上海: 东华大学, 2014. [DENG Junying. Application of CloudSat in the study of pre⁃ cipitation clouds[D]. Shanghai: Donghua University, 2014. ]
[27]	SASSEN K, WANG Z. Classifying clouds around the globe with the CloudSat radar: 1 year of results[J]. Geophysical Research Let⁃ ters, 2008, 35(4): L04805, doi: 10.1029/2007GL032591.
[28]	AUSTIN R T, HEYMSFIELD A J, STEPHENS G L. Retrieval of ice cloud microphysical parameters using the CloudSat millimeter wave radar and temperature[J]. Journal of Geophysical Research: Atmospheres, 2009, 114(D8), doi:10.1029/2008JD010049.
[29]	光莹, 邓军英, 陈勇航, 等. 层状云微物理属性垂直分布的季节变化——以新疆地区为例[J]. 干旱区地理, 2017, 40(4): 754- 761. [GUANG Ying, DENG Junying, CHEN Yonghang, et al. Ver⁃ tical distribution and its seasonal variation of microphysical prop⁃ erties of stratiform clouds in Xinjiang[J]. Arid Land Geography, 2017, 40(4): 754-761. ]
[30]	张华, 杨冰韵, 彭杰, 等. 东亚地区云微物理量分布特征的 CloudSat 卫星观测研究 [J]. 大气科学, 2015, 39(2): 235- 248. [ZHANG Hua, YANG Bingyun, PENG Jie, et al. The characteris⁃ tics of cloud microphysical properties in East Asia with the Cloud⁃ Sat dataset[J]. Chinese Journal of Atmospheric Sciences, 2015, 39 (2): 235-248. ]
[31]	杨冰韵, 张华, 彭杰, 等. 利用 CloudSat 卫星资料分析云微物理和光学性质的分布特征[J]. 高原气象, 2014, 33(4): 1105-1118. [YANG Bingyun, ZHANG Hua, PENG Jie, et al. Analysis on glob⁃ al distribution characteristics of cloud microphysical and optical properties based on the CloudSat data[J]. Plateau Meteorology, 2014, 33(4): 1105-1118. ]
[32]	HEYMSFIELD A J, PROTAT A, BOUNIOL D, et al. Testing IWC retrieval methods using radar and ancillary measurements with in situ data[J]. Journal of Applied Meteorology and Climatology, 2008, 47(1): 135－163.