• DocumentCode
    2229081
  • Title

    Bayesian formulation of DSD retrieval algorithm for dual-polarized X-band weather radar network

  • Author

    Yoshikawa, Eiichi ; Chandrasekar, V. ; Ushio, Tomoo ; Kawasaki, Zen

  • Author_Institution
    Osaka Univ., Suita, Japan
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    6055
  • Lastpage
    6058
  • Abstract
    Raindrop size distribution (DSD) retrieval algorithm for a weather radar network consisting of X-band dual-polarization weather radars is proposed. This algorithm is based on a DSD retrieval method for a single-radar (SRR), which is elaborated in our paper of the SRR, “RAINDROP SIZE DISTRIBUTION (DSD) RETRIEVAL FOR X-BAND DUAL-POLARIZATION RADAR” in this conference. The SRR outputs an ML solution of the two DSD parameters of the normalized Gamma DSD, Nw and D0. The proposed algorithm calculates posterior probability of the DSD profile with the use of a prior probability, and then, the posterior probabilities on different polar coordinates are integrated to that on a common Cartesian grid by Bayesian theorem. An example of the numerical simulation shows that the fluctuated DSD profiles of the SRRs are improved to less fluctuated DSD profiles on a common Cartesian grid with spatially homogeneous quality.
  • Keywords
    Bayes methods; atmospheric techniques; drops; gamma distribution; meteorological radar; numerical analysis; radar polarimetry; rain; Bayesian formulation; Bayesian theorem; Cartesian grid; DSD parameters; DSD retrieval algorithm; ML solution; dual-polarized X-band weather radar network; fluctuated DSD profiles; normalized Gamma DSD; numerical simulation; polar coordinates; posterior probability; prior probability; raindrop size distribution retrieval algorithm; spatially homogeneous quality; Bayesian methods; Meteorological radar; Meteorology; Numerical simulation; Radar polarimetry; DSD retrieval; X-band radar; dual-polarization; radar network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6352226
  • Filename
    6352226