Climate model data

Canadian Centre for Climate Modelling and Analysis

CanESM2 / CGCM4 model output


Models/CanESM2:

CMIP5 Experiments

Experiment IDExperiment name
1pctCO21 percent per year CO2
abrupt4xCO2abrupt 4XCO2
esmControlESM pre-industrial control
esmFdbk1ESM feedback 1
esmFdbk2ESM feedback 2
esmFixClim1ESM fixed climate 1
esmFixClim2ESM fixed climate 2
esmHistoricalESM historical
esmrcp85ESM RCP8.5
historicalhistorical
historicalExthistorical extension
historicalGHGGHG-only
historicalMiscother historical forcing
historicalNatnatural-only
piControlpre-industrial control
rcp26RCP2.6
rcp45RCP4.5
rcp85RCP8.5
sstClimcontrol SST climatology
sstClim4xCO2CO2 forcing
sstClimAerosolall aerosol forcing
sstClimSulfatesulfate aerosol forcing

LUCID (Land Use Change, Impacts and Dynamics intercomparison) Experiments

Experiment IDExperiment name
L1B26RCP 2.6 scenario driven with CO2 emissions and all other forcings but without land use change
L1B85RCP 8.5 scenario driven with CO2 emissions and all other forcings but without land use change
L1C26RCP 2.6 scenario driven with CO2 emissions and all other forcings including land use change
L2A26RCP 2.6 scenario driven with CO2 concentrations and all other forcings but without land use change
L2A85RCP 8.5 scenario driven with CO2 concentrations and all other forcings but without land use change

GeoMIP (The Geoengineering Model Intercomparison Project) experiments

Experiment IDExperiment name
G1quadruple preindustrial CO2 and balance with solar constant reduction
G1oceanAlbedoquadruple preindustrial CO2 balanced by increased ocean albedo
G21%per yr CO2 increase from preindustrial and balance with solar constant reduction
G4RCP4.5 2020-2069 and 5 Tg SO2 injection per yr
G4cdncRCP4.5 with 50% increase of liquid cloud droplet concentration for oceanic low clouds during the period 2020-2069
sstClimG1oceanAlbedoforcing due to quadruple preindustrial CO2 balanced by increased ocean albedo

User information

The user should be aware that grid box values are not directly comparable to station data. Climate models attempt to represent the full climate system from first principles on large scales. Physical "parameterizations" are used to approximate the effects of unresolved small scale processes because it is not economically feasible to include detailed representations of these processes in present day models. Caution is therefore needed when comparing climate model output with observations or analyses on spatial scales shorter than several grid lengths (hundreds of km), or when using model output to study the impacts of climate variability and change.

The user is further cautioned that estimates of climate variability and change obtained from climate model results are subject to sampling variability. This uncertainty arises from the natural variability that is part of the observed climate system and is generally well simulated by the climate models.

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