A Cluster Analysis Approach to Comparing Atmospheric Radiation Measurement (ARM) Data and Global Climate Model (GCM) Results

Conference · Mon Jan 01 00:00:00 EST 2007

OSTI ID:932214

Mahajan, Salil ^[1]; Hoffman, Forrest M ^[1]; Christensen, Sigurd W ^[1]; Mills, Richard T ^[1]

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1. ORNL

Cluster analysis was employed to compare ARM observational data at the Southern Great Plains (SGP) site with corresponding 6-hourly output from an integration of the Community Climate System Model Version 3 (CCSM3) run under the IPCC SRES A2 scenario for the current decade. Cluster analysis is a technique for classifying multivariate data into distinct regimes or states based on Euclidean distance in a phase space formed from the variables under consideration. A three-way process was used for the comparison: (1) CCSM output was projected onto states derived from ARM observations, (2) ARM observations were projected onto states derived from CCSM output, and (3) both ARM observations and CCSM output were projected onto states derived from the combination of the two datasets. A parallel clustering algorithm developed at ORNL has been improved by adding an acceleration technique and a method for handling empty clusters. Both serve to significantly reduce the time-to-solution. In addition, a parallel principal components analysis (PCA) tool has been developed to reduce the dimensionality of the analysis phase space while preserving most of the variance contained in the data.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Computational Sciences
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 932214
• Resource Relation: Conference: American Geophysical Union Fall Meeting, San Francisco, CA, USA, 20071210, 20071214
• Country of Publication: United States
• Language: English