The Canadian Earth System Model version 5 (CanESM5.0.3)

Swart, Neil C.; Cole, Jason N. S.; Kharin, Viatcheslav; Lazare, Mike; Scinocca, John; Gillett, Nathan P.; Anstey, James; Arora, Vivek K.; Christian, James R.; Hanna, Sarah; Jiao, Yuling; Lee, Warren G.; Majaess, Fouad; Saenko, Oleg A.; Seiler, Christian; Seinen, Clint; Shao, Andrew; Solheim, Larry; Salzen, Knut von; Yang, Duo; Winter, Barbara

doi:10.5194/gmd-2019-177

Cited by 128 publications

(151 citation statements)

References 46 publications

(55 reference statements)

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“…that was used in the Coupled Model Intercomparison Project phase 5 (CMIP5). CanESM5 represents a major update to CanESM2 and described in detail inSwart et al (2019). The major changes relative to CanESM2 are the implementation of completely new models for the ocean, sea-ice, marine ecosystems, and a new coupler.…”

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confidence: 99%

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Carbon-concentration and carbon-climate feedbacks in CMIP6 models, and their comparison to CMIP5 models

Arora¹,

Katavouta²,

Williams³

et al. 2019

Preprint

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Abstract. Results from the fully-, biogeochemically-, and radiatively-coupled simulations in which CO2 increases at a rate of 1&#8201;% per year (1pctCO2) from its pre-industrial value are analyzed to quantify the magnitude of two feedback parameters which characterize the coupled carbon-climate system. These feedback parameters quantify the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate. The results are based on eight comprehensive Earth system models from the fifth Coupled Model Intercomparison Project (CMIP5) and eleven models from the sixth CMIP (CMIP6). The comparison of model results from two CMIP phases shows that, for both land and ocean, the model mean values of the feedback parameters and their multi-model spread has not changed significantly across the two CMIP phases. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The sensitivity of feedback parameters to the three different ways in which they may be calculated is shown and, consistent with existing studies, the most relevant definition is that calculated using results from the fully- and biogeochemically-coupled configurations. Based on these two simulations simplified expressions for the feedback parameters are obtained when the small temperature change in the biogeochemically-coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters allows identification of the reasons for differing responses among ocean and land carbon cycle models.

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confidence: 99%

“…The horizontal resolution is based on a 1° Mercator grid, varying with the cosine of latitude, with a refinement of the meridional grid spacing to 1/3° near the equator. Two modifications have been introduced to the NEMO's mesoscale and smallscale mixing physics in CanESM5 and these are detailed inSwart et al (2019). Sea ice is…”

mentioning

confidence: 99%

Carbon-concentration and carbon-climate feedbacks in CMIP6 models, and their comparison to CMIP5 models

Arora¹,

Katavouta²,

Williams³

et al. 2019

Preprint

Self Cite

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“…The forecasts and simulations are produced using the Canadian Earth System Model version 5 (CanESM5) developed at the Canadian Centre for Climate Modelling and Analysis as a contribution to the Decadal Climate Prediction Project (Boer et al, 2016). CanESM5 is described in Swart et al (2019), and the decadal prediction experiment, together with evaluations of key atmospheric and oceanic fields, is described in a separate publication in preparation. The data used here are available online (https://esgf-node.llnl.gov/ search/cmip6/).…”

Section: Methodsmentioning

confidence: 99%

Assessing the Impact of Initialization on Decadal Prediction Skill

Sospedra‐Alfonso

Boer

2020

Geophysical Research Letters

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An alternative approach to evaluating the correlation skill of near‐term climate predictions is proposed. The approach separately quantifies the skill of the initialized and uninitialized components of the forecast and their contributions to overall correlation skill. The initialized component consists of the predictable part of the internally generated natural variability and that part of the externally forced component affected by initialization. The methodology is applied to results from the latest Canadian Centre for Climate Modelling and Analysis' decadal prediction system. The initialized component of annual mean temperature forecasts exhibits regional skill over ocean and land. The contribution to overall skill is modest at longer ranges and for multiyear temperature averages, partly because of the strong temperature response to external forcing. Larger ensembles increase the percentage of global area with predictable variance due to initialization and the contribution to overall skill from the initialized component of the forecast.

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“…Emerging results from CMIP6 suggest that a number of other models also exhibit climate sensitivities above the top of the CMIP5 ensemble (e.g., Forster et al., 2019; Gettleman et al., 2019; Golaz et al., 2019; Meehl et al., 2020; Swart et al., 2019), and there is now an urgent need to understand the reasons for this increase in sensitivity and whether there are any common reasons for this across the models. Meehl et al.…”

Section: The Broader Modeling Landscapementioning

confidence: 99%

U.K. Community Earth System Modeling for CMIP6

Senior

Jones

Wood

et al. 2020

J Adv Model Earth Syst

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We describe the approach taken to develop the United Kingdom's first community Earth system model, UKESM1. This is a joint effort involving the Met Office and the Natural Environment Research Council (NERC), representing the U.K. academic community. We document our model development procedure and the subsequent U.K. submission to CMIP6, based on a traceable hierarchy of coupled physical and Earth system models. UKESM1 builds on the well‐established, world‐leading HadGEM models of the physical climate system and incorporates cutting‐edge new representations of aerosols, atmospheric chemistry, terrestrial carbon, and nitrogen cycles and an advanced model of ocean biogeochemistry. A high‐level metric of overall performance shows that both models, HadGEM3‐GC3.1 and UKESM1, perform better than most other CMIP6 models so far submitted for a broad range of variables. We point to much more extensive evaluation performed in other papers in this special issue. The merits of not using any forced climate change simulations within our model development process are discussed. First results from HadGEM3‐GC3.1 and UKESM1 include the emergent climate sensitivity (5.5 and 5.4 K, respectively) which is high relative to the current range of CMIP5 models. The role of cloud microphysics and cloud‐aerosol interactions in driving the climate sensitivity, and the systematic approach taken to understand this role, is highlighted in other papers in this special issue. We place our findings within the broader modeling landscape indicating how our understanding of key processes driving higher sensitivity in the two U.K. models seems to align with results from a number of other CMIP6 models.

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The Canadian Earth System Model version 5 (CanESM5.0.3)

Cited by 128 publications

References 46 publications

Carbon-concentration and carbon-climate feedbacks in CMIP6 models, and their comparison to CMIP5 models

Carbon-concentration and carbon-climate feedbacks in CMIP6 models, and their comparison to CMIP5 models

Assessing the Impact of Initialization on Decadal Prediction Skill

U.K. Community Earth System Modeling for CMIP6

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