留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

利用静止卫星资料的川渝地区云覆盖特征研究

王健捷 胡秀清 樊丝慧 闵佳园 刘超 张鹏

王健捷,胡秀清,樊丝慧,闵佳园,刘超,张鹏. 2023. 利用静止卫星资料的川渝地区云覆盖特征研究. 气象学报,81(6):1-15 doi: 10.11676/qxxb2023.20230067
引用本文: 王健捷,胡秀清,樊丝慧,闵佳园,刘超,张鹏. 2023. 利用静止卫星资料的川渝地区云覆盖特征研究. 气象学报,81(6):1-15 doi: 10.11676/qxxb2023.20230067
Wang Jianjie, Hu Xiuqing, Fan Sihui, Min Jiayuan, Liu Chao, Zhang Peng. 2023. Cloud cover characteristics in Sichuan-Chongqing region based on geostationary satellite data. Acta Meteorologica Sinica, 81(6):1-15 doi: 10.11676/qxxb2023.20230067
Citation: Wang Jianjie, Hu Xiuqing, Fan Sihui, Min Jiayuan, Liu Chao, Zhang Peng. 2023. Cloud cover characteristics in Sichuan-Chongqing region based on geostationary satellite data. Acta Meteorologica Sinica, 81(6):1-15 doi: 10.11676/qxxb2023.20230067

利用静止卫星资料的川渝地区云覆盖特征研究

doi: 10.11676/qxxb2023.20230067
基金项目: 国家自然科学基金项目(42105135)、国家重点研发课题(2022YFB3902901)。
详细信息
    作者简介:

    王健捷,主要从事卫星云遥感研究。E-mail:15261810356@163.com

    通讯作者:

    胡秀清,主要从事卫星遥感器定标理论及技术方法、遥感反演科学算法和遥感大数据应用研究。E-mail:huxq@cma.gov.cn

  • 中图分类号: P407

Cloud cover characteristics in Sichuan-Chongqing region based on geostationary satellite data

  • 摘要: 利用气象卫星风云四号A星和葵花8号观测资料,根据川渝地区独特的地形、地势将其分为东部低海拔地区和西部高海拔地区,建立高分辨率的网格化无云背景场,作为无云与有云辐射差异对比,使用阈值法进行晴空、水云、冰云、低层云雾、霾和积雪的检测,进而提高云识别信度,统计分析2016—2021年川渝地区云覆盖时、空分布特征。研究表明:川渝地区云的区域分布特征明显,东、西部存在明显差异,总体呈东多西少,云覆盖频率常年存在高值中心,云覆盖面积有明显月变化。东部低海拔地区云覆盖频率常年在70%—80%,而西部高海拔地区云覆盖频率在50%—65%。云覆盖频率的高、低值过渡区对应青藏高原与四川盆地之间的陡峭地形区,这与地形地势、水汽条件和大气环流特征有关。各月的云覆盖面积在东部低海拔地区相对稳定(占比在60%—80%),而西部高海拔地区差异较大。其中东部的冰云和西部的总云面积具有显著月变化(单峰)特征,峰值出现在7月,分别为37%和76%。6 a中各类型云覆盖面积占比年际波动较小,东部的云覆盖面积占比常年超过70%,其中水云占比最大(35%—40%),冰云次之(20%左右),低层云雾最小(约13%);西部的云覆盖面积占比常年约60%(水云24%—26%,冰云22%—25%,低层云雾约10%)。

     

  • 图 1  川渝地区地形地势 (红色实线是近1500 m等高线)

    Figure 1.  Topography of the Sichuan-Chongqing region (the solid red line indicates the elevation contour close to 1500 m)

    图 2  AGRI和AHI的检测算法流程

    Figure 2.  Flowchart of AGRI and AHI detection algorithms

    图 3  检测结果对比 (a. AHI,b. AGRI,c. RGB真彩图,d. CALIOP; AHI和AGRI数据时间是2020年1月1日05时00分、04时53分,相应的CALIOP时间是2020年1月1日05时37分 (世界时,下同);紫色实线为CALIOP的轨迹)

    Figure 3.  Comparison of detection results (a. AHI,b. AGRI,c. RGB true color,d. CALIOP;the AHI and AGRI observations are at 05:00 and 04:53 UTC 1 January 2020,respectively,and simultaneous CALIOP observation is at 05:37 UTC 1 January 2020;the solid purple line represents the CALIOP track)

    图 4  图3,但AHI和AGRI数据时间是2020年4月1日06时00分、05时38分,相应的CALIOP时间是2020年4月1日05时48分

    Figure 4.  Same as Fig. 3 except that the AHI and AGRI observations are at 06:00 and 05:38 UTC 1 April 2020,respectively,and simultaneous CALIOP observation is at 05:48 UTC 1 April 2020

    图 5  图3,但AHI和AGRI数据时间是2019年7月1日06时00分、05时38分,相应的CALIOP时间为2019年7月1日06时02分

    Figure 5.  Same as Fig. 3 except that the AHI and AGRI observations are at 06:00 and 05:38 UTC 1 July 2019,respectively,and simultaneous CALIOP observation is at 06:02 UTC 1 July 2019

    图 6  图3,但AHI和AGRI数据时间是2019年10月5日06时00分、05时38分,相对应的CALIOP时间为2019年10月5日05时54分

    Figure 6.  Same as Fig. 3 except that the AHI and AGRI observations are at 06:00 and 05:38 UTC 5 October 2019,respectively,and simultaneous CALIOP observation is at 05:54 UTC 5 October 2019

    图 7  2019年AHI检测结果 (晴空、水云和冰云) 和CALIOP产品验证对比

    Figure 7.  Comparison of AHI results (clear,water,and ice) and CALIOP products in 2019

    图 8  川渝地区2021年AGRI和AHI的检测结果对比 (a. 东部低海拔,b. 西部高海拔)

    Figure 8.  Comparison of AGRI and AHI results in the Sichuan-Chongqing region during 2021 (a. Low altitude,b. high altitude)

    图 9  2016—2021年月平均云覆盖率分布

    Figure 9.  Distributions of monthly mean cloud cover frequency in each month over 2016—2021

    图 10  2016—2021年云覆盖率空间分布

    Figure 10.  Spatial distributions of cloud cover frequency over 2016—2021

    图 11  2016—2021年东部低海拔 (Low) 和西部高海拔 (High) 地区云覆盖率 (a) 和晴空率 (b) 分布

    Figure 11.  Distributions of cloud cover (a) and clear (b) frequency in the east low-altitude region and the west high-altitude region over 2016—2021

    图 12  2016—2021年东部低海拔地区 (a) 和西部高海拔地区 (b) 各类型面积占比月际变化

    Figure 12.  Monthly variation characteristics of area proportions for all types in the east low-altitude region (a) and the west high-altitude regions (b) over 2016—2021

    图 13  2016—2021年东部低海拔地区 (a) 和西部高海拔地区 (b) 各类型面积占比逐年变化情况

    Figure 13.  Annual variation characteristics of area proportions for all types in the east low-altitude region (a) and the west high-altitude region (b) over 2016—2021

    表  1  所用AGRI和AHI通道

    Table  1.   AGRI and AHI channels used for the present study

    通道中心波长 ( μm ) AGRI AHI
    中心波长
    光谱带宽( μm )
    分辨率 ( km ) 中心波长
    光谱带宽( μm )
    分辨率 ( km )
    0.47 0.47 (0.45—0.49) 1.0 0.47 (0.45—0.49) 1.0
    0.65 0.65 (0.55—0.75) 0.5—1.0 0.64 (0.63—0.66) 0.5
    1.61 1.61 (1.58—1.64) 2.0 1.61(1.60—1.62) 2.0
    3.8 3.75 (3.50—4.00) 2.0 3.85 (3.74—3.96) 2.0
    8.5 8.50 (8.00—9.00) 4.0 8.60 (8.44—8.76) 2.0
    11.0 10.80 (10.30—11.30) 4.0 11.20 (11.10—11.30) 2.0
     注:当两个仪器通道的中心波长存在差异时,为表述方便,选择一个数值代表与两者最接近的通道。
    下载: 导出CSV

    表  2  各类型检测方法及阈值

    Table  2.   Methods and thresholds for the detection of each type

    检测类型 通道及阈值 参考文献
    云雾 R(0.47)−BG(0.47)>0.10
    R(0.47)>0.12
    或BTD(11.0−3.8)<−14.0 K
    Frey,et al,2008
    低层云雾 AGRI:ΔR(0.65−1.61)<
    −0.025
    AHI: ΔR(0.65−1.61)<0
    张培等,2019
    Ryu,et al,2020
    Yang,et al,2021
    冰云 AGRI:BT(8.5)<283.0 K且
      BTD(8.5−11.0)>−1.5 K
    AHI:BT(8.5)<285.0 K且
      BTD(8.5−11.0)>−1.0 K
    Baum,et al,2012
    朝鲁门等,2019
    积雪 NDSI>0.36且 DEM≥1500 m Xiao,et al,2001
    Shang,et al,2017
    R(0.47)>0.11
     注:R表示反射率,例如R(0.65)表示0.65 μm通道反射率,ΔR(0.65−1.61)表示两通道反射率差,BT表示亮度温度,例如BT(8.5)表示8.5 μm通道亮度温度,BTD(8.5−11)表示两通道亮温差。
    下载: 导出CSV
  • [1] 朝鲁门,宁小莉,包玉海等. 2019. 基于葵花-8卫星的白天冰云识别初探. 内蒙古农业大学学报(自然科学版),40(2):45-49. Chao L M,Ning X L,Bao Y H,et al. 2019. Preliminary study of identification day ice cloud based on Himawari-8 data. J Inner Mongolia Agric Univ (Nat Sci Ed),40(2):45-49 (in Chinese

    Chao L M, Ning X L, Bao Y H, et al. 2019. Preliminary study of identification day ice cloud based on Himawari-8 data. J Inner Mongolia Agric Univ (Nat Sci Ed), 402): 45-49 (in Chinese)
    [2] 丁守国,赵春生,石广玉等. 2005. 近20年全球总云量变化趋势分析. 应用气象学报,16(5):670-677. Ding S G,Zhao C S,Shi G Y,et al. 2005. Analysis of global total cloud amount variation over the past 20 years. J Appl Meteor Sci,16(5):670-677 (in Chinese

    Ding S G, Zhao C S, Shi G Y, et al. 2005. Analysis of global total cloud amount variation over the past 20 years. J Appl Meteor Sci, 165): 670-677 (in Chinese)
    [3] 李慧晶,刘建西,刘东升等. 2014. 西南地区云量变化特征. 干旱气象,32(2):194-200. Li H J,Liu J X,Liu D S,et al. 2014. Variation characteristics of cloud cover over Southwestern China. J Arid Meteor,32(2):194-200 (in Chinese

    Li H J, Liu J X, Liu D S, et al. 2014. Variation characteristics of cloud cover over Southwestern China. J Arid Meteor, 322): 194-200 (in Chinese)
    [4] 李昀英,寇雄伟,方乐锌等. 2015. 中国东部云-降水对应关系的分析与模式评估. 气象学报,73(4):766-777. Li Y Y,Kou X W,Fang L X,et al. 2015. Analysis and model evaluation of the relationship between clouds and precipitation over Eastern China. Acta Meteor Sinica,73(4):766-777 (in Chinese

    Li Y Y, Kou X W, Fang L X, et al. 2015. Analysis and model evaluation of the relationship between clouds and precipitation over Eastern China. Acta Meteor Sinica, 734): 766-777 (in Chinese)
    [5] 梁潇云,刘屹岷,吴国雄. 2005. 青藏高原隆升对春、夏季亚洲大气环流的影响. 高原气象,24(6):837-845. Liang X Y,Liu Y M,Wu G X. 2005. The impact of Qinghai-Xizang Plateau uplift on Asian general circulation in spring and summer. Plateau Meteor,24(6):837-845 (in Chinese

    Liang X Y, Liu Y M, Wu G X. 2005. The impact of Qinghai-Xizang Plateau uplift on Asian general circulation in spring and summer. Plateau Meteor, 246): 837-845 (in Chinese)
    [6] 刘洪利,朱文琴,宜树华等. 2003. 中国地区云的气候特征分析. 气象学报,61(4):466-473. Liu H L,Zhu W Q,Yi S H,et al. 2003. Climatic analysis of the cloud over China. Acta Meteor Sinica,61(4):466-473 (in Chinese

    Liu H L, Zhu W Q, Yi S H, et al. 2003. Climatic analysis of the cloud over China. Acta Meteor Sinica, 614): 466-473 (in Chinese)
    [7] 刘健,王锡津. 2017. 主要卫星云气候数据集评述. 应用气象学报,28(6):654-665. Liu J,Wang X J. 2017. Assessment on main kinds of satellite cloud climate datasets. J Appl Meteor Sci,28(6):654-665 (in Chinese

    Liu J, Wang X J. 2017. Assessment on main kinds of satellite cloud climate datasets. J Appl Meteor Sci, 286): 654-665 (in Chinese)
    [8] 刘奇,傅云飞,冯沙. 2010. 基于ISCCP观测的云量全球分布及其在NCEP再分析场中的指示. 气象学报,68(5):689-704. Liu Q,Fu Y F,Feng S. 2010. Geographical patterns of the cloud amount derived from the ISCCP and their correlation with the NCEP reanalysis datasets. Acta Meteor Sinica,68(5):689-704 (in Chinese

    Liu Q, Fu Y F, Feng S. 2010. Geographical patterns of the cloud amount derived from the ISCCP and their correlation with the NCEP reanalysis datasets. Acta Meteor Sinica, 685): 689-704 (in Chinese)
    [9] 刘瑞霞,刘玉洁,杜秉玉. 2004. 中国云气候特征的分析. 应用气象学报,15(4):468-476. Liu R X,Liu Y J,Du B Y. 2004. Cloud climatology characteristics of China from ISCCP data. J Appl Meteor Sci,15(4):468-476 (in Chinese

    Liu R X, Liu Y J, Du B Y. 2004. Cloud climatology characteristics of China from ISCCP data. J Appl Meteor Sci, 154): 468-476 (in Chinese)
    [10] 卢乃锰,方翔,刘健等. 2017. 气象卫星的云观测. 气象,43(3):257-267. Lu N M,Fang X,Liu J,et al. 2017. Understanding clouds by meteorological satellite. Meteor Mon,43(3):257-267 (in Chinese

    Lu N M, Fang X, Liu J, et al. 2017. Understanding clouds by meteorological satellite. Meteor Mon, 433): 257-267 (in Chinese)
    [11] 吕巧谊,张玉轩,李积明. 2017. 南半球中高纬度区域不同类型云的辐射特性. 气象学报,75(4):596-606. Lü Q Y,Zhang Y X,Li J M. 2017. Radiative characteristics of various cloud types over southern mid-high latitudes. Acta Meteor Sinica,75(4):596-606 (in Chinese

    Lü Q Y, Zhang Y X, Li J M. 2017. Radiative characteristics of various cloud types over southern mid-high latitudes. Acta Meteor Sinica, 754): 596-606 (in Chinese)
    [12] 牛生杰,陆春松,吕晶晶等. 2016. 近年来中国雾研究进展. 气象科技进展,6(2):6-19. Niu S J,Lu C S,Lü J J,et al. 2016. Advances in fog research in China. Adv Meteor Sci Technol,6(2):6-19 (in Chinese

    Niu S J, Lu C S, Lü J J, et al. 2016. Advances in fog research in China. Adv Meteor Sci Technol, 62): 6-19 (in Chinese)
    [13] 吴国雄,毛江玉,段安民等. 2004. 青藏高原影响亚洲夏季气候研究的最新进展. 气象学报,62(5):528-540. Wu G X,Mao J Y,Duan A M,et al. 2004. Recent progress in the study on the impacts of Tibetan Plateau on Asian summer climate. Acta Meteor Sinica,62(5):528-540 (in Chinese

    Wu G X, Mao J Y, Duan A M, et al. 2004. Recent progress in the study on the impacts of Tibetan Plateau on Asian summer climate. Acta Meteor Sinica, 625): 528-540 (in Chinese)
    [14] 肖递祥,杨康权,俞小鼎等. 2017. 四川盆地极端暴雨过程基本特征分析. 气象,43(10):1165-1175. Xiao D X,Yang K Q,Yu X D,et al. 2017. Characteristics analyses of extreme rainstorm events in Sichuan Basin. Meteor Mon,43(10):1165-1175 (in Chinese

    Xiao D X, Yang K Q, Yu X D, et al. 2017. Characteristics analyses of extreme rainstorm events in Sichuan Basin. Meteor Mon, 4310): 1165-1175 (in Chinese)
    [15] 徐兴奎. 2012. 中国区域总云量和低云量分布变化. 气象,38(1):90-95. Xu X K. 2012. Spatiotemporal variation of total cloud and low cloud over China. Meteor Mon,38(1):90-95 (in Chinese

    Xu X K. 2012. Spatiotemporal variation of total cloud and low cloud over China. Meteor Mon, 381): 90-95 (in Chinese)
    [16] 张华,荆现文. 2016. 气候模式中云的垂直重叠及其辐射传输问题研究进展. 气象学报,74(1):103-113. Zhang H,Jing X W. 2016. Advances in studies of cloud overlap and its radiative transfer issues in the climate models. Acta Meteor Sinica,74(1):103-113 (in Chinese

    Zhang H, Jing X W. 2016. Advances in studies of cloud overlap and its radiative transfer issues in the climate models. Acta Meteor Sinica, 741): 103-113 (in Chinese)
    [17] 张培,吴东. 2019. 基于Himawari-8数据的日间海雾检测方法. 大气与环境光学学报,14(3):211-220. Zhang P,Wu D. 2019. Daytime sea fog detection method using Himawari-8 data. J Atmos Environ Opt,14(3):211-220 (in Chinese

    Zhang P, Wu D. 2019. Daytime sea fog detection method using Himawari-8 data. J Atmos Environ Opt, 143): 211-220 (in Chinese)
    [18] 张琪,李跃清,陈权亮等. 2011. 近46年西南地区云量的时空变化特征. 高原气象,30(2):339-348. Zhang Q,Li Y Q,Chen Q L,et al. 2011. Temporal and spatial distributions of cloud cover over Southwest China in recent 46 years. Plateau Meteor,30(2):339-348 (in Chinese

    Zhang Q, Li Y Q, Chen Q L, et al. 2011. Temporal and spatial distributions of cloud cover over Southwest China in recent 46 years. Plateau Meteor, 302): 339-348 (in Chinese)
    [19] Baum B A,Menzel W P,Frey R A,et al. 2012. MODIS cloud-top property refinements for collection 6. J Appl Meteor Climatol,51(6):1145-1163 doi: 10.1175/JAMC-D-11-0203.1
    [20] Chen D D,Guo J P,Wang H Q,et al. 2018. The cloud top distribution and diurnal variation of clouds over East Asia:Preliminary results from advanced Himawari imager. J Geophys Res Atmos,123(7):3724-3739 doi: 10.1002/2017JD028044
    [21] Chen Y L,Chen G C,Cui C G,et al. 2020. Retrieval of the vertical evolution of the cloud effective radius from the Chinese FY-4 (Feng Yun 4) next-generation geostationary satellites. Atmos Chem Phys,20(2):1131-1145 doi: 10.5194/acp-20-1131-2020
    [22] Da C. 2015. Preliminary assessment of the advanced Himawari imager (AHI) measurement onboard Himawari-8 geostationary satellite. Remote Sens Lett,6(8):637-646 doi: 10.1080/2150704X.2015.1066522
    [23] Dessler A E. 2010. A determination of the cloud feedback from climate variations over the past decade. Science,330(6010):1523-1527 doi: 10.1126/science.1192546
    [24] Frey R A,Ackerman S A,Liu Y H,et al. 2008. Cloud detection with MODIS. Part I:Improvements in the MODIS cloud mask for collection 5. J Atmos Ocean Technol,25(7):1057-1072 doi: 10.1175/2008JTECHA1052.1
    [25] Liu Y H,Ackerman S A,Maddux B C,et al. 2010. Errors in cloud detection over the Arctic using a satellite imager and implications for observing feedback mechanisms. J Climate,23(7):1894-1907 doi: 10.1175/2009JCLI3386.1
    [26] Liu Z Y,Vaughan M,Winker D,et al. 2009. The CALIPSO lidar cloud and aerosol discrimination:Version 2 algorithm and initial assessment of performance. J Atmos Ocean Technol,26(7):1198-1213 doi: 10.1175/2009JTECHA1229.1
    [27] Myers T A,Scott R C,Zelinka M D,et al. 2021. Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity. Nat Climate Change,11(6):501-507 doi: 10.1038/s41558-021-01039-0
    [28] Platnick S,King M D,Ackerman S A,et al. 2003. The MODIS cloud products:Algorithms and examples from Terra. IEEE Trans Geosci Remote Sens,41(2):459-473 doi: 10.1109/TGRS.2002.808301
    [29] Ryu H S,Hong S. 2020. Sea fog detection based on normalized difference snow index using advanced Himawari imager observations. Remote Sens,12(9):1521 doi: 10.3390/rs12091521
    [30] Scott R C,Myers T A,Norris J R,et al. 2020. Observed sensitivity of low-cloud radiative effects to meteorological perturbations over the global oceans. J Climate,33(18):7717-7734 doi: 10.1175/JCLI-D-19-1028.1
    [31] Shang H Z,Chen L F,Letu H,et al. 2017. Development of a daytime cloud and haze detection algorithm for Himawari-8 satellite measurements over central and eastern China. J Geophys Res Atmos,122(6):3528-3543 doi: 10.1002/2016JD025659
    [32] Wang X,Min M,Wang F,et al. 2019. Intercomparisons of cloud mask products among Fengyun-4A,Himawari-8,and MODIS. IEEE Trans Geosci Remote Sens,57(11):8827-8839 doi: 10.1109/TGRS.2019.2923247
    [33] Winker D M,Vaughan M A,Omar A,et al. 2009. Overview of the CALIPSO mission and CALIOP data processing algorithms. J Atmos Ocean Technol,26(11):2310-2323 doi: 10.1175/2009JTECHA1281.1
    [34] Xiao X M,Shen Z X,Qin X G. 2001. Assessing the potential of VEGETATION sensor data for mapping snow and ice cover:A normalized difference snow and ice index. Int J Remote Sens,22(13):2479-2487 doi: 10.1080/01431160119766
    [35] Xu W J,Lyu D. 2021. Evaluation of cloud mask and cloud top height from Fengyun-4A with MODIS cloud retrievals over the Tibetan Plateau. Remote Sens,13(8):1418 doi: 10.3390/rs13081418
    [36] Yang J,Zhang Z Q,Wei C Y,et al. 2017. Introducing the new generation of Chinese geostationary weather satellites,Fengyun-4. Bull Amer Meteor Soc,98(8):1637-1658 doi: 10.1175/BAMS-D-16-0065.1
    [37] Yang J H,Yoo J M,Choi Y S. 2021. Advanced dual-satellite method for detection of low stratus and fog near Japan at dawn from FY-4A and Himawari-8. Remote Sens,13(5):1042 doi: 10.3390/rs13051042
    [38] Zhou C,Zelinka M D,Klein S A. 2016. Impact of decadal cloud variations on the earth's energy budget. Nat Geosci,9(12):871-874 doi: 10.1038/ngeo2828
  • 加载中
图(13) / 表(2)
计量
  • 文章访问数:  76
  • HTML全文浏览量:  19
  • PDF下载量:  24
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-05-06
  • 录用日期:  2023-10-16
  • 修回日期:  2023-07-21
  • 网络出版日期:  2023-07-25

目录

    /

    返回文章
    返回