J10.4
A new Canadian air quality forecast model: GEM-MACH15

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Thursday, 21 January 2010: 2:15 PM
B316 (GWCC)
David Anselmo, EC, Dorval, QC, Canada; and M. D. Moran, S. Ménard, D. Talbot, V. Bouchet, P. Makar, W. Gong, A. Kallaur, P. A. Beaulieu, H. Landry, P. Huang, and S. Gong

Presentation PDF (1.7 MB)

Operational AQ forecasting began in Canada in 2001 with the implementation by Environment Canada (EC) of a continental-scale, 21-km, ozone-only version of the off-line CHRONOS chemical transport model. The meteorological driver used was the regional configuration of EC's operational GEM weather forecast model. Operational CHRONOS forecasts of PM2.5 and PM10 using a simple 2-bin sectional representation of the PM size distribution followed in 2003.

Work to develop a new EC operational AQ forecast model called GEM-MACH started in 2006. This model is an in-line chemical transport model embedded within GEM, the operational weather forecast model at EC. In late 2009, GEM-MACH15, a limited-area 15-km version of GEM-MACH was implemented as the replacement to CHRONOS. A number of AQ process representations from EC's AURAMS chemical transport model have been implemented in GEM-MACH, including gas-phase, aqueous-phase, and heterogeneous chemistry and aerosol processes. Like CHRONOS, GEM-MACH15 uses a 2-bin sectional representation of the PM size distribution, but PM chemical composition is treated in more detail and additional processes affecting PM concentrations have been included. The SMOKE emissions processing system is used to produce anthropogenic input emission files on the GEM-MACH15 rotated latitude-longitude grid based on the 2006 Canadian and 2005 U.S. national inventories. Biogenic emissions are estimated on-line using the BEIS v3.09 algorithms.

This presentation will provide an overview of GEM-MACH, and a description of the specific domain and grid configuration chosen for GEM-MACH15. Results of performance evaluations of GEM-MACH15 against CHRONOS forecasts and O3, NO2, and PM2.5 measurements will be presented.