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EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART I - OZONE
APPEL, W., A. GILLILAND, G. SARWAR, AND R. C. GILLIAM. EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART I - OZONE. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 41(40):9603-9613, (2007).
This study examines ozone (O3) predictions from the Community Multiscale Air Quality (CMAQ) model version 4.5 and discusses potential factors influencing the model results. Daily maximum 8-hr average O3 levels are largely underpredicted when observed O3 levels are above 85 ppb and overpredicted when they are below 35 ppb. Using a clustering approach, model performance was examined separately for several different synoptic regimes. Under the most common synoptic conditions of a typical summertime Bermuda High setup, the model showed good overall performance for O3, while associations have been identified here between other, less frequent, synoptic regimes and the O3overprediction and underprediction biases. A sensitivity test between the CB-IV and CB05 chemical mechanisms showed that predictions of daily maximum 8-hr average O3 using CB05 were on average 7.3 % higher than those using CB-IV. Boundary condition (BC) sensitivity tests show that the overprediction biases at low O3 levels are more sensitive to the BC O3levels near the surface than BC concentrations aloft. These sensitivity tests also show the model performance for O3 improved when using the global GEOS-CHEM BCs instead of default profiles. Simulations using the newest version of the CMAQ model (v4.6) showed a small improvement in O3 predictions, particularly when vertical layers were not collapsed. Collectively, the results suggest that key synoptic weather patterns play a leading role in the prediction biases, and more detailed study of these episodes are needed to identify further modeling improvements.
The objective of this task is to thoroughly characterize the performance of the emissions, meteorological and chemical/transport modeling components of the Models-3 system, with an emphasis on the chemical/transport model, CMAQ. Emissions-based models are composed of highly complex scientific hypotheses concerning natural processes that can be evaluated through comparison with observations, but not truly validated. Static and Dynamic Operational, Diagnostic, and ultimately Probablistic evaluation methods are needed to both establish credibility and build confidence within the client and scientific community in the simulations results for policy and scientific applications. The characterization of the performance of Models-3/CMAQ is also a tool for the model developers to identify aspects of the modeling system that require further improvement.
Record Details:Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL EXPOSURE RESEARCH LAB
ATMOSPHERIC MODELING DIVISION
MODEL EVALUATION AND APPLIED RESEARCH BRANCH