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

主要卫星云气候数据集评述

刘健 王锡津

刘健, 王锡津. 主要卫星云气候数据集评述. 应用气象学报, 2017, 28(6): 654-665. DOI: 10.11898/1001-7313.20170602..
引用本文: 刘健, 王锡津. 主要卫星云气候数据集评述. 应用气象学报, 2017, 28(6): 654-665. DOI: 10.11898/1001-7313.20170602.
Liu Jian, Wang Xijin. Assessment on main kinds of satellite cloud climate datasets. J Appl Meteor Sci, 2017, 28(6): 654-665. DOI:  10.11898/1001-7313.20170602.
Citation: Liu Jian, Wang Xijin. Assessment on main kinds of satellite cloud climate datasets. J Appl Meteor Sci, 2017, 28(6): 654-665. DOI:  10.11898/1001-7313.20170602.

主要卫星云气候数据集评述

DOI: 10.11898/1001-7313.20170602
资助项目: 

国家自然科学基金项目 61531019

国家自然科学基金项目 41175022

详细信息
    通信作者:

    刘健, email: liujian@cma.gov.cn

Assessment on Main Kinds of Satellite Cloud Climate Datasets

  • 摘要: 自20世纪70年代气象卫星进入业务化观测以来,气象卫星已提供了40余年的观测数据。长时间序列的卫星数据为云气候研究提供了可能。基于长时间序列的卫星数据,构建云气候数据集会涉及诸如定标、反演算法、反演数据精度验证等方面。目前国际上也已生成了一系列的云气候数据集,如ISCCP,Patmos-x,CLARA和MODIS-ST等,这些数据集所选用的探测数据、反演算法不尽一致,数据集产品的时空属性各异。如何发挥极轨和静止气象卫星各自优势,融合两类卫星数据,形成高时间分辨率、质量稳定的长时间序列云气候数据集是未来需要解决的问题。
  • 图  1  不同卫星白天观测地方时的时序变化

    Fig. 1  Day-time equator observation times for satellites

    图  2  1982—2015年20°~40°N,73°~105°E区域内NOAA-07,NOAA-09,NOAA-11,NOAA-14,NOAA-16和NOAA-18卫星的CLARA-A1,CLARA-A2及Patmos-x月平均白天云量时序图

    Fig. 2  Monthly mean cloud fraction at day-time from CLARA-A1, CLARA-A2 and Patmos-x by NOAA-07, NOAA-09, NOAA-11, NOAA-14, NOAA-16 and NOAA-18 over 20°-40°N, 73°-105°E during 1982-2015

    图  3  1982—2015年20°~40°N,73°~105°E区域内NOAA-07,NOAA-09,NOAA-11,NOAA-14,NOAA-16和NOAA-18卫星的CLARA-A1,CLARA-A2及Patmos-x月平均夜间云量时序图

    Fig. 3  Monthly mean cloud fraction at night-time from CLARA-A1, CLARA-A2 and Patmos-x by NOAA-07, NOAA-09, NOAA-11, NOAA-14, NOAA-16 and NOAA-18 over 20°-40°N, 73°-105°E during 1982-2015

    图  4  2005—2015年20°~40°N,73°~105°E区域内CLARA-A2, Patmos-x的NOAA-18和Aqua/MODIS月平均白天云量时序图

    Fig. 4  Monthly mean cloud fraction at day-time from CLARA-A2, Patmos-x by NOAA-18 and Aqua/MODIS over 20°-40°N, 73°-105°E during 1982-2015

    图  5  2005—2015年20°~40°N,73°~105°E区域内CLARA-A2, Patmos-x的NOAA-18和Aqua/MODIS月平均夜间云量时序图

    Fig. 5  Monthly mean cloud fraction at night-time from CLARA-A2, Patmos-x by NOAA-18 and Aqua/MODIS over 20°-40°N, 73°-105°E during 1982-2015

    表  1  主要云数据集信息

    Table  1  Some kinds of cloud climate dataset information

    数据集名称 空间分辨率 时间分辨率 时间范围 主要数据源
    ISCCP 2.5°×2.5°(C和D系列)
    30 km×30 km(DX数据)
    3 h, 日, 月 1983—2009年 NOAA,GMS,GOES,METEOSAT
    Patmos-x 0.1°×0.1° 每日2次,月 1979年至今 NOAA,Metop
    CLARA-A1 0.25°×0.25° 日,月 1982—2009年 NOAA
    CLARA-A2 0.25°×0.25° 日,月 1982—2015年 NOAA,Metop
    MODIS-ST 1 km×1 km,5 km×5 km 每日2次,月 2000年至今
    2003年至今
    EOS/Terra
    EOS/Aqua
    HIRS 1980—2015年 NOAA,Metop
    下载: 导出CSV
  • [1] Di G, Menzies A, Zhao G, et al.MISR Level 3 Cloud Fraction by Altitude Algorithm Theoretical Basis.Jet Propulsion Laboratory Rep.JPL D-62358, 2010.
    [2] Goloub P, Herman M, Chepfer H, et al.Cloud thermodynamical phase classification from the POLDER spaceborne instrument.J Geophys Res, 2000, 105:14747-14759. doi:  10.1029/1999JD901183
    [3] Fritz S, Wark D Q, Fleming H E, et al.Temperature Sounding from Satellites.NOAA Technical Report, 1972, NESS 59.US Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite Service, Washington D C.1972.
    [4] Rodgers C D.Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation.Rev Geophys Space Phys, 1976, 14:609-624. doi:  10.1029/RG014i004p00609
    [5] Houghton J T, Taylor F W, Rodgers C D.Remote Sounding of Atmospheres.Cambridge:Cambridge University Press, 1984.
    [6] Twomey S.An Introduction to the Mathematics of Inversion in Remote Sensing and Indirect Measurements.New York:Elsevier, 1977.
    [7] Scot N A, Chedin A, Armante R, et al.Characteristics of the TOVS Pathfinder Path-B dataset.Bull Amer Meteor Soc, 1999, 80:2679-2701. doi:  10.1175/1520-0477(1999)080<2679:COTTPP>2.0.CO;2
    [8] O'Dell C W, Wentz F J, Bennartz R.Cloud liquid water path from satellite-based passive microwave observations:A new climatology over the global oceans.J Climate, 2008, 21:1721-1739. doi:  10.1175/2007JCLI1958.1
    [9] Stephens G L, and Coauthors.The CloudSat mission and the A-Train.Bull Amer Meteor Soc, 2002, 83:1771-1790. doi:  10.1175/BAMS-83-12-1771
    [10] Stubenrauch C J, Rossow W B, Kinne S, et al.Assessment of global cloud datasets from satellites.Bull Amer Meteor Soc, 2013, 6:1031-1049.
    [11] Schiffer R A, Rossow W B.The International Satellite Cloud Climatology Project (ISCCP):The first project of the World Climate Research Programme.Bull Amer Meteor Soc, 1983, 64:779-784. http://d.wanfangdata.com.cn/OAPaper/oai_doaj-articles_fd48456dce06470da8cf82dcdc3148fc
    [12] Hidinger A K, Foster M, Walther A, et al.The pathfinder atmospheres-extended AVHRR climate dataset.Bull Amer Meteor Soc, 2014, 7:909-922. http://connection.ebscohost.com/c/articles/97240863/pathfinder-atmospheres-extended-avhrr-climate-dataset
    [13] Karlsson K G, Riihelä A, Müller R, et al, CLARA-A1:A cloud, albedo, and radiation dataset from 28 yr of global AVHRR data.Atmos Chem Phys, 2013, 13:5351-5367. doi:  10.5194/acp-13-5351-2013
    [14] Karlsson K G, Anttila K, Trentmann J, et al.CLARA-A2:The second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data.Atmos Chem Phys, 2017, 17:5809-5828. doi:  10.5194/acp-17-5809-2017
    [15] Schiffer R A, Rossow W B.ISCCP global radiance data set:A new resource for climate research.Bull Amer Meteor Soc, 1985, 66:1498-1505. doi:  10.1175/1520-0477(1985)066<1498:IGRDSA>2.0.CO;2
    [16] Rossow W B, Kinsella E, Wolf A, et al. International Satellite Cloud Climatology Project (ISCCP) Description of Reduced Resolution Radiance Data.WMO/TD 58(Revised), World Climate Research Program (ICSU and WMO), 1987.
    [17] Rossow W B, Schiffer R A.ISCCP cloud data products.Bull Amer Meteor Soc, 1991, 72:2-20. doi:  10.1175/1520-0477(1991)072<0002:ICDP>2.0.CO;2
    [18] Rossow W B, Schiffer R A.Advances in understanding clouds from ISCCP.Bull Amer Meteor Soc, 1999, 80(11):2261-2287. doi:  10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2
    [19] Rossow W B, Walker A W, Gander L C.Comparison of ISCCP and other cloud amounts.J Climate, 1993, 6:2394-2418. doi:  10.1175/1520-0442(1993)006<2394:COIAOC>2.0.CO;2
    [20] 魏丽, 钟强, 侯萍.中国大陆卫星反演云参数的评估.高原气象, 1996, 15(2):147-156. http://d.wanfangdata.com.cn/Thesis/Y1077918
    [21] 翁笃鸣, 韩爱梅.我国卫星总云量与地面总云量分布的对比分析.应用气象学报, 1998, 9(1):32-37. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19980105&flag=1
    [22] 刘洪利, 朱文琴, 直树华, 等.中国地区云的气候特征分析.气象学报, 2003, 61(4):466-473. doi:  10.11676/qxxb2003.045
    [23] 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):670-676. doi:  10.11898/1001-7313.20050514
    [24] 王旻燕, 王伯民.ISCCP产品和我国地面观测总云量差异.应用气象学报, 2009, 20(4):411-418. doi:  10.11898/1001-7313.20090404
    [25] 刘瑞霞, 刘玉洁, 杜秉玉, 等.利用ISCCP资料分析青藏高原云气候特征.南京气象学院学报, 2002, 25(2):226-234. http://d.wanfangdata.com.cn/Periodical/njqxxyxb200202013
    [26] 王可丽, 江灏, 陈世强, 等.青藏高原地区的总云量-地面观测、卫星反演和同化资料的对比分析.高原气象, 2001, 20(3):252-257. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=gyqx200103004&dbname=CJFD&dbcode=CJFQ
    [27] 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
    [28] 陈勇航, 陈艳, 黄建平, 等.中国西北地区云的分布及其变化趋势.高原气象, 2007, 26(4):741-748. http://d.wanfangdata.com.cn/Periodical/gyqx200704011
    [29] 刘健.中国区域云特性分析及其在FY-2云检测中的应用.应用气象学报, 2009, 20(6):673-681. doi:  10.11898/1001-7313.20090604
    [30] Heidinger A, Straka W C, Molling C C, et al.Deriving an inter sensor consistent calibration for the AVHRR solar reflectance data record.Int J Remote Sensing, 2010, 31:6493-6517. doi:  10.1080/01431161.2010.496472
    [31] Heidinger A, Cao C, Sullivan J T. Using Moderate Resolution Imaging Spectrometer (MODIS) to calibrate Advanced Very High Resolution Radiometer reflectance channels.J Geophys Res, 2002, 107:4702. doi:  10.1029-2001JD002035/
    [32] Zhao Y T, Heidinger A K, Knapp K R.Long-term trends of zonally averaged aerosol optical thickness observed from operational satellite AVHRR instrument.Meteor Appl, 2011, 18:440-445. doi:  10.1002/met.v18.4
    [33] Cermak J, Wild M, Knutti R, et al.Consistency of global satellite-derived aerosol and cloud data sets with recent brightening observations.Geophys Res Lett, 2010, 37:L21704. doi:  10.1029%2F2010GL044632
    [34] Rao C R N, Sullivan J T, Walton C C, et al.Nonlinearity Corrections for the Thermal Infrared Channels of the Advanced Very hIgh Resolution Radiometer:Assessment and Corrections.NOAA Tech Rep, NESDIS 69, 1993.
    [35] Heidinger A K, Evan A T, Foster M J, et al.A naive Bayesian cloud detection scheme derived from CALIPSO and applied within PATMOS-x.J Appl Meteor Climatol, 2012, 51:1129-1144. doi:  10.1175/JAMC-D-11-02.1
    [36] Heidinger A K, Pavolonis M J.Gazing at cirrus clouds for 25 years through a split window.Part Ⅰ:Methodology.J Appl Meteor Climatol, 2009, 48:1100-1116. doi:  10.1175/2008JAMC1882.1
    [37] Walther A, Heidinger A.Implementation of the daytime cloud optical and microphysical properties algorithm (DCOMP) in PATMOS-x.J Appl Meteor Climatol, 2012, 51:1371-1390. doi:  10.1175/JAMC-D-11-0108.1
    [38] Heidinger A, Foster M, Botambekov D, et al.Using the NASA EOS A-train to probe the performance of the NOAA PATMOS-x cloud fraction CDR.Remote Sensing, 2016, 8:511-528. doi:  10.3390/rs8060511
    [39] Foster M J, Heidinger A.Entering the Era of 30-year satellite cloud climatologies:A north American case study.J Climate, 2014, 27:6687-6697. doi:  10.1175/JCLI-D-14-00068.1
    [40] 涂钢, 刘波, 于清波.PATMOS-X、ISCCP云量产品及地面观测在中国区域的对比分析.地理科学, 2014, 34(2):198-204. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=dlkx201402010&dbname=CJFD&dbcode=CJFQ
    [41] Karl-Göran K, Kati A, Jörg T, et al.CLARA-A2:The second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data.Atmos Chem Phys, 2017, 17:5809-5828. doi:  10.5194/acp-17-5809-2017
    [42] Sun B M, FreeM, Yoo H Y, et al.Variability and trends in US cloud cover:ISCCP, Patmos-x and CLARA-A1 compared to homogeneity-adjusted weather observations.J Climate, 2015, 28:4373-4389. doi:  10.1175/JCLI-D-14-00805.1
    [43] Ackerman S A, Strabala K I, Menzel W P, et al, Discriminating clear-sky from clouds with MODIS.J Geophys Res, 1998, 103(D24):32141-32157. doi:  10.1029/1998JD200032
    [44] Frey R A, Ackerman S A.Cloud detection with MODIS.Part Ⅰ:Recent improvements in the MODIS cloud mask.J Atmos Oceanic Technol, 2008, 25:1057-1072. doi:  10.1175/2008JTECHA1052.1
    [45] Menzel W P, and Coauthors.MODIS global cloud-top pressure and amount estimation:Algorithm description and results.J Appl Meteor Climatol, 2008, 47:1175-1198. doi:  10.1175/2007JAMC1705.1
    [46] Platnick S, King M D, Ackerman S A, et al.The MODIS cloud products:Algorithms and examples from Terra.IEEE Trans Geosci Remote Sens, 2003, 41:459-473. doi:  10.1109/TGRS.2002.808301
    [47] Minnis P, Szedung S M, Yan C.CERES edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data.Part Ⅰ:Algorithms.IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(11):4374-4400. doi:  10.1109/TGRS.2011.2144601
    [48] Minnis P, Szedung S M, Yan C, et al.CERES Edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data.Part Ⅱ:Examples of average results and comparisons with other data.IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(11):4401-4430. doi:  10.1109/TGRS.2011.2144602
    [49] Kotarba A Z.A comparison of MODIS-derived cloud amount with visual surface observations.Atmospheric Research, 2009, 92:522-530. doi:  10.1016/j.atmosres.2009.02.001
    [50] 曹芸, 何永健, 邱新法, 等.基于地面观测资料的MODIS云量产品订正.遥感学报, 2012, 16(2):325-342. doi:  10.11834/jrs.2012368
    [51] 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
    [52] 陈勇航, 毛晓琴, 黄建平, 等.西北典型地域条件下云量的对比分析.气候与环境研究, 2009, 14(1):77-84. http://d.wanfangdata.com.cn/Periodical/qhyhjyj200901009
    [53] 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
    [54] 吴晓, 游然, 王旻燕, 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
    [55] 刘健.利用卫星数据分析青藏高原云微物理特性.高原气象, 2015, 32(1):38-45. http://d.wanfangdata.com.cn/Periodical/gyqx201301005
    [56] Wylie D P, Menzel W P.Eight years of high cloud statistics using HIRS.J Climate, 1999, 12:170-184. doi:  10.1175/1520-0442-12.1.170
    [57] Wylie D P, Jackson D L, Menzel W P, et al.Trends in global cloud cover in two decades of HIRS observations.J Climate, 2005, 18:3021-3031. doi:  10.1175/JCLI3461.1
    [58] Cao C, Goldberg M, Wang L.Spectral bias estimation of historical HIRS using IASI observations for improved fundamental climate data records.J Atmos Oceanic Technol, 2009, 26:1378-1387. doi:  10.1175/2009JTECHA1235.1
    [59] Chen R, Cao C.Physical analysis and recalibration of MetOp HIRS using IASI for cloud studies.J Geophys Res, 2012, 117:D03103. http://adsabs.harvard.edu/abs/2012JGRD..117.3103C
    [60] Chen R, Cao C, Menzel W P.Intersatellite calibration of NOAA HIRS CO2 channels for climate studies.J Geophys Res, 2013, 118:5190-5203. doi:  10.1002/jgra.50449
    [61] Nagle F W, Holz R E.Computationally efficient methods of collocating satellite, aircraft, and ground observations.J Atmos Oceanic Technol, 2009, 26:1585-1595. doi:  10.1175/2008JTECHA1189.1
    [62] Menzel W P, and Coauthors.MODIS global cloud-top pressure and amount estimation:Algorithm description and results.J Appl Meteor Climatol, 2008, 47:1175-1198. doi:  10.1175/2007JAMC1705.1
    [63] Baum B A, Menzel W P, Frey R A, et al.MODIS cloudtop property refinements for collection 6.J Appl Meteor Climatol, 2012, 51:1145-1163. doi:  10.1175/JAMC-D-11-0203.1
    [64] Menzel W P, Frey R A, Borbas E E, et al.Reprocessing of HIRS satellite measurements from 1980 to 2015:Development toward a consistent decadal cloud record.J Appl Meteor Climate, 2016, 55:2397-2410. doi:  10.1175/JAMC-D-16-0129.1
    [65] 刘健, 张里阳.气象卫星高空间分辨率数据的云量计算与检验.应用气象学报, 2011, 22(1):35-45. doi:  10.11898/1001-7313.20110104
    [66] 刘健, 杨晓峰, 崔鹏.NOAA卫星2007年总云量数据精度评估.高原气象, 2016, 35(4):1027-1038. http://d.wanfangdata.com.cn/Periodical/gyqx201604017
  • 加载中
图(5) / 表(1)
计量
  • 摘要浏览量:  2568
  • HTML全文浏览量:  1376
  • PDF下载量:  655
  • 被引次数: 0
出版历程
  • 收稿日期:  2017-07-10
  • 修回日期:  2017-10-10
  • 刊出日期:  2017-11-30

目录

    /

    返回文章
    返回