Preprints
https://doi.org/10.5194/gmd-2021-1
https://doi.org/10.5194/gmd-2021-1

Submitted as: model evaluation paper 28 May 2021

Submitted as: model evaluation paper | 28 May 2021

Review status: a revised version of this preprint is currently under review for the journal GMD.

Decadal climate predictions with the Canadian Earth System Model version 5 (CanESM5)

Reinel Sospedra-Alfonso, William J. Merryfield, George J. Boer, Viatsheslav V. Kharin, Woo-Sung Lee, Christian Seiler, and James R. Christian Reinel Sospedra-Alfonso et al.
  • Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8

Abstract. The Canadian Earth System Model version 5 (CanESM5) developed at Environment and Climate Change Canada's Canadian Centre for Climate Modelling and Analysis (CCCma) is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A 40-member ensemble of CanESM5 historical decadal forecasts (or hindcasts) is integrated for ten years from realistic initial states during 1961 to present using prescribed external forcing. The results are part of CCCma's contribution to the Decadal Climate Prediction Project (DCPP) component of CMIP6. This paper evaluates CanESM5 large ensemble decadal hindcasts against observational benchmarks and against historical climate simulations initialized from preindustrial control run states. The focus is on the evaluation of the potential predictability and actual skill of annual and multi-year averages of key oceanic and atmospheric fields at regional and global scales. The impact of initialization on prediction skill is quantified from the hindcasts decomposition into uninitialized and initialized components. The dependence of potential and actual skill on ensemble size is examined. CanESM5 decadal hindcasts skilfully predict upper-ocean states and surface climate with a significant impact from initialization that depend on climate variable, forecast range, and geographic location. Deficiencies in the skill of North Atlantic surface climate are identified and potential causes discussed. The inclusion of biogeochemical modules in CanESM5 enables the prediction of carbon cycle variables which are shown to be skilful on decadal time scales, with a strong long-lasting impact from initialization on skill in the ocean and a moderate short-lived impact on land.

Reinel Sospedra-Alfonso et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-1', Anonymous Referee #1, 05 Jun 2021
  • RC2: 'Comment on gmd-2021-1', Anonymous Referee #2, 23 Jun 2021
  • AC3: 'Comment on gmd-2021-1', Reinel Sospedra-Alfonso, 24 Jul 2021

Reinel Sospedra-Alfonso et al.

Data sets

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppA-assim, Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3556

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppA-hindcast Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3557

CCCma CanESM5 model output prepared for CMIP6 CMIP historical Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3610

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppC-forecast-noPinatubo Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3575

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppC-forecast-noElChichon Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3574

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppC-forecast-noAgung Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3573

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppC-forecast-addPinatubo Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3572

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppC-forecast-addElChichon Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3571

CCCma CanESM5 model output prepared for CMIP6 DCPP dcppC-forecast-addAgung Sospedra-Alfonso, R., Lee, W., Merryfield, W. J., Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M. https://doi.org/10.22033/ESGF/CMIP6.3570

Model code and software

The Canadian Earth System Model (CanESM), v5.0.3. Swart, N. C., Cole, J., Kharin, S.and Lazare, M. S. J., Gillett, N., Anstey, J., Arora, V., Christian, J., Hanna, S., Jiao, Y., Lee, W., Majaess, F., Saenko, O., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., and Winter, B. https://doi.org/10.5281/zenodo.3251114

Reinel Sospedra-Alfonso et al.

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Short summary
CanESM5 decadal predictions started from observed climate states represent the observed evolution of upper ocean temperatures, surface climate, and the carbon cycle better than ones not started from observed climate states for several years into the forecast. This is due both to better representing climate internal variability, and to corrections of the model response to external forcing including changes in GHG emissions and aerosols.