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THE ATMOSPHERIC MODEL EVALUATION (AMET): METEOROLOGY MODULE
Citation:
GILLIAM, R. C., W. APPEL, AND S. PHILLIPS. THE ATMOSPHERIC MODEL EVALUATION (AMET): METEOROLOGY MODULE. Presented at 4th Annual CMAS Models-3 Users Conference, Chapel Hill, NC, September 26 - 28, 2005.
Impact/Purpose:
The objectives of this task are to develop, improve, and evaluate EPA's Community Multiscale Air Quality (CMAQ) model, as an air quality management and NAAQS implementation tool. CMAQ is a multiscale and multi-pollutant chemistry-transport model (CTM) that includes the necessary critical science process modules for atmospheric transport, deposition, cloud mixing, emissions, gas- and aqueous-phase chemical transformation processes, and aerosol dynamics and chemistry. To achieve the advances in CMAQ, research will be conducted to develop and test appropriate chemical and physical mechanisms, improve the accuracy of emissions and dry deposition algorithms, and to develop and improve state-of-the-science meteorology models and contributing process parameterizations.
The model will be tested and evaluated to thoroughly characterize the performance of the emissions, meteorological and chemical/transport modeling components of the CMAQ 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. Both operational and diagnostic evaluations, together with sensitivity analyses are needed to both establish credibility and build confidence within the client and scientific community in the simulation 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.
Description:
An Atmospheric Model Evaluation Tool (AMET), composed of meteorological and air quality components, is being developed to examine the error and uncertainty in the model simulations. AMET matches observations with the corresponding model-estimated values in space and time, and then stores the paired observation and model values in a relational database. Subsequent analysis programs extract user specified data from the database to generate statistical plots and tables.