2007 Fall Meeting          
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Cite abstracts as Author(s) (2007), Title, Eos Trans. AGU,
(52), Fall Meet. Suppl., Abstract xxxxx-xx

HR: 0800h
AN: A41A-0010
TI: A Cluster Analysis Approach to Comparing Atmospheric Radiation Measurement (ARM) Observations with General Circulation Model (GCM) Results
AU: * Mahajan, S
EM: salilmahajan@neo.tamu.edu
AF: Texas A&M University, Dept. of Atmospherics Sciences, College Station, TX 77840, United States
AU: Hoffman, F M
EM: forrest@climatemodeling.org
AF: Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831-6016, United States
AU: Hargrove, W W
EM: hnw@geobabble.org
AF: USDA Forest Service, 200 WT Weaver Blvd., Asheville, NC 28804, United States
AU: Christensen, S W
EM: swc@ornl.gov
AF: Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831-6016, United States
AU: Mills, R T
EM: rmills@climatemodeling.org
AF: Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831-6016, United States
AB: Continued validation of General Circulation Models (GCMs) is essential for their improvement, and pin-pointing their biases and systematic deviations might be of service to climate modelers. The availability of abundant multi-variate atmospheric data from the Dept. of Energy's Atmospheric Radiation Measurement (ARM) Program sites allows for comparison of atmospheric column observations to GCM simulations at high temporal resolutions at those locations. This study focuses on using a multi-variate cluster analysis approach to compare ARM observations of tropospheric vertical temperature, humidity, wind speed profiles, and surface pressure at the Southern Great Plains (SGP) site with corresponding output from an integration of the Community Climate System Model (CCSM) for the same location, highlighting observed discrepancies in the GCM results. Cluster analysis is a technique for classifying multi-variate data into distinct regimes based on Euclidean distance in phase space. A parallel clustering algorithm, designed for analyzing very large datasets, was applied to developing various atmospheric column regimes at the SGP site from the observations and, separately, from the CCSM model results. A comparison of the atmospheric regimes derived from the observations against the CCSM output proves to be useful in distinguishing their individual nature and identifying singular behavior. Some atmospheric regimes are found to be poorly represented in the CCSM. For example, while ARM SGP observations show hot humid lower tropospheric conditions are usually associated with low shear conditions, such conditions in CCSM output are associated with stronger shear. Low shear conditions in CCSM usually occur in a hot, moderately humid lower troposphere. These distinct regimes in CCSM, as compared to ARM observations, suggest misrepresentation of atmospheric states in CCSM over the SGP site, which could have ramifications on the formation of clouds in CCSM simulations, affecting the local radiation budget. In addition, the multi-variance of CCSM is lower than that of ARM observations suggesting that estimates of extremes based on GCM simulations are probably conservative.
DE: 0321 Cloud/radiation interaction
DE: 0325 Evolution of the atmosphere (1610, 8125)
DE: 0343 Planetary atmospheres (5210, 5405, 5704)
DE: 0350 Pressure, density, and temperature
DE: 0360 Radiation: transmission and scattering
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting

Research partially sponsored by the 1) Climate Change Research Division (CCRD) of the Office of Biological and Environmental Research (OBER), and 2) Mathematical, Information, and Computational Sciences (MICS) Division of the Office of Advanced Scientific Computing Research (OASCR) within the U.S. Department of Energy's Office of Science (SC). This research used resources of the National Center for Computational Science (NCCS) at Oak Ridge National Laboratory (ORNL) which is managed by UT-Battelle, LLC, for the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
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