Operational chemical weather forecasting with the ECCC online Regional Air Quality Deterministic Prediction System version 023 (RAQDPS023) – Part 1: System description
Bibliographic record
Abstract
Abstract. The online version of the Regional Air Quality Deterministic Prediction System (RAQDPS) is a chemical weather forecast system that has been employed operationally by Environment and Climate Change Canada (ECCC) since 2009. It is run twice per day to produce 72-hour forecasts of hourly 10 km abundance fields of three key predictands, NO2, O3, and PM2.5 total mass, as well as other gas-phase chemical species, PM2.5 chemical components, and dry and wet deposition for Canada, the contiguous U.S., and northern Mexico. The forecasts of NO2, O3, and PM2.5 are needed to calculate the Air Quality Health Index (AQHI), which is used to communicate current and forecasted pollutant levels to the Canadian public. Version 023 of the RAQDPS (RAQDPS023) went into service at ECCC in December 2021 and was replaced by the RAQDPS025 in June 2024. This paper provides the first full description of any version of the online RAQDPS. After giving a brief history of the ECCC operational air quality forecasting program, we provide a comprehensive description of the RAQDPS023 forecast system as well as shorter descriptions of several upstream and downstream forecast and analysis systems. The latter include two upstream operational meteorological forecast systems that were based on version 5.1.0 of the ECCC Global Environmental Multiscale (GEM) numerical weather prediction model, one which used a global configuration, the Global Deterministic Prediction System (GDPS 8.0.0), and the other which used a regional configuration, the Regional Deterministic Prediction System (RDPS 8.0.0). An emissions processing system, an Updateable Model Output Statistics-based system for bias-corrected station-specific pollutant concentration forecasts (UMOS-AQ), and a regional objective analysis system for surface pollutant concentration fields, the Regional Deterministic Air Quality Analysis system (RDAQA 2.0.0), are also described. The RAQDPS023 itself consisted of version 3.1.0.0 of the GEM-Modelling Air quality and CHemistry (GEM-MACH) chemistry module, which was embedded with one-way coupling within GEM 5.1.0, its meteorological host model. The meteorological configuration of the RAQDPS023 closely followed that of the RDPS 8.0.0. Details covered in this paper include a summary of the dynamical representations and physical parameterizations used in the three GEM-based forecast systems, which are closely harmonized, the chemical parameterizations used in the MACH chemistry module, numerical solvers, system inputs, including both anthropogenic and natural emissions of chemical species, system outputs, and run configuration, strategies, and timings. One simplification employed to reduce RAQDPS023 execution time for operational deployment was to represent the particulate matter (PM) size distribution with only two aerosol particle size bins, one corresponding to particle diameters in the 0–2.5 µm range (“fine particles” or PM2.5) and the other to the 2.5–10 µm range (“coarse fraction” or PMcf). A second simplification was to represent the chemical composition of PM2.5 with only nine chemical components, and a third simplification was to use a longer time step (900 s) for the time integration of atmospheric chemistry than the time step used for time integration of atmospheric dynamics and physics (300 s). Even so, activating the MACH module increased RAQDPS023 run time by a factor of 4.4 on average compared to meteorology only, partly due to the cost of the integration of chemistry but partly to the increased cost of integration of the GEM dynamical core due to the advection with imposed shape preservation and mass conservation of 57 additional chemical tracers. The role of the RAQDPS-FW023, a second chemical weather forecast system that was identical to the RAQDPS023 except for the addition of near-real-time biomass burning emissions, is also described. Biomass burning emissions for Canada and the U.S. estimated from satellite measurements were first calculated by the Canadian Forest Fire Emissions Prediction System (CFFEPS) version 4.1 before each RAQDPS-FW023 run was launched. Outputs from the two RAQDPS versions were then used to produce forecasts of wildfire smoke transport and diffusion. The paper closes by summarizing the key upgrades made to the RAQDPS025, the current version of the ECCC operational chemical weather forecast system, and then describing some possible future improvements and updates. A companion paper by Moran et al. (2025) presents the results of a comprehensive, five-year performance evaluation of prospective and retrospective annual air quality simulations made with the RAQDPS023.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.019 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".