Abstract
Environment Canada routinely issues twice-daily, 48-h public forecasts of (a) gridded surface and near-surface O3, PM2.5, and NO2 concentration fields made by the GEM-MACH15 on-line chemical weather forecast model on a 15-km North American grid plus (b) point-specific forecasts for Canadian cities of the national Air Quality Health Index (AQHI) prepared by a statistical post-processing package called UMOS-AQ. The AQHI is a health-based, additive, no-threshold, hourly AQ index that ranges from 0 to 10+ and is based on a weighted sum of local O3, PM2.5, and NO2 concentrations. An objective analysis scheme for surface O3, PM2.5, and NO2, which will provide model-measurement data fusion and model error diagnostics, is now being tested. These recent advances as well as plans for further improvements to the AQ forecasting system are described.
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References
Anselmo D, Moran MD, Ménard S, Bouchet V, Makar P, Gong W, Kallaur A, Beaulieu P-A, Landry H, Stroud C, Huang P, Gong S, Talbot D (2010) A new Canadian air quality forecast model: GEM-MACH15. In: Proceedings of the 12th AMS conference on Atmospheric Chemistry, Jan. 17–21, Atlanta, GA. American Meteorological Society, Boston, 6 pp. See http://ams.confex.com/ams/pdfpapers/165388.pdf
Hollingsworth A, Lönnberg P (1986) The statistical structure of short-range forecast errors as determined from radiosonde data. Part I: the wind field. Tellus 38A:111–136
Mahfouf J-F, Brasnett B, Gagnon S (2007) A Canadian precipitation analysis (CaPA) project: description and preliminary results. Atmos-Ocean 45:1–17
Moran MD, Chen J, Ménard S, Pavlovic R, Landry H, Beaulieu P-A, Gilbert S, Makar PA, Gong W, Stroud C, Kallaur A, Robichaud A, Gong S, Anselmo D (2011) Two years of operational AQ forecasting with GEM-MACH15: a look back and a look ahead. In: Proceedings of the 10th CMAS conference, 24–26 Oct., Chapel Hill, NC, 7 pp. See http://www.cmascenter.org/conference/2011/abstracts/moran_two_years_2011.pd
Moran MD, Ménard S, Talbot D, Huang P, Makar PA, Gong W, Landry H, Gravel S, Gong S, Crevier L-P, Kallaur A, Sassi M (2010) Particulate-matter forecasting with GEM-MACH15, a new Canadian air-quality forecast model. In: Steyn DG, Rao ST (eds) Air pollution modelling and its application XX. Springer, Dordrecht, pp 289–292M
Stieb DM, Burnett RT, Smith-Doiron M, Brion O, Hyun Shin H, Economou V (2008) A new multipollutant, no-threshold air quality health index based on short-term associations observed in daily time-series analyses. J Air Waste Manage Assoc 58:435–450
Wilson LJ, Vallée M (2002) The Canadian Updateable Model Output Statistics (UMOS) system: design and development tests. Weather Forecast 17:206–222
Wilson LJ, Vallée M (2003) The Canadian Updateable Model Output Statistics (UMOS) system: validation against perfect prog. Weather Forecast 18:288–302
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Questioner Name: Sarav Arunachalam
Q: You have developed an advanced air quality forecast (AQF) system. Do you have any information on how much this AQF system is used by the public for protecting public health and/or for general awareness? Documenting any information on gross usage statistics will be helpful to assess the utility and value of this system.
A: In terms of gross usage statistics, for the most recent year, 2011, there were 800,000 visits to our AQHI values on Environment Canada’s public Weatheroffice website (http://www.weatheroffice.gc.ca/canada_e.html). As well, EC has been and is working with polling and market research firms to track how well the AQHI is understood by the public, how it is being used, and by whom.
Questioner Name: Sarav Arunachalam
Q: After UMOS-AQ is applied, it seems that PM2.5 performance degrades rather than improves whereas O3 and NO2 seem just fine. Do you know why?
A: In comparing the scatterplots for GEM-MACH15 vs. observations and UMOS-AQ vs. observations for summer 2010, you are correct that to the eye the amount of data-point scatter appears to have increased for UMOS-AQ. However, the overall forecast skill for PM2.5 has in fact improved: for example, the Pearson correlation coefficient r increased from 0.28 to 0.52 and the slope of the best-fit line moved closer to unity.
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Moran, M.D. et al. (2014). Recent Advances in Canada’s National Operational AQ Forecasting System. In: Steyn, D., Builtjes, P., Timmermans, R. (eds) Air Pollution Modeling and its Application XXII. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5577-2_37
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DOI: https://doi.org/10.1007/978-94-007-5577-2_37
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