Global Aerosol Classification Based on Aerosol Robotic Network (AERONET) and Satellite Observation

被引:15
|
作者
Lin, Jianyu [1 ,2 ,3 ]
Zheng, Yu [4 ,5 ]
Shen, Xinyong [1 ,2 ,3 ,6 ]
Xing, Lizhu [1 ,2 ,3 ]
Che, Huizheng [4 ,5 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Key Lab Meteorol Disaster, Minist Educ, Nanjing 210044, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Joint Int Res Lab Climate & Environm Change, Nanjing 210044, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Peoples R China
[4] Chinese Acad Meteorol Sci, CMA, State Key Lab Severe Weather LASW, Beijing 100081, Peoples R China
[5] Chinese Acad Meteorol Sci, CMA, Key Lab Atmospher Chem LAC, Beijing 100081, Peoples R China
[6] Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China
基金
中国国家自然科学基金;
关键词
particle linear depolarization ratio; single scatter albedo; radiative forcing; BIOMASS BURNING EMISSIONS; OPTICAL-PROPERTIES; MICROPHYSICAL PROPERTIES; MIDDLE-EAST; DUST EVENTS; NPP-VIIRS; CHINA; DEPTH; SUN; CLIMATOLOGY;
D O I
10.3390/rs13061114
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The particle linear depolarization ratio (PLDR) and single scatter albedo (SSA) in 1020 nm from the Aerosol Robotic Network (AERONET) level 2.0 dataset was utilized among 52 stations to identify dust and dust dominated aerosols (DD), pollution dominated mixture (PDM), strongly absorbing aerosols (SA) and weakly absorbing aerosols (WA), investigate their spatial and temporal distribution, net radiative forcing and radiative forcing efficiency in global range, and further compare with VIIRS Deep Blue Production. The conclusion about net radiative forcing suggests that the high values of radiative forcing from dust and dust dominated aerosols, pollution dominated mixture both mainly come from western Africa. Strongly absorbing aerosols in South Africa and India contribute greatly to the net radiative forcing and the regions with relative high values of weakly absorbing aerosols are mainly located at East Asia and India. Lastly, the observation of VIIRS Deep Blue satellite monthly averaged products depicts the characteristics about spatial distribution of four kinds of aerosol well, the result from ground-based observation presents great significant to validate the measurements from remote sensing technology.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] Development of global aerosol models using cluster analysis of Aerosol Robotic Network (AERONET) measurements
    Omar, AH
    Won, JG
    Winker, DM
    Yoon, SC
    Dubovik, O
    McCormick, MP
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2005, 110 (D10) : 1 - 14
  • [2] Maritime aerosol network as a component of AERONET - first results and comparison with global aerosol models and satellite retrievals
    Smirnov, A.
    Holben, B. N.
    Giles, D. M.
    Slutsker, I.
    O'Neill, N. T.
    Eck, T. F.
    Macke, A.
    Croot, P.
    Courcoux, Y.
    Sakerin, S. M.
    Smyth, T. J.
    Zielinski, T.
    Zibordi, G.
    Goes, J. I.
    Harvey, M. J.
    Quinn, P. K.
    Nelson, N. B.
    Radionov, V. F.
    Duarte, C. M.
    Losno, R.
    Sciare, J.
    Voss, K. J.
    Kinne, S.
    Nalli, N. R.
    Joseph, E.
    Moorthy, K. Krishna
    Covert, D. S.
    Gulev, S. K.
    Milinevsky, G.
    Larouche, P.
    Belanger, S.
    Horne, E.
    Chin, M.
    Remer, L. A.
    Kahn, R. A.
    Reid, J. S.
    Schulz, M.
    Heald, C. L.
    Zhang, J.
    Lapina, K.
    Kleidman, R. G.
    Griesfeller, J.
    Gaitley, B. J.
    Tan, Q.
    Diehl, T. L.
    [J]. ATMOSPHERIC MEASUREMENT TECHNIQUES, 2011, 4 (03) : 583 - 597
  • [3] A Regional Aerosol Model for the Oceanic Area around Eastern China Based on Aerosol Robotic Network (AERONET)
    Chen, Shunping
    Dai, Congming
    Liu, Nana
    Lian, Wentao
    Zhang, Yuxuan
    Wu, Fan
    Zhang, Cong
    Cui, Shengcheng
    Wei, Heli
    [J]. REMOTE SENSING, 2024, 16 (06)
  • [4] Diurnal variability of aerosol optical depth observed at AERONET (Aerosol Robotic Network) sites
    Smirnov, A
    Holben, BN
    Eck, TF
    Slutsker, I
    Chatenet, B
    Pinker, RT
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2002, 29 (23)
  • [5] Multiangle Imaging Spectroradiometer (MISR) global aerosol optical depth validation based on 2 years of coincident Aerosol Robotic Network (AERONET) observations
    Kahn, RA
    Gaitley, BJ
    Martonchik, JV
    Diner, DJ
    Crean, KA
    Holben, B
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2005, 110 (D10) : 1 - 16
  • [6] The spatiotemporal variations of aerosol types in representative sites of China basing on the Aerosol Robotic Network (AERONET)
    He, Xin
    Zhou, Ru
    Yao, Yuan
    Shen, Zi-Xuan
    Zhu, Jun
    [J]. Zhongguo Huanjing Kexue/China Environmental Science, 2020, 40 (02): : 485 - 496
  • [7] Fog- and cloud-induced aerosol modification observed by the Aerosol Robotic Network (AERONET)
    Eck, T. F.
    Holben, B. N.
    Reid, J. S.
    Giles, D. M.
    Rivas, M. A.
    Singh, R. P.
    Tripathi, S. N.
    Bruegge, C. J.
    Platnick, S.
    Arnold, G. T.
    Krotkov, N. A.
    Carn, S. A.
    Sinyuk, A.
    Dubovik, O.
    Arola, A.
    Schafer, J. S.
    Artaxo, P.
    Smirnov, A.
    Chen, H.
    Goloub, P.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2012, 117
  • [8] Inferring black carbon content and specific absorption from Aerosol Robotic Network (AERONET) aerosol retrievals
    Schuster, GL
    Dubovik, O
    Holben, BN
    Clothiaux, EE
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2005, 110 (D10) : 1 - 19
  • [9] Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data
    Wei, Xiaoli
    Cui, Qian
    Ma, Leiming
    Zhang, Feng
    Li, Wenwen
    Liu, Peng
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2024, 24 (08) : 5025 - 5045
  • [10] An AERONET-based aerosol classification using the Mahalanobis distance
    Hamill, Patrick
    Giordano, Marco
    Ward, Carolyne
    Giles, David
    Holben, Brent
    [J]. ATMOSPHERIC ENVIRONMENT, 2016, 140 : 213 - 233