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Developments and Results from a Global Multiscale Air Quality Model (GEM-AQ)

  • L. Neary
  • Jacek W. Kaminski
  • A. Lupu
  • J. C. McConnell

The GEM-AQ model (Global Environmental Multiscale model with Air Quality processes) is based on Canada’s operational weather prediction model developed by the Meteorological Services of Canada (MSC). The chemical module is included in the host meteorological model “online”, so that the chemical species are advected at each dynamical timestep and the meteorological information can be used in the chemical process calculations. The processes include over 100 gas phase chemical reactions, anthropogenic and biogenic emissions, transport due to vertical diffusion and convection, dry deposition and wet scavenging. We have recently introduced size-resolved aerosols which undergo processes such as coagulation, nucleation, dry and wet scavenging. GEM-AQ is capable of running on a global uniform or global variable resolution domain. The variable resolution capability allows a high resolution simulation over an area of interest without the computational overhead of a global high resolution domain, as well as eliminating the need for boundary conditions in the case of limited area modeling. The capabilities of this modelling system give us a tool to help examine local air quality issues while keeping the global picture in mind. The design philosophy behind GEM-AQ allows for the integration of different physics and chemistry modules into a single computational platform. The major advantage of this approach allows for the development and improvement of parameterizations which can easily be included in the system. In addition, the use of GEMAQ as the core of the modelling system will permit the incorporation of data assimilation techniques into the model validation and application studies on processes by researchers participating in the Multiscale Air Quality Modelling Network (MAQNet).

Keywords

Aerosol Optical Depth Aerosol Type Smoke Plume Limited Area Model Aerosol Module 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • L. Neary
    • 1
  • Jacek W. Kaminski
    • 2
  • A. Lupu
    • 1
  • J. C. McConnell
    • 1
  1. 1.York UniversityDepartment of Earth & Space Science & EngineeringNorth YorkCanada
  2. 2.Department of Earth and Space ScienceYork UniversityTorontoCanada

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