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The Canadian Regional Climate Model Large Ensemble The CanRCM4 large ensemble is a 50-member ensemble from 1950-2100 with all historical forcings for the North American Domain. Each ensemble member is driven by a member of the CanESM2 large ensemble (https://open.canada.ca/data/en/dataset/aa7b6823-fd1e-49ff-a6fb-68076a4a477c). The model, forcings, variable names, and file formats all follow those used in the Coordinated Regional Downscaling Experiment (CORDEX). Simulations were run to 2005 using CMIP5 historical forcings and then to 2100 using RCP 8.5 forcings following the Coupled Model Intercomparison Project Phase 5 (CMIP5) protocols, which were employed for the CanESM2 large ensemble. The CanRCM4 large ensemble is an extension of the CanESM2 large ensemble proposed by the Canadian Sea Ice and Snow Evolution Network (CanSISE) Climate Change and Atmospheric Research (CCAR) Network project. Relevant Publications: Description of the Model: J. F. Scinocca, V. V. Kharin, Y. Jiao, M. W. Qian, M. Lazare, L. Solheim, G. M. Flato, S. Biner, M. Desgagne, B. Dugas, Coordinated global and regional climate modeling. J. Clim. 29, 17–35 (2016). https://doi.org/10.1175/JCLI-D-15-0161.1 Examples of applications of the large ensemble: Fyfe, J.C., C. Derksen, L. Mudryk, G.M. Flato, B.D. Santer, N.C. Swart, N.P. Molotch, X. Zhang, H. Wan, V.K. Arora, J. Scinocca, 2017: Large near-term projected snowpack loss over the western United States, Nature Comm., 8:14996, https://doi.org/10.1038/ncomms14996 Kirchmeier-Young, M. C., N. P. Gillett, F. W. Zwiers, A. J. Cannon, F. S. Anslow, 2018: Influence of human-induced climate change on British Columbia’s extreme 2017 fire season. Earth's Future, 7, 2-10. https://doi.org/10.1029/2018EF001050. 2018-09-26 2019-12-03 Environment and Climate Change Canada open-ouvert@tbs-sct.gc.ca Nature and Environmentlarge ensemblesregional climate modelclimate CanRCM4 Large Ensemble OutputNetCDF http://crd-data-donnees-rdc.ec.gc.ca/CCCMA/products/CanSISE/output/CCCma/CanRCM4/ Data DictionaryPDF http://data.ec.gc.ca/data/climate/scientificknowledge/the-canadian-regional-climate-model-large-ensemble/CanRCM4_LE_DataDictionary.pdf Data DictionaryPDF http://data.ec.gc.ca/data/climate/scientificknowledge/the-canadian-regional-climate-model-large-ensemble/CanRCM4_GE_dictionnaire-de-donnees.pdf View ECCC Data Mart (English)HTML http://data.ec.gc.ca/data/climate/scientificknowledge/the-canadian-regional-climate-model-large-ensemble View ECCC Data Mart (French)HTML http://data.ec.gc.ca/data/climate/scientificknowledge/the-canadian-regional-climate-model-large-ensemble?lang=fr

The Canadian Regional Climate Model Large Ensemble

The CanRCM4 large ensemble is a 50-member ensemble from 1950-2100 with all historical forcings for the North American Domain. Each ensemble member is driven by a member of the CanESM2 large ensemble (https://open.canada.ca/data/en/dataset/aa7b6823-fd1e-49ff-a6fb-68076a4a477c). The model, forcings, variable names, and file formats all follow those used in the Coordinated Regional Downscaling Experiment (CORDEX). Simulations were run to 2005 using CMIP5 historical forcings and then to 2100 using RCP 8.5 forcings following the Coupled Model Intercomparison Project Phase 5 (CMIP5) protocols, which were employed for the CanESM2 large ensemble. The CanRCM4 large ensemble is an extension of the CanESM2 large ensemble proposed by the Canadian Sea Ice and Snow Evolution Network (CanSISE) Climate Change and Atmospheric Research (CCAR) Network project.

Relevant Publications:

Description of the Model:

J. F. Scinocca, V. V. Kharin, Y. Jiao, M. W. Qian, M. Lazare, L. Solheim, G. M. Flato, S. Biner, M. Desgagne, B. Dugas, Coordinated global and regional climate modeling. J. Clim. 29, 17–35 (2016). https://doi.org/10.1175/JCLI-D-15-0161.1

Examples of applications of the large ensemble:

Fyfe, J.C., C. Derksen, L. Mudryk, G.M. Flato, B.D. Santer, N.C. Swart, N.P. Molotch, X. Zhang, H. Wan, V.K. Arora, J. Scinocca, 2017: Large near-term projected snowpack loss over the western United States, Nature Comm., 8:14996, https://doi.org/10.1038/ncomms14996

Kirchmeier-Young, M. C., N. P. Gillett, F. W. Zwiers, A. J. Cannon, F. S. Anslow, 2018: Influence of human-induced climate change on British Columbia’s extreme 2017 fire season. Earth's Future, 7, 2-10. https://doi.org/10.1029/2018EF001050.

Resources

Resource Name Resource Type Format Language Links
CanRCM4 Large Ensemble Output Dataset NetCDF English
French
Access
Data Dictionary Guide PDF English Access
Data Dictionary Guide PDF French Access
View ECCC Data Mart (English) Website HTML English Access
View ECCC Data Mart (French) Website HTML French Access

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