• Adv. Atmos. Sci.  2019, Vol. 36 Issue (1): 1-14    DOI: 10.1007/s00376-018-8075-9
    Aerosol Data Assimilation Using Data from Fengyun-3A and MODIS: Application to a Dust Storm over East Asia in 2011
    Xiaoli XIA, Jinzhong MIN(), Feifei SHEN, Yuanbing WANG, Chun YANG
    Key Laboratory of Meteorological Disaster of Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China
    Abstract
    Abstract  

    Aerosol optical depth (AOD) is the most basic parameter that describes the optical properties of atmospheric aerosols, and it can be used to indicate aerosol content. In this study, we assimilated AOD data from the Fengyun-3A (FY-3A) and MODIS meteorological satellite using the Gridpoint Statistical Interpolation three-dimensional variational data assimilation system. Experiments were conducted for a dust storm over East Asia in April 2011. Each 0600 UTC analysis initialized a 24-h Weather Research and Forecasting with Chemistry model forecast. The results generally showed that the assimilation of satellite AOD observational data can significantly improve model aerosol mass prediction skills. The AOD distribution of the analysis field was closer to the observations of the satellite after assimilation of satellite AOD data. In addition, the analysis resulting from the experiment assimilating both FY-3A/MERSI (Medium-resolution Spectral Imager) AOD data and MODIS AOD data had closer agreement with the ground-based values than the individual assimilation of the two datasets for the dust storm over East Asia. These results suggest that the Chinese FY-3A satellite aerosol products can be effectively applied to numerical models and dust weather analysis.

    Keywords Fengyun-3A satellite      aerosol optical depth      data assimilation      dust storm     
    Corresponding Authors: Jinzhong MIN   
    Just Accepted Date: 07 September 2018   Issue Date: 01 November 2018
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    Xiaoli XIA
    Jinzhong MIN
    Feifei SHEN
    Yuanbing WANG
    Chun YANG
    Cite this article:   
    Xiaoli XIA,Jinzhong MIN,Feifei SHEN, et al. Aerosol Data Assimilation Using Data from Fengyun-3A and MODIS: Application to a Dust Storm over East Asia in 2011[J]. Adv. Atmos. Sci., 2019, 36(1): 1 -14 .
    URL:  
    http://159.226.119.58/aas/EN/10.1007/s00376-018-8075-9     OR     
    http://159.226.119.58/aas/EN/Y2019/V36/I1/1
    References
    1  
    2  
    3  
    4  
    5  
    6  
    7  
    8  
    9  
    10  
    11  
    12  
    13  
    14  
    15  
    16  
    17  
    18  
    19  
    20  
    21  
    Li X. J.,P. Zhang, H. Qiu, and C. L. Fu, 2008: Introduction of MERSI/FY-3A land aerosol products. China Meteorological Society, Beijing. (in Chinese), 1.
    22  
    23  
    24  
    25  
    Nieradzik L. P.,H. Elbern, 2006: Variational assimilation of combined satellite retrieved and in situ aerosol data in an advanced chemistry transport model. Proceedings of the ESA Atmospheric Science Conference, ESA, Frascati.
    26  
    27  
    28  
    Pang Y.,2012: Distribution and evolution of atmospheric pollutants over Beijing-Tianjing-Hebei region. M.S. thesis, Nanjing University of Information Science & Technology. 1- 51.
    29  
    30  
    31  
    32  
    33  
    34  
    35  
    36  
    37  
    38  
    39  
    40  
    41  
    42  
    Zhang Q, D. G. Streets, G. R. Carmichael, K. He. H. Huo, A. Kannari, Z. Klimont, I. Park, S. Reddy, J. S. Fu, D. Chen, L. Duan, Y. Lei, L. Wang, Z. Yao, 2009: Asian emissions in 2006 for the NASA INTEX-B mission. Atmospheric Chemistry & Physics Discussions, 9, 5131- 5153.
    43  
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