• DocumentCode
    2305866
  • Title

    Retrieval of Atmospheric Water Vapor from MODIS and Analysis of Its Seasonal Variability over Chinese Continent

  • Author

    Gong, Shaoqi ; Dong, Guokai ; Sun, Deyong ; Zhao, Qiaohua

  • Author_Institution
    Key Lab. of Meteorol. Disaster of Minist. of Educ., NUIST, Nanjing, China
  • fYear
    2011
  • fDate
    25-27 April 2011
  • Firstpage
    365
  • Lastpage
    369
  • Abstract
    Atmospheric water vapor plays an important role in the high-energy thermodynamics of the atmosphere and the genesis of storm systems. Water vapor remote sensing can provide a detailed primary parameter within meteorological prediction models and climate models. The research selects four typical periods MODIS images and retrieves the contents of water vapor over Chinese continent in four seasons. Then the distributed maps of water vapor are drawn. Comparison with the measured values by radiosonde in aero logical stations, the retrieval values are a bit higher. The atmospheric water vapor contents over Chinese continent in winter are the lowest, the second for spring, the third for autumn, and that in summer are the highest. The whole spatial distribution of water vapor is the lowest in southwest of China, especially in Qinghai Tibetan Plateau, lower in northeast and north of China, higher in northwest of China, the highest in east and south of China. The spatial variability of water vapor content in China depends mainly on geographical location and terrain while its seasonal variability is relative with atmospheric circulation and monsoon.
  • Keywords
    atmospheric humidity; atmospheric movements; atmospheric thermodynamics; climatology; geophysical image processing; radiosondes; remote sensing; storms; Chinese continent; MODIS images; Qinghai Tibetan Plateau; aerological stations; atmospheric circulation; atmospheric water vapor contents; climate models; geographical location; high-energy thermodynamics; meteorological prediction models; radiosonde; retrieval values; seasonal variability; spatial distribution; spatial variability; storm systems; water vapor remote sensing; Absorption; Atmospheric measurements; MODIS; Predictive models; Sensors; Storms; Chinese continent; MODIS; Seasonal Variability; atmospheric water vapor; remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Computing (ICIC), 2011 Fourth International Conference on
  • Conference_Location
    Phuket Island
  • Print_ISBN
    978-1-61284-688-0
  • Type

    conf

  • DOI
    10.1109/ICIC.2011.105
  • Filename
    5954581