• DocumentCode
    2105438
  • Title

    Assimilation of multi-time radar observations with WRF-based Ensemble Kalman Filter

  • Author

    Yang, Yi ; Qiu, Xiaobin ; Wang, Zhenghu ; Wen, Deyao ; Shao, Aimei

  • Author_Institution
    Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, China 730000
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    6470
  • Lastpage
    6473
  • Abstract
    Weather Doppler radar can provide high spatial and temporal resolution observations, but most observations are discarded during data assimilation. Only the radar data observed at assimilation time are used in operational prediction. In this paper, the radial velocity observation that not only at the assimilation time but also at some earlier and later time are all assimilated with Ensemble Square Root Kalman Filter (EnSRF) based on WRF model. Result shows that the new scheme produces better analysis than the traditional scheme which only uses radar observations at the assimilation time. The improvement is especially clear in the first several assimilation cycles and then decreases with following assimilation cycles generally.
  • Keywords
    Atmospheric modeling; Data assimilation; Data models; Doppler radar; Kalman filters; Weather forecasting; Doppler radar; EnKF; Multi-Time; assimilation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2010 2nd International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4244-7616-9
  • Type

    conf

  • DOI
    10.1109/ICISE.2010.5689539
  • Filename
    5689539