• DocumentCode
    3349707
  • Title

    Spatiotemporal characteristics of the vertical structure of predictability over the Northern Hemisphere

  • Author

    Aixia Feng ; Qiguang Wang ; Zhiqiang Gong ; Guolin Feng

  • Author_Institution
    Coll. of Phys. Sci. & Technol., Yangzhou Univ., Yangzhou, China
  • Volume
    4
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    2341
  • Lastpage
    2344
  • Abstract
    Based on nonlinear prediction and NCEP/NCAR monthly multi-level geopotential heights, spatial heterogeneity of predictability was obtained over the Northern Hemisphere. On the whole, the predictability is high in continental and higher levels and low in oceans and lower levels from seasonal to interannual timescale. The predictability of the seasonal time scale is similar with the seasonal to interannual timescale. When it goes to the interannual time scale, the predictability becomes high in lower troposphere and low in mid-upper troposphere contrary to the formers. And on the whole the interannual trend is more predictable than the seasonal trend. The strength of the seasonal cycle plays a great role in the heterogeneity of predictability which is proved true by spectrum analysis. Other reasons maybe the properties of the atmospheric air, topographic forcing and timescale interactions.
  • Keywords
    sea level; troposphere; weather forecasting; Northern Hemisphere; atmospheric air property; interannual timescale; interannual trend; lower troposphere; mid-upper troposphere; multilevel geopotential heights; nonlinear prediction; ocean level; predictability spatial heterogeneity; predictability vertical structure; seasonal time scale; seasonal trend; spatiotemporal characteristics; spectrum analysis; timescale interactions; topographic forcing; Atmospheric modeling; Correlation; Meteorology; Ocean temperature; Terrestrial atmosphere; Time series analysis; geopotential height; predictability; seasonal cycle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2011 Seventh International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4244-9950-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2011.6022554
  • Filename
    6022554