5:25pm Friday 21st September 2018
Current Conditions at CIRA
Temperature: 71.8 F
Dewpoint: 40.3 F
Relative Humidity: 32 %
Barometer: 29.957 in
Wind: S at 0.0 mph
Rainfall: 0.00 in
CIRA

Cooperative Institute for Research in the Atmosphere

Partain, Phil

Phil Partain

Job Title:
Research Associate IV
Phone Number:

970-491-7835

Fax Number:

970-491-8809

Mailing Addresss:
Philip Partain
Cooperative Institute for Research in the Atmosphere
Colorado State University
1375 Campus Delivery
Fort Collins, CO 80523-1375
Office Location:
ACRC 05
Affiliations:
  • CloudSat
About Me:

Phil helped design, develop, and implement the CloudSat data processing system.  Currently, he manages the Data Processing Center and works with the CloudSat Science Team to develop new data products.  He holds a BS in Atmospheric Science from UCLA (1994) and a MS in Atmospheric Science from Colorado State University (1998).  He obtained a project management certificate from PMI and Colorado State University in 2007.  His work on the CloudSat project has been recognized with several awards:

  • NASA Exceptional Public Service Medal for exceptional contributions to the CloudSat mission in the design and implementation of the Level 2 software infrastructure for the CloudSat Data Processing System, July 2008.
  • NASA Public Service Group Achievement Award for exemplary performance in the development and implementation of the CloudSat Standard Data Product algorithms, July 2008.
  • NASA Public Service Group Achievement Award for exceptional contributions to the CloudSat mission in the design, development, and implementation of the CloudSat Data Processing System, June 2007.
  • Recognition of Excellence from the NASA CloudSat Project for developing the Algorithm Interface Management System, November 2001.

    Publications

    GHOST: A Satellite Mission Concept for Persistent Monitoring of Stratospheric Gravity Waves Induced by Severe Storms

    Published Date: 2018
    Published By: American Meteorological Society


    Cloud-Base Height Estimation from VIIRS. Part II: A Statistical Algorithm Based on A-Train Satellite Data

    Published Date: 2017
    Published By: Journal of Atmospheric and Oceanic Technology


    Estimating Three-Dimensional Cloud Structure via Statistically Blended Satellite Observations

    Published Date: 2014
    Published By: American Meteorological Society

    The launch of the NASA CloudSat in April 2006 enabled the first satellite-based global observation of vertically resolved cloud information. However, CloudSat’s nonscanning W-band (94 GHz) Cloud Profiling Radar (CPR) provides only a nadir cross section, or “curtain,” of the atmosphere along the satellite ground track, precluding a full three-dimensional (3D) characterization and thus limiting its utility for certain model verification and cloud-process studies. This paper details an algorithm for extending a limited set of vertically resolved cloud observations to form regional 3D cloud structure. Predicated on the assumption that clouds of the same type (e.g., cirrus, cumulus, and stratocumulus) often share geometric and microphysical properties as well, the algorithm identifies cloud-type-dependent correlations and uses them to estimate cloud-base height and liquid/ice water content vertical structure. These estimates, when combined with conventional retrievals of cloud-top height, result in a 3D structure for the topmost cloud layer. The technique was developed on multiyear CloudSat data and applied to Moderate Resolution Imaging Spectroradiometer (MODIS) swath data from the NASA Aquasatellite. Data-exclusion experiments along the CloudSat ground track show improved predictive skill over both climatology and type-independent nearest-neighbor estimates. More important, the statistical methods, which employ a dynamic range-dependent weighting scheme, were also found to outperform type-dependent near-neighbor estimates. Application to the 3D cloud rendering of a tropical cyclone is demonstrated.