A Comprehensive Performance Evaluation of the Next Generation of the Canadian Operational Regional Air Quality Deterministic Prediction System

The core of the Environment and Climate Change Canada (ECCC) operational Regional Air Quality Deterministic Prediction System (RAQDPS) is the GEM-MACH air quality model, which consists of an on-line chemical transport model embedded within the GEM model, ECCC’s multi-scale operational weather forecast model. A new version of GEM-MACH, version 2, which is based on the next-generation version of GEM, became operational earlier this year (2016) after 4 years of development and testing. A comprehensive evaluation of the performance of GEM-MACH version 2 for a 2010 annual simulation on a 10-km North American continental grid was performed as part of this implementation effort using measurements from multiple Canadian and U.S. air-chemistry and precipitation-chemistry surface networks. One evaluation metric considered was skill in predicting annual mean values of a number of gas- and particle-phase species, including PM2.5 chemical components such as elemental carbon and crustal material. Such an analysis of time-averaged spatial fields is useful to check for systematic errors in input emissions fields, in chemical lateral boundary conditions, and in the representation of atmospheric dispersion, chemistry, and removal processes by the model. Spatial R values for NO2, O3, and PM2.5 mean annual concentrations in air for all networks were 0.84, 0.76, and 0.58, and for PM2.5 chemical components SO4, NO3, NH4, EC, OM, and CM the corresponding R values were 0.95, 0.88, 0.78, 0.77, 0.54, and 0.41. For SO 4 = , NO3 −, and NH4 + mean annual concentrations in precipitation the R values were 0.79, 0.80, and 0.92.