Li Te, Zheng Youfei, Wang Liwen, et al. Ice cloud distribution and seasonal migration over land area of China based on MODIS data. J Appl Meteor Sci, 2017, 28(6): 724-736. DOI:  10.11898/1001-7313.20170608.
Citation: Li Te, Zheng Youfei, Wang Liwen, et al. Ice cloud distribution and seasonal migration over land area of China based on MODIS data. J Appl Meteor Sci, 2017, 28(6): 724-736. DOI:  10.11898/1001-7313.20170608.

Ice Cloud Distribution and Seasonal Migration over Land Area of China Based on MODIS Data

DOI: 10.11898/1001-7313.20170608
  • Received Date: 2017-03-13
  • Rev Recd Date: 2017-09-15
  • Publish Date: 2017-11-30
  • Ice clouds have an important impact on the global climate, and ice cloud features vary with convection and weather system. Mid-latitude ice clouds originate from the convective cloud system and the atmospheric circulation in the atmosphere, but the understanding on the formation of ice crystals in clouds is still lacking. Non-spherical ice crystal particles have also posed a great challenge to the accurate calculation of the ice cloud in the climate model. Due to limitations of aircraft observation and remote sensing, the observation of ice clouds depends mainly on satellite remote sensing. Based on moderate resolution imaging spectrometer (MODIS) cloud product level-3 data (MOD08_M3), the probability distribution of ice cloud, ice cloud optical thickness, ice cloud effective radius and ice water path over China from November 2011 to October 2016 are analyzed, and the distribution and seasonal migration are discussed. The horizontal distribution and trend of ice cloud attributes in different seasons are studied emphatically. Main conclusions are as follows. The occurrence probability of ice clouds is higher in the northeastern part of the Qinghai-Tibet Plateau during winter, spring and autumn, mainly due to the warm and humid air raised by the northeast slope of the Qinghai-Tibet Plateau. The occurrence probability of ice clouds in low latitudes in summer is related to monsoon and the intertropical convergence zone. The overall occurrence probability of ice clouds is on the rise, especially in the summer of 2016. The horizontal distribution of effective radius of ice cloud is increasing from southwest to northeast, mainly due to the difference of temperature distribution. Through the year, the effective low radius of the ice particles appears in the southwest region, and the high value appears in the northeastern region during the winter, spring and autumn, and appears in Xinjiang area during summer. The ice cloud effective particle radius is larger in high latitudes than in low latitudes, and the overall seasonal variation is not obvious. The horizontal distribution and seasonal changes of ice cloud thickness and ice water path are roughly the same, showing the downward trend from southeast to northwest. The large value of ice cloud optical thickness and ice water path are mainly in the southern region. The minimum value appears in the northern part of Xinjiang, which is mainly related to the air vapor content and the East Asian Monsoon. The ice cloud optical thickness and ice water path are larger in monsoon area than in non-monsoon zone. There is little difference in the distribution of ice thickness between ice age and ice water, and large value areas are in the southern region. Seasonal changes in northwest, northern and the Qinghai-Tibet Plateau regions are relatively significant.
  • Fig. 1  Regional division of China

    Fig. 2  Seasonal probability distribution of ice clouds from Nov 2011 to Oct 2016

    Fig. 3  Occurrence probability trend of ice clouds in different regions of China from Nov 2011 to Oct 2016

    Fig. 4  Seasonal distribution of ice clouds effective radius from Nov 2011 to Oct 2016

    Fig. 5  The effective radius trend of ice clouds in different regions of China from Nov 2011 to Oct 2016

    Fig. 6  Seasonal distribution of ice clouds optical thickness from Nov 2011 to Oct 2016

    Fig. 7  The optical thickness trend of ice clouds in different regions of China from Nov 2011 to Oct 2016

    Fig. 8  Seasonal distribution of ice water path from Nov 2011 to Oct 2016

    Fig. 9  The ice water path trend in different regions of China from Nov 2011 to Oct 2016

    Table  1  The seasonal average of ice clouds in different regions of China(unit: %)

    区域 冬季 春季 夏季 秋季
    中国区域 21.1 28.2 35.3 23.4
    西北地区 26.7 30.7 22.5 21.6
    北方地区 23.5 29.2 31.0 23.6
    青藏高原地区 16.1 29.4 37.0 16.5
    西南地区 12.8 28.7 47.6 22.5
    南方地区 11.9 27.3 47.5 23.3
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    Table  2  The seasonal average of ice clouds effective radius in different regions of China(unit: μm)

    区域 冬季 春季 夏季 秋季
    中国区域 32.9 32.8 32.9 33.2
    西北地区 33.6 32.8 35.5 33.8
    北方地区 36.9 35.0 34.8 36.1
    青藏高原地区 29.8 31.5 31.8 31.4
    西南地区 27.9 29.4 28.8 29.9
    南方地区 29.4 31.3 31.3 32.1
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    Table  3  The seasonal average of ice clouds optical thickness in different regions of China

    区域 冬季 春季 夏季 秋季
    中国区域 11.2 10.9 14.1 12.7
    西北地区 9.8 8.6 12.9 10.7
    北方地区 8.6 9.8 14.0 12.6
    青藏地区 9.4 11.1 13.7 11.3
    西南地区 12.9 12.3 14.4 15.3
    南方地区 16.8 17.2 16.2 17.1
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  • [1]
    Hartmann D L, Ockert-Bell M E, Michelsen M L.The effect of cloud type on Earth's energy balance:Global analysis.J Climate, 1992, 5(11):1281-1304. doi:  10.1175/1520-0442(1992)005<1281:TEOCTO>2.0.CO;2
    [2]
    Liou K N.Influence of cirrus clouds on weather and climate processes:A global perspective.Mon Wea Rev, 1986, 114(6):1167-1199. doi:  10.1175/1520-0493(1986)114<1167:IOCCOW>2.0.CO;2
    [3]
    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.大气与环境光学学报, 2013, 8(4):271-281. http://d.wanfangdata.com.cn/Periodical/dqyhjgxxb201304004
    [4]
    Waliser D E, Li J L F, Woods C P, et al.Cloud ice:A climate model challenge with signs and expectations of progress.Journal of Geophysical Research:Atmospheres, 2009, 114(D8):D00A21, DOI: 10.1029/2008jd010015.
    [5]
    易欣, 卢均, 何锡玉, 等.利用MODIS可见光和1.38通道反演卷云反射率.气象科学, 2008, 28(1):62-67. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=qxkx200801012&dbname=CJFD&dbcode=CJFQ
    [6]
    Meyer K, Yang P, Gao B C.Ice cloud optical depth from MODIS cirrus reflectance.IEEE Geoscience and Remote Sensing Letters, 2007, 4(3):471-474. doi:  10.1109/LGRS.2007.897428
    [7]
    张国栋.冰云短波辐射特性参数化.应用气象学报, 1997, 8(3):283-291. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19970341&flag=1
    [8]
    孙治安, Keith P.混合云在GCM气候模拟中的重要性.应用气象学报, 1996, 7(4):452-459. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19960469&flag=1
    [9]
    丁守国, 赵春生, 石广玉, 等.近20年全球总云量变化趋势分析.应用气象学报, 2005, 16(5):670-677. doi:  10.11898/1001-7313.20050514
    [10]
    Chen B, Liu X.Seasonal migration of cirrus clouds over the Asian Monsoon regions and the Tibetan Plateau measured from MODIS/Terra.Geophys Res Lett, 2005, 32:67-106. doi:  10.1029/2004GL020868
    [11]
    Meyer K, Yang P, Gao B C.Tropical ice cloud optical depth, ice water path, and frequency fields inferred from the MODIS level-3 data.Atmos Res, 2007, 85(2):171-182. doi:  10.1016/j.atmosres.2006.09.009
    [12]
    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.高原气象, 2014, 33(4):1105-1118. doi:  10.7522/j.issn.1000-0534.2013.00026
    [13]
    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.大气与环境光学学报, 2013, 8(4):271-281. http://d.wanfangdata.com.cn/Periodical/dqyhjgxxb201304004
    [14]
    杨亦萍, 董晓刚, 戴聪明, 等.利用MODIS数据对北极夏季卷云特性的研究.红外与激光工程, 2016, 45(4):432002-0432002(8). http://d.wanfangdata.com.cn/Periodical/hwyjggc201604005
    [15]
    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.应用气象学报, 2005, 16(5):678-684. doi:  10.11898/1001-7313.20050515
    [16]
    吴晓, 游然, 王雯燕, 等.基于MODIS云宏微观特性的卫星云分类方法.应用气象学报, 2016, 27(2):201-208. doi:  10.11898/1001-7313.20160208
    [17]
    刘瑞霞, 陈洪滨, 郑照军, 等.总云量产品在中国区域的分析检验.应用气象学报, 2009, 20(5):571-578. doi:  10.11898/1001-7313.20090508
    [18]
    King M D, Menzel W P, Kaufman Y J, et al.Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS.IEEE Transactions on Geoscience & Remote Sensing, 2003, 41(2):442-458. http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=1196060
    [19]
    王帅辉, 韩志刚, 姚志刚, 等.基于CloudSat资料的中国及周边地区各类云的宏观特征分析.气象学报, 2011, 69(5):883-899. doi:  10.11676/qxxb2011.077
    [20]
    闵敏, 王普才, 宗雪梅.中国地区卷云分布特征的星载激光雷达遥感.气候与环境研究, 2011, 16(3):301-309. http://d.wanfangdata.com.cn/Periodical/qhyhjyj201103005
    [21]
    杜亮亮. 青藏高原东北边坡地带云水资源分析及夏季云量中短期预报方法研究. 兰州: 兰州大学, 2012. http://cdmd.cnki.com.cn/Article/CDMD-10730-1012375053.htm
    [22]
    陈勇航, 黄建平, 王天河, 等.西北地区不同类型云的时空分布及其与降水的关系.应用气象学报, 2005, 16(6):717-727. doi:  10.11898/1001-7313.20050612
    [23]
    Gao B C, Yang P, Guo G, et al.Measurements of water vapor and high clouds over the Tibetan Plateau with the Terra MODIS instrument.IEEE Transactions on Geoscience & Remote Sensing, 2003, 41(4):895-900. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1202951
    [24]
    刘瑞霞, 刘玉洁, 杜秉玉.中国云气候特征的分析.应用气象学报, 2004, 15(4):468-476. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20040456&flag=1
    [25]
    曹亚楠, 陈秀红, 魏合理.卷云高度对大气的红外光谱辐射影响的研究.红外与激光工程, 2012, 41(8):1965-1970. http://d.wanfangdata.com.cn/Periodical/hwyjggc201208001
    [26]
    段皎, 刘煜.中国地区云光学厚度和云滴有效半径变化趋势.气象科技, 2011, 39(4):408-416. http://d.wanfangdata.com.cn/Periodical/qxkj201104004
    [27]
    杨大生, 王普才.中国地区夏季云粒子尺寸的时空分布特征.气候与环境研究, 2012, 17(4):433-443. doi:  10.3878/j.issn.1006-9585.2011.10066
    [28]
    Liou K N, Davies R.Radiation and Cloud Processes in the Atmosphere.The Greek New Testament.United Bible Societies, 1968:507-508.
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    • Received : 2017-03-13
    • Accepted : 2017-09-15
    • Published : 2017-11-30

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