• DocumentCode
    987193
  • Title

    Spatial scales of tropical precipitation inferred from TRMM microwave imager data

  • Author

    Smith, Dean F. ; Gasiewski, Albin J. ; Jackson, Darren L. ; Wick, Gary A.

  • Author_Institution
    Center for Integrated Plasma Studies, Univ. of Colorado, Boulder, CO, USA
  • Volume
    43
  • Issue
    7
  • fYear
    2005
  • fDate
    7/1/2005 12:00:00 AM
  • Firstpage
    1542
  • Lastpage
    1551
  • Abstract
    The local spatial scales of tropical precipitating systems were studied using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rate imagery from the TRMM satellite. Rain rates were determined from TMI data using the Goddard Profiling (GPROF) Version 5 algorithm. Following the analysis of Ricciardulli and Sardeshmukh (RS), who studied local spatial scales of tropical deep convection using global cloud imagery (GCI) data, active precipitating months were defined alternatively as those having greater than either 0.1 mm/h or 1 mm/h of rain for more than 5% of the time. Spatial autocorrelation values of rain rate were subsequently computed on a 55×55 km grid for convectively active months from 1998 to 2002. The results were fitted to an exponential correlation model using a nonlinear least squares routine to estimate a spatial correlation length at each grid cell. The mean spatial scale over land was 90.5 km and over oceans was 122.3 km for a threshold of 0.1 mm/h of rain with slightly higher values for a threshold of 1 mm/h of rain. An error analysis was performed which showed that the error in these determinations was of order 2% to 10%. The results of this study should be useful in the design of convective schemes for general circulation models and for precipitation error covariance models for use in numerical weather prediction and associated data assimilation schemes. The results of the TMI study also largely concur with those of RS, although the more direct relationship between the TMI data and rain rate relative to the GCI imagery provide more accurate correlation length estimates. The results also confirm the strong impact of land in producing short spatial scale convective rain.
  • Keywords
    atmospheric techniques; data assimilation; geophysical signal processing; microwave measurement; rain; remote sensing; weather forecasting; AD 1998 to 2002; Goddard Profiling Version 5; TRMM Microwave Imager; Tropical Rainfall Measuring Mission; convective rain; data assimilation; error covariance models; exponential correlation model; global cloud imagery; nonlinear least squares; numerical weather prediction; rain rate imagery; spatial correlation length; tropical deep convection; tropical precipitation; Autocorrelation; Clouds; Grid computing; Image analysis; Least squares approximation; Microwave measurements; Predictive models; Rain; Satellites; Sea measurements; Convection; correlation length; microwave; precipitation;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2005.848426
  • Filename
    1459020