Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Mark Buehner
CORRESPONDING AUTHOR
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Jean-Francois Caron
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Ervig Lapalme
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Alain Caya
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Ping Du
Meteorological Service of Canada, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Yves Rochon
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, M3H 5T4, Canada
Sergey Skachko
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Maziar Bani Shahabadi
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Sylvain Heilliette
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Martin Deshaies-Jacques
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Weiguang Chang
Meteorological Service of Canada, Environment and Climate Change Canada, Dorval, Quebec, H9P 1J3, Canada
Michael Sitwell
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, M3H 5T4, Canada
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Michael Sitwell, Mark W. Shephard, and Shailesh K. Kharol
EGUsphere, https://doi.org/10.5194/egusphere-2025-4034, https://doi.org/10.5194/egusphere-2025-4034, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Bidirectional flux models give a unified model for emission and dry deposition, but few studies have been conducted in which satellite observations are used to refine the parameters in these models. A new bidirectional flux model for ammonia was developed that was designed specifically for use with satellite observations. Ammonia satellite observations were used to refine bidirectional flux model parameters, which improved the agreement of the model with ammonia surface observations.
Frédéric Dupont, Dany Dumont, Jean-François Lemieux, Elie Dumas-Lefebvre, and Alain Caya
The Cryosphere, 16, 1963–1977, https://doi.org/10.5194/tc-16-1963-2022, https://doi.org/10.5194/tc-16-1963-2022, 2022
Short summary
Short summary
In some shallow seas, grounded ice ridges contribute to stabilizing and maintaining a landfast ice cover. A scheme has already proposed where the keel thickness varies linearly with the mean thickness. Here, we extend the approach by taking into account the ice thickness and bathymetry distributions. The probabilistic approach shows a reasonably good agreement with observations and previous grounding scheme while potentially offering more physical insights into the formation of landfast ice.
Michael Sitwell, Mark W. Shephard, Yves Rochon, Karen Cady-Pereira, and Enrico Dammers
Atmos. Chem. Phys., 22, 6595–6624, https://doi.org/10.5194/acp-22-6595-2022, https://doi.org/10.5194/acp-22-6595-2022, 2022
Short summary
Short summary
Observations of ammonia made using the satellite-borne CrIS instrument were used to improve the ammonia emissions used in the GEM-MACH model. These observations were used to refine estimates of the monthly mean ammonia emissions over North America for May to August 2016. The updated ammonia emissions reduced biases of GEM-MACH surface ammonia fields with surface observations and showed some improvements in the forecasting of species involved in inorganic particulate matter formation.
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Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible...