Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-1-2025
https://doi.org/10.5194/gmd-18-1-2025
Development and technical paper
 | 
06 Jan 2025
Development and technical paper |  | 06 Jan 2025

The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)

Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell

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Cited articles

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Bishop, C. H., Whitaker, J. S., and Lei, L.: Gain Form of the Ensemble Transform Kalman Filter and Its Relevance to Satellite Data Assimilation with Model Space Ensemble Covariance Localization, Mon. Weather Rev., 145, 4575–4592, https://doi.org/10.1175/MWR-D-17-0102.1, 2017. 
Bonavita, M., Trémolet, Y., Hólm, E., Lang, S., Chrust, M., Janiskova, M., Lopez, P., Laloyaux, P., de Rosnay, P., Fisher, M., Hamrud, M., and English, S.: A strategy for data assimilation, ECMWF Technical Memorandum 800, ECMWF, Reading, UK, https://doi.org/10.21957/tx1epjd2p, 2017. 
Buehner, M.: Local Ensemble Transform Kalman Filter with Cross Validation, Mon. Weather Rev., 148, 2265–2282, https://doi.org/10.1175/MWR-D-19-0402.1, 2020. 
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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.
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