基于CALIOP和MODIS数据的气溶胶时空分布特征对比分析
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摘要
利用两个AERONET站点(Hangzhou-ZFU、SACOL)的Level 2 AOD数据对比验证CALIOP Level 2气溶胶光学厚度(aerosol optical depth,AOD)数据。结果表明:Hangzhou-ZFU、SACOL站的相关系数为0.87、0.85,回归方程的斜率为0.76、0.92,这表明CALIOP AOD与AERONET AOD显著相关,在这两个站点及附近区域具有适应性。基于2008~2015年无云条件下的CALIOP Level 3月气溶胶产品和同期的MODIS Terra/Aqua Level 3月气溶胶产品,对比分析中国东南和西北区域气溶胶光学厚度(aerosol optical depth,AOD)时空分布特征。分析表明:中国东南区域AOD季节与空间变化明显,AOD高值主要分布在长三角、珠三角等地,且夏季最高、春季次之,秋冬季相当。MODIS AOD月均值保持在在0.25~0.8之间,且与CALIOP夜间AOD值接近,但与CALIOP白天AOD值差异较大,最大相差值可达0.45。中国西北区域两种卫星获取的AOD值空间分布非常相似,其高值区都位于塔里木盆地、准格尔盆地和柴达木盆地;AOD值春季最高,夏季减少、冬季次之、秋季最低;MODIS AOD值波动显著且普遍高于CALIOP AOD值。
Combining CALIOP aerosol optical depth(AOD) products and coincident AODs at two AERONET sites(i.e.,Hangzhou_ZFU and SACOL),CALIOP Level 2 column AOD against AERONET AOD is validated.Intercomparison analyses show that the correlation coefficient between AOD at Hangzhou_ZFU(SACOL) and CALIPSO-derived AOD reaches as high as 0.87(0.85),and the slope of the regression equation is 0.76(0.92),indicating that CALIOP AOD is better enough to be applied to characterize the regional air pollution.Based on concurrent CALIOP level 3 monthly mean gridded AOD products(daytime and nighttime) and the MODIS Terra/Aqua level 3 monthly mean AOD dataset of the 8 years(2008~2015),the spatial and temporal variations of AOD over Southeast China and Northwest China are analyzed.Results show that Southeast China exhibits a significant seasonal and spatial variability.High AOD values are largely located in Yangtze River Delta and Pearl River Delta.The highest AOD occurs in spring,followed by summer,and then winter and autumn.In terms of monthly average AOD,MODIS tends to overestimate AOD compared with AERONET,ranging from0.25 to 0.8.CALIOP AOD during night is commensurate with MODIS AOD.By comparison,much difference exists between the daytime CALIPSO AOD and MODIS AOD,which is as high as 0.45.Results from both MODIS and CALIPSO AODs suggest that the spatial distribution of AOD is very similar.To be more specific,the high AOD value is largely located in the Tarim Basin,Junggar Basin and Qaidam Basin.Meanwhile,the highest AOD value occurs in the spring,followed by summer,then winter and autumn.Overall,MODIS AOD values fluctuate significantly and are generally higher than CALIOP AOD values.
Combining CALIOP aerosol optical depth(AOD) products and coincident AODs at two AERONET sites(i.e.,Hangzhou_ZFU and SACOL),CALIOP Level 2 column AOD against AERONET AOD is validated.Intercomparison analyses show that the correlation coefficient between AOD at Hangzhou_ZFU(SACOL) and CALIPSO-derived AOD reaches as high as 0.87(0.85),and the slope of the regression equation is 0.76(0.92),indicating that CALIOP AOD is better enough to be applied to characterize the regional air pollution.Based on concurrent CALIOP level 3 monthly mean gridded AOD products(daytime and nighttime) and the MODIS Terra/Aqua level 3 monthly mean AOD dataset of the 8 years(2008~2015),the spatial and temporal variations of AOD over Southeast China and Northwest China are analyzed.Results show that Southeast China exhibits a significant seasonal and spatial variability.High AOD values are largely located in Yangtze River Delta and Pearl River Delta.The highest AOD occurs in spring,followed by summer,and then winter and autumn.In terms of monthly average AOD,MODIS tends to overestimate AOD compared with AERONET,ranging from0.25 to 0.8.CALIOP AOD during night is commensurate with MODIS AOD.By comparison,much difference exists between the daytime CALIPSO AOD and MODIS AOD,which is as high as 0.45.Results from both MODIS and CALIPSO AODs suggest that the spatial distribution of AOD is very similar.To be more specific,the high AOD value is largely located in the Tarim Basin,Junggar Basin and Qaidam Basin.Meanwhile,the highest AOD value occurs in the spring,followed by summer,then winter and autumn.Overall,MODIS AOD values fluctuate significantly and are generally higher than CALIOP AOD values.
引文
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[23]Deng Xueliang,Deng Weitao,He Dongyan.Spatial-temporal features of atmospheric aerosol in East China in recent years[J].Transactions of Atmospheric Sciences,2010,33(3):347-354(in Chinese).邓学良,邓伟涛,何冬燕.近年来华东地区大气气溶胶的时空特征[J].大气科学学报,2010,33(3):347-354.
[24]Wang Pu.Analysis of Aerosol-Cloud Interaction Observed from Spaceborne Sensors over Eastern China[D].Chengdu:Doctorial Dissertation of University of Electronic Science and Technology of China,2015(in Chinese).王富.中国东部地区气溶胶.云相互作用卫星遥感建模研究[D].成都:电子科技大学博士论文,2015.
[25]Hsu N C,Tsay S C,King M D,et al.Deep blue retrievals of Asian aerosol properties during ACEAsia[J].IEEE T.Geosci.Remote,2006,44(11):3180-3195.
[26]Hu Die,Zhang Lei,Sha Sha.Contrast and application of MODIS aerosol products over the arid and semiarid region in Northwest China[J],Journal of Arid Meteorology,2013,31(4):677-683(in Chinese).胡蝶,张镭,沙莎,等.西北地区MODIS气溶胶产品的对比应用分析[J].干旱气象,2013,31(4):677-683.
[27]Liu Zhen,Zheng Youfei,Liu Jianjun,et al.Research on the distribution of the northern region of China aerosol based on A-trian satellite[J],China Environmental Science,2015,35(10):2891-2898(in Chinese).刘贞,郑有飞,刘建军,等.基于A-train卫星对中国北方地区气溶胶分布的研究[J].中国环境科学,2015,35(10):2891-2898.
[2]D'Almeida G A,Koepke P,Shettle E P.Atmospheric aerosols:global climatology and radiative characteristics[J].J.Med.Microbiol,2005,54(1):55-61.
[3]Allen S K,Plattner G K,Nauels A,et al.Climate change 2013:the physical science basis.An overview of the working group 1 contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change(IPCC)[C]//EGU General Assembly Conference.EGU General Assembly Conference Abstracts,2014.
[4]Remer L A,Santiago G,Hegg D A,et al.Urban/industrial aerosol:Ground-based Sun/sky radiometer and airborne in situ measurements[J].J.Geophys.Res.,1997,102(D14):16849-16859.
[5]Satheesh S K,Moorthy K K.Radiative effects of natural aerosols:A review[J].Atmos.Environ.,2005,39(11):2089-2110.
[6]Jacobson M Z.Global direct radiative forcing due to multicomponent anthropgenic and natural aerosols[J].J.Geophys.Res.,2001,106(D2):1551-1568.
[7]Song Wei,Zhang Lei.A review of remote sensing for aerosol optical depth[J].Arid Meteorology,2007,25(3):76-81(in Chinese).宋薇,张镭.大气气溶胶光学厚度遥感研究概况[J].干旱气象,2007,25(3):76-81.
[8]Li Xiaojing,Gao Ling,Zhang Xingying,et al.Global change of aerosol optical depth based on satellite remote sensing data[J].Science&Technology Review,2015,33(17):30-39(in Chinese).李晓静,高玲,张兴赢,等.卫星遥感监测全球大气气溶胶光学厚度变化[J].科技导报,2015,33(17):30-40.
[9]Chu D A,Remer L A,Kaufman Y J,et al.Evaluation of aerosol properties over ocean from Moderate Resolution Imaging Spectroradiometer(MODIS)during ACE-Asia[J].J.Geophys.Res.,2005,110(D7):1275-1287.
[10]Winker D M,Hostetler C A,Hunt W H.Cloud-aerosol lidar with orthogonal polarization(CALIOP)[C]//Geoscience and Remote Sensing Symposium,2003.IGARSS'03.Proceedings.2003 IEEE International.IEEE,2003:1514-1516.
[11]Winker D M,Vaughan M A,Omar A,et aJ.Overview of the CALIOP mission and CALIOP data processing algorithms[J].J.Atmos.Ocean.Tech.,2009,26(11):2310-2323.
[12]Hu Die.AerosoJ Optical Depth Based on Satellite Observations in China[D].Lanzhou:Master's Thesis of Lanzhou University,2012(in Chinese).胡蝶.中国地区大气气溶胶光学厚度的卫星遥感监测分析[D].兰州:兰州大学硕士论文,2012.
[13]Li Z,Niu F,Kwon-Ho L,et ai.Validation and understanding of Moderate Resolution Imaging Spectroradiometer aerosol products(C5)using groundbased measurements from the handheld Sun photometer network in China[J].J.Geophys.Res.,2007,112(D22):365-371.
[14]Mao Jietai,Li Chengcai,Zhang Junhua,et al.The comparison of remote sensing aerosol optical depth from MODIS data and ground-photometer observations[J].Journal of Applied Meteorological Science,2002,13:127-135(in Chinese).毛节泰,李成才,张军华,等.MODIS卫星遥感北京地区气溶胶光学厚度及与地面光度计遥感的对比[J].应用气象学报,2002,13:127-135.
[15]Kittaka C,Winker D M,Vaughan M A,et al.Intercomparison of column aerosol optical depths from CALIPSO and MODIS-Aqua[J].Atmos.Meas.Tech.,2011,4(2):183-186.
[16]Redemann J,Vaughan M A,Zhang Q,et al.The comparison of MODIS-Aqua(C5)and CALIOP(V2&V3)aerosol optical depth[J].Atmos.Chem.Phys.Discuss.,2011,11(6):3025-3043.
[17]Omar A H,Winker D M,Kittaka C,et ai.The CALIOP automated aerosol classification and lidar ratio selection algorithm[J].J.Atmos.Ocean.Tech.,2009,26(10):1994-2014.
[18]Tackett J L,Winker D M,Getzewich B J,et ai.Quality screening algorithms implemented in the new CALIOP Level 3 aerosol profile product[C].American Geophysical Union,2012.
[19]Yu H,Chin M,Winker D M,et ai.Global view of aerosol vertical distributions from CALIOP lidar measurements and GOCART simulations:regional and seasonal variations[J].J.Geophys.Res.,2010,115(D4):1307-1314.
[20]Levy R C,Mattoo S,Munchak L A,et ai.The Collection 6 MODIS aerosol products over land and ocean[J].Atmos.Meas.Tech.Discuss.,2013,6(1):159-259.
[21]Holben B N,Tanre D,Smirnov A,et al.An emerging groundbased aerosol climatology:Aerosol optical depth from AERONET[J].J.Geophys.Res.,2001,106(D11):12067-12097.
[22]Dubovik O,Smirnov A,Holben B N,et al.Accuracy assessments of aerosol optical properties retrieved from Aerosol Robotic Network(AERONET)Sun and sky radiance measurements[J].J.Geophys.Res.,2000,105(D8):9791-9806.
[23]Deng Xueliang,Deng Weitao,He Dongyan.Spatial-temporal features of atmospheric aerosol in East China in recent years[J].Transactions of Atmospheric Sciences,2010,33(3):347-354(in Chinese).邓学良,邓伟涛,何冬燕.近年来华东地区大气气溶胶的时空特征[J].大气科学学报,2010,33(3):347-354.
[24]Wang Pu.Analysis of Aerosol-Cloud Interaction Observed from Spaceborne Sensors over Eastern China[D].Chengdu:Doctorial Dissertation of University of Electronic Science and Technology of China,2015(in Chinese).王富.中国东部地区气溶胶.云相互作用卫星遥感建模研究[D].成都:电子科技大学博士论文,2015.
[25]Hsu N C,Tsay S C,King M D,et al.Deep blue retrievals of Asian aerosol properties during ACEAsia[J].IEEE T.Geosci.Remote,2006,44(11):3180-3195.
[26]Hu Die,Zhang Lei,Sha Sha.Contrast and application of MODIS aerosol products over the arid and semiarid region in Northwest China[J],Journal of Arid Meteorology,2013,31(4):677-683(in Chinese).胡蝶,张镭,沙莎,等.西北地区MODIS气溶胶产品的对比应用分析[J].干旱气象,2013,31(4):677-683.
[27]Liu Zhen,Zheng Youfei,Liu Jianjun,et al.Research on the distribution of the northern region of China aerosol based on A-trian satellite[J],China Environmental Science,2015,35(10):2891-2898(in Chinese).刘贞,郑有飞,刘建军,等.基于A-train卫星对中国北方地区气溶胶分布的研究[J].中国环境科学,2015,35(10):2891-2898.