Selected Science Team Proposals – FY 1992


  • Dr. R. Nelson Byrne, SAIC: "Evaluation
    of a New GCM-Capable Stochastic Cloud/Radiation Parameterization using
    ARM Data"
  • Dr. Steven J. Ghan, Pacific Northwest National Laboratory: "Development
    of a GCM Stratiform Cloud Parmameterization"
  • Dr. Andrew J. Heymsfield, National Center for Atmospheric Research:
    "Development and
    Testing of Parameterizations for Continental and Tropical Ice Cloud Microphysical
    and Radiative Properties in GCM and Mesoscale Models"
  • Dr. C. Y. Jim Kao, Los Alamos National Laboratory: "Development
    of a Cloud Parameterization Package for the Improvement of Cloud Simulations
    in Climate Models"
  • Dr. W. Philip Kegelmeyer, Jr, Sandia National Laboratory: "Passive
    Cloud Dynamics Measurement – A Flow Fields Registration Approach"
  • Dr. Jeffrey T. Kiehl, National Center for Atmospheric Research: "A
    Hierarchical Approach to Improved Cloud-Radiative Parameterization for
    Climate Models through the ARM Program"
  • Dr. Robert A. Kropfli, NOAA.ERL: "Shipboard
    Measurements of the Cloud-capped Marine Boundary Layer During FIRE-ASTEX"
  • Dr. David G. Murcray, University of Denver: "Development
    of a SWIR Solar Spectral Radiometer for the ARM Program"
  • Dr. C.M.R. Platt, CSIRO: "A
    Precise Passive Narrow-Beam Filter Infrared Radiometer and It’s Use with
    Lidar in the ARM Program"
  • Dr. David Randall, CSU: "The
    Use of ARM Data to Test an Improved Parameterization of Upper Tropospheric
    Clouds for Use in Climate Models"
  • Dr. William L. Smith, University of Wisconson: "ARM
    Fourier Transform Spectrometer Data Analysis Tools"
  • Dr. James Spinhirne, NASA-GSFC: "Cirrus
    and Aerosol Profilometer for Radiometric Measurements"
  • Dr. Rolland B. Stull, University of Wisconson: "Parameterization
    of GCM Subgrid Nonprecipitating Cumulus and Stratocumulus Clouds Using
    Stochastic/Phenomenological Methods"
  • Dr. Chris J. Walcek, SUNY-Albany: "Use
    of Cloud Observations and Mesoscale Meteorology Models to Evaluate and
    Improve Cloud Parameterizations"