Voici la liste des publications réalisées par les membres du projet ARRIMÉ :
Une mise à jour sera faite prochainement pour vous permettre de faire une sélection par date, par auteur ou par sujet à partir de notre base de données des publications sous l’application ZOTERO.
Alpizar, M., Di Luca, A., Gachon, P., & Roberge, F. (2026). Mesoscale Convective Systems in Northeastern North America: Identification and evaluation with the convection-permitting version of the Canadian Regional Climate Model. Climate Dynamics, 64(129). https://doi.org/10.1007/s00382-026-08102-6
Cloutier-Gervais, M. (2025). Évaluation de la performance du modèle régional canadien du climat pour simuler les cyclones extratropicaux au nord-est Amérique du Nord [Mémoire accepté, Université du Québec à Montréal]. https://archipel.uqam.ca/19368/
De Meyer, V., Di Luca, A., & Gachon, P. (2025). An Eulerian Evaluation of Intense Low-Pressure Systems over North America in CMIP6 and a Regional Climate Model. Climate Dynamics.
Ghosh, S., Lucas-Picher, P., Roy, P., Gachon, P., & Di Luca, A. (2025). Optimal Configuration of a Convection-Permitting Regional Climate Model in Simulating Precipitation Extremes: The Saguenay Flood. Journal of Hydrometeorology, 26(11), 1751–1774. https://doi.org/10.1175/JHM-D-25-0011.1
Marois, C. (2025). Intégration de facteurs de correction dans la modélisation conjointe des précipitations extrêmes pour l’estimation des courbes IDF en climat futur [Master’s Thesis, Polytechnique Montréal]. https://publications.polymtl.ca/67714/
Martin, A. (2024). Estimation statistique de la précipitation maximale probable à l’aide de la loi de Pearson de type I [Master’s thesis, Polytechnique Montréal]. https://www.proquest.com/openview/30fe3b54c5cf5b1615cfd2cb117b7e94/1?pq-origsite=gscholar&cbl=18750&diss=y
Martin, A., Fournier, É., & Jalbert, J. (2025). Statistical estimation of probable maximum precipitation. Hydrology and Earth System Sciences, 29, 4811–4824. https://doi.org/10.5194/hess-29-4811-2025
Michaud, Amélie (2026). Caractéristiques des vents horaires et des rafales de vents telles que simulées par un modèle régional du climat à très haute résolution. Mémoire. Montréal (Québec, Canada), Université du Québec à Montréal, Maîtrise en sciences de l’environnement. https://archipel.uqam.ca/secure/id/eprint/20137
Voici la liste des publications d’autres auteurs :
Abramowitz, G., Herger, N., Gutmann, E., Hammerling, D., Knutti, R., Leduc, M., Lorenz, R., Pincus, R., and Schmidt, G. A. (2019). ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing, Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019.
Adinolfi, M., Raffa, M., Reder, A., & Mercogliano, P. (2021). Evaluation and expected changes of summer precipitation at convection permitting scale with COSMO-CLM over alpine space. Atmosphere, 12, 54. https://doi.org/10.3390/atmos12010054
Alexander D. (2021). Cascading Disasters: Multiple Risk Reduction and Resilience. In: Eslamian S., Eslamian F. (eds) Handbook of Disaster Risk Reduction for Resilience. Springer, Cham. https://doi.org/10.1007/978-3-030-61278-8_8
Alfieri, L., Bisselink, B., Dottori, F., Naumann, G., De Roo, A., Salamon, P., Wyser, K., & Feyen, L. (2017). Global projections of river flood risk in a warmer world. Earth’s Future, 5(2), 171–182. https://doi.org/10.1002/2016EF000485
AMAP (2021). Arctic Climate Change Update 2021: Key Trends and Impacts. Summary for Policymakers. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. 16 pp. Retrieved July 11, 2026, from https://www.amap.no/documents/doc/amap-arctic-climate-change-update-2021-key-trends-and-impacts/3594
Argüeso, D., Romero, R., & Homar, V. (2020). Precipitation features of the maritime continent in parameterized and explicit convection models. Journal of Climate, 33, 2449–2466. https://doi.org/10.1175/JCLI-D-19-0416.1
BAC (Bureau d’assurance du Canada). (2015). La gestion financière du risque d’inondation. https://a.storyblok.com/f/339220/x/6083a5d247/the_financial_management_of_flood_risk_fr.pdf
Ban, N., Caillaud, C., Coppola, E. et al. (2021). The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation. Clim Dyn (2021). https://doi.org/10.1007/s00382-021-05708-w
Ban N, Schmidli J, Schär C (2014). Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J Geophys Res Atmos 119:7889–7907. https://doi.org/10.1002/2014JD021478
Ban, N., Schmidli, J., & Schär, C. (2015). Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster? Geophysical Research Letters, 42(4), 1165–1172. https://doi.org/10.1002/2014GL062588
Bao, J., & Sherwood, S. C. (2019). The role of convective self-aggregation in extreme instantaneous versus daily precipitation. Journal of Advances in Modeling Earth Systems, 11, 19–33. https://doi.org/10.1029/2018MS001503
Beauchamp, J., Leconte, R., Trudel, M., & Brissette, F. (2013). Estimation of the summer-fall PMP and PMF of a northern watershed under a changed climate: PMP and PMF Estimation Under Climate Change. Water Resources Research, 49(6), 3852–3862. https://doi.org/10.1002/wrcr.20336
Ben Alaya, M. A., Zwiers, F., & Zhang, X. (2018). Probable Maximum Precipitation: Its Estimation and Uncertainty Quantification Using Bivariate Extreme Value Analysis. Journal of Hydrometeorology, 19(4), 679–694. https://doi.org/10.1175/JHM-D-17-0110.1
Berry, G., Reeder, M. J., & Jakob, C. (2011). A global climatology of atmospheric fronts: GLOBAL CLIMATOLOGY OF ATMOSPHERIC FRONTS. Geophysical Research Letters, 38(4), n/a-n/a. https://doi.org/10.1029/2010GL046451
Brasseur, O. (2001). Development and Application of a Physical Approach to Estimating Wind Gusts. https://doi.org/10.1175/1520-0493(2001)129<0005:DAAOAP>2.0.CO;2.
Brönnimann, S., Rajczak, J., Fischer, E. M., Raible, C. C., Rohrer, M., & Schär, C. (2018). Changing seasonality of moderate and extreme precipitation events in the Alps. Natural Hazards and Earth System Sciences, 18(7), 2047–2056. https://doi.org/10.5194/nhess-18-2047-2018
Bush, E. and Lemmen, D.S., editors (2019). Canada’s Changing Climate Report; Government of Canada, Ottawa, ON. 444 p., https://changingclimate.ca/site/assets/uploads/sites/2/2019/04/CCCR_FULLREPORT-EN-FINAL.pdf
C3S (2021). The Climate Data Store of the European Copernicus project: https://cds.climate.copernicus.eu/#!/home
Catto, J. L., & Dowdy, A. (2021). Understanding compound hazards from a weather system perspective. Weather and Climate Extremes, 32, 100313. https://doi.org/10.1016/j.wace.2021.100313
Cholette, M., Laprise, R., & Thériault, J. M. (2015). Perspectives for Very High-Resolution Climate Simulations with Nested Models: Illustration of Potential in Simulating St. Lawrence River Valley Channelling Winds with the Fifth-Generation Canadian Regional Climate Model. Climate, 3(2), 283–307. https://doi.org/10.3390/cli3020283
Clavet-Gaumont, J., Huard, D., Frigon, A., Koenig, K., Slota, P., Rousseau, A., Klein, I., Thiémonge, N., Houdré, F., Perdikaris, J., Turcotte, R., Lafleur, J., Larouche, B. (2017). Probable maximum flood in a changing climate: an overview for Canadian basins. Journal of Hydrology: Regional Studies 13. 1–25. https://doi.org/10.1016/j.ejrh.2017.07.003
Coppola, E., Raffaele, F., Giorgi, F. et al. Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble. Clim Dyn 57, 1293–1383 (2021). https://doi.org/10.1007/s00382-021-05640-z
Council of Canadian Academies. (2019). Canada’s Top Climate Change Risks. Council of Canadian Academies. https://cca-reports.ca/wp-content/uploads/2019/07/Report-Canada-top-climate-change-risks.pdf
Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-.-J., Park, B.-.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553-597. https://doi.org/10.1002/qj.828
Diaconescu, E. P., Gachon, P., Laprise, R., & Scinocca, J. F. (2016). Evaluation of Precipitation Indices over North America from Various Configurations of Regional Climate Models. Atmosphere-Ocean, 54(4), 418–439. https://doi.org/10.1080/07055900.2016.1185005
Di Luca, A., Argüeso, D., Sherwood, S., & Evans, J. P. (2021). Evaluating precipitation errors using the environmentally conditioned intensity-frequency decomposition method. Journal of Advances in Modeling Earth Systems, 13, e2020MS002447. https://doi.org/10.1029/2020MS002447
Dowdy, A. J., & Catto, J. L. (2017). Extreme weather caused by concurrent cyclone, front and thunderstorm occurrences. Scientific Reports, 7(1), 40359. https://doi.org/10.1038/srep40359
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937–1958. https://doi.org/10.5194/gmd-9-1937-2016
Faranda, D., Fery, L., Dubrulle, B., Podvin, B., and Pons, F., “Learning a weather dictionary of atmospheric patterns using Latent Dirichlet Allocation”, vol. 2021, Art. no. IN42B-01, 2021. https://ui.adsabs.harvard.edu/abs/2021AGUFMIN42B..01F
Feser, F., Rockel, B., von Storch, H., Winterfeldt, J., & Zahn, M. (2011). Regional Climate Models Add Value to Global Model Data: A Review and Selected Examples. Bulletin of the American Meteorological Society, 92(9), 1181-1192. https://doi.org/10.1175/2011BAMS3061.1
Fortin, J.-P., Turcotte, R., Massicotte, S., Moussa, R., Fitzback, J., & Villeneuve, J.-P. (2001). Distributed Watershed Model Compatible with Remote Sensing and GIS Data. I: Description of Model. Journal of Hydrologic Engineering, 6(2), 91–99. https://doi.org/10.1061/(ASCE)1084-0699(2001)6:2(91)
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GoldSim Technology Group LLC. (2017). GoldSim: Using Simulation to Move Beyond the Limitations of Spreadsheet Models [White Paper]. GoldSim Technology Group LLC. https://media.goldsim.com/Documents/WhitePapers/Spreadsheet_GoldSim.pdf
Gutowski, W. J., Jr, Ullrich, P. A., Hall, A., Leung, L. R., O’Brien, T. A., Patricola-DiRosario, C. M., Arritt, R. W., Bukovsky, M. S., Calvin, K. V., Feng, Z., Jones, A. D., Kooperman, G. J., Monier, E., Pritchard, M. S., Pryor, S. C., Qian, Y., Rhoades, A. M., Roberts, A. F., Sakaguchi, K., Urban, N., & Zarzycki, C. (2020). The Ongoing Need for High-Resolution Regional Climate Models: Process Understanding and Stakeholder Information. Bulletin of the American Meteorological Society, 101(5), E664-E683. https://doi.org/10.1175/BAMS-D-19-0113.1
GEOSLOPE International Ltd. 2021. Heat and mass transfer modeling with GeoStudio 2021. Calgary, Alberta, Canada. https://www.scribd.com/document/812009018/Heat-and-Mass-Transfer-Modeling-Geostudio
Heikkilä, U., Sandvik, A., & Sorteberg, A. (2011). Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model. Climate Dynamics, 37(7), 1551–1564. https://doi.org/10.1007/s00382-010-0928-6
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., … Thépaut, J. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049. https://doi.org/10.1002/qj.3803
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Hiraga Y., Y. Iseri, M. D. Warner, C. D. Frans, A. M. Duren, J. F. England, M. Levent Kavvas (2021). Estimation of Long-duration Maximum Precipitation during a winter season for large basins dominated by Atmospheric Rivers using a Numerical Weather Model, Journal of Hydrology, 598, 126224, https://doi.org/10.1016/j.jhydrol.2021.126224.
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Ishida, K., Ohara, N., Kavvas, M. L., Chen, Z. Q., & Anderson, M. L. (2018). Impact of air temperature on physically-based maximum precipitation estimation through change in moisture holding capacity of air. Journal of Hydrology, 556, 1050–1063. https://doi.org/10.1016/j.jhydrol.2016.10.008
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Lind, P., Belušić, D., Christensen, O. B., Dobler, A., Kjellström, E., Landgren, O., Lindstedt, D., Matte, D., Pedersen, R. A., Toivonen, E., & Wang, F. (2020). Benefits and added value of convection-permitting climate modeling over Fenno-Scandinavia. Climate Dynamics, 55(7–8), 1893–1912. https://doi.org/10.1007/s00382-020-05359-3
Lind, P., Lindstedt, D., Kjellström, E., & Jones, C. (2016). Spatial and Temporal Characteristics of Summer Precipitation over Central Europe in a Suite of High-Resolution Climate Models. Journal of Climate, 29(10), 3501–3518. https://doi.org/10.1175/JCLI-D-15-0463.1
Lucas‐Picher, P., Argüeso, D., Brisson, E., Tramblay, Y., Berg, P., Lemonsu, A., Kotlarski, S., & Caillaud, C. (2021). Convection ‐permitting modeling with regional climate models: Latest developments and next steps. WIREs Climate Change, 12(6), e731. https://doi.org/10.1002/wcc.731
Lucas-Picher, P., Laprise, R., & Winger, K. (2017). Evidence of added value in North American regional climate model hindcast simulations using ever-increasing horizontal resolutions. Climate Dynamics, 48(7–8), 2611–2633. https://doi.org/10.1007/s00382-016-3227-z
Maraun, D., Shepherd, T. G., Widmann, M., Zappa, G., Walton, D., Gutiérrez, J. M., Hagemann, S., Richter, I., Soares, P. M. M., Hall, A., & Mearns, L. O. (2017). Towards process-informed bias correction of climate change simulations. Nature Climate Change, 7(11), 764–773. https://doi.org/10.1038/nclimate3418
McTaggart-Cowan, R., Vaillancourt, P. A., Zadra, A., Chamberland, S., Charron, M., Corvec, S., Milbrandt, J. A., Paquin-Ricard, D., Patoine, A., Roch, M., Separovic, L., & Yang, J. (2019). Modernization of Atmospheric Physics Parameterization in Canadian NWP. Journal of Advances in Modeling Earth Systems, 11(11), 3593–3635. https://doi.org/10.1029/2019MS001781
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Mendoza, P. A., Mizukami, N., Ikeda, K., Clark, M. P., Gutmann, E. D., Arnold, J. R., Brekke, L. D., & Rajagopalan, B. (2016). Effects of different regional climate model resolution and forcing scales on projected hydrologic changes. Journal of Hydrology, 541, 1003–1019. https://doi.org/10.1016/j.jhydrol.2016.08.010
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Rasmussen, K. L., Prein, A. F., Rasmussen, R. M., Ikeda, K., & Liu, C. (2020). Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over the United States. Climate Dynamics, 55(1–2), 383–408. https://doi.org/10.1007/s00382-017-4000-7
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Rhoades, A. M., Risser, M. D., Stone, D. A., Wehner, M. F., & Jones, A. D. (2021). Implications of warming on western United States landfalling atmospheric rivers and their flood damages. Weather and Climate Extremes, 32, 100326. https://doi.org/10.1016/j.wace.2021.100326
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Roy, P., Rondeau-Genesse, G., Jalbert, J., & Fournier, É. (2024). Climate scenarios of extreme precipitation using a combination of parametric and non-parametric bias correction methods in the province of Québec. Canadian Water Resources Journal / Revue Canadienne Des Ressources Hydriques, 49(1), 23–39. https://doi.org/10.1080/07011784.2023.2220682
Salas, J. D., Anderson, M. L., Papalexiou, S. M., & Frances, F. (2020). PMP and climate variability and change: A review. Journal of Hydrologic Engineering, 25(12). https://hdl.handle.net/11420/57869
Salas, J.D., Gavilan, G., Salas, F.R., Julien, P.Y., & Abdullah, J. (2018). Uncertainty of the PMP and PMF. Handbook of Engineering Hydrology (Three-Volume Set).
Semie, A. G., & Bony, S. (2020). Relationship Between Precipitation Extremes and Convective Organization Inferred From Satellite Observations. Geophysical Research Letters, 47(9), e2019GL086927. https://doi.org/10.1029/2019GL086927
Shepherd, T. G., Boyd, E., Calel, R. A., Chapman, S. C., Dessai, S., Dima-West, I. M., Fowler, H. J., James, R., Maraun, D., Martius, O., Senior, C. A., Sobel, A. H., Stainforth, D. A., Tett, S. F. B., Trenberth, K. E., van den Hurk, B. J. J. M., Watkins, N. W., Wilby, R. L., & Zenghelis, D. A. (2018). Storylines: An alternative approach to representing uncertainty in physical aspects of climate change. Climatic Change, 151(3–4), 555–571. https://doi.org/10.1007/s10584-018-2317-9
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