CanLEAD

Summary Description

CanLEADv1 is an ensemble of bias-adjusted climate simulations created by ECCC based on two CMIP5 era large ensembles: the Canadian Earth System Model Large Ensembles (CanESM2 LE) and Canadian Regional Climate Model Large Ensemble (CanRCM4 LE). This means that there are 50 members for for both the global climate model CanESM2 and the regional climate model CanRCM4. It downscales 8 variables for two models and their 50 members using the multivariate bias-adjustment method MBCn. It is performed with two reference datasets (EWEMBI and S14FD). The experiments included are historical (1950-2005), RCP8.5 (2006–2100) and historicalNAT (1950–2020, only for CanESM2-LE). A detailed description of the method is available in Cannon et al. (2022).

CanLEADv1 CanLEADv1-table2

Dataset Characteristics

  • Current version: v1
  • Temporal coverage: 1950-2100
  • Temporal resolution: daily
  • Spatial coverage: CORDEX NAM-44i
  • Spatial resolution: 0.5°
  • Data type: gridded NetCDF
  • Web references:
    Government of Canada’s Open data portal
  • Reference publications: Cannon et al. (2022)

Strengths and Limitations

Key Strengths of CanLead

Strength Description
Multiple variables Eight variables have been adjusted.
Multiple members 50 members for each model allow to study the natural variability.
Event attribution It can be used for event attribution studies, using the ALL and NAT forcings experiment.
Two references The uncertainty associated with the observational references can be sampled better.
Effective for multivariate/compound indices The dataset reproduces multivariate/compound indices (e.g., hot-dry days, precipitation-as-snow) more effectively than datasets using an univariate bias adjustment, which could improve analyses where multivariate dependence matters.

Key Limitations of CanLead

Limitation Description
Lower resolution The resolution is not as high compared to other bias-adjusted datasets.
Only two models Only includes one RCM and one GCM.
Only one scenario Only includes RCP8.5.
CMIP5 era The dataset is based on CMIP5 data, which is not the most recent data available and uses different experiments than CMIP6.

Expert Guidance

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The CanLEADv1 ensemble intended uses include hydrological and land surface impact modelling, event attribution studies and analysis of compound extremes.

In their paper (Cannon et al. (2022)), the authors identify a few limitations. First, with its high climate sensitivity GCM and its high emission scenario, the CanLEAD ensemble warms much faster than other datasets. One solution presented by the authors is to show the results in terms of global warming level, rather then by time horizon. Second, even though internal variability and observation reference uncertainties are well covered. This is not the case for model and scenario uncertainties. Third, the resolution might not be high enough for all application. For example, hydrological modelling on small basins is not recommended.

Example Applications

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Available Variables in CanLead

For details click on variable group to uncollapse

- Daily maximum near-surface (2 m) air temperature (tasmax) [K]
- Daily minimum near-surface (2 m) air temperature (tasmin) [K]

Tasmax and tasmin are derived from bias-adjustment of tas (tasmin + tasmax)/2 and dtr (tasmax − tasmin).
- Daily mean precipitation rate (pr) [kg m−2 s−1]
- Daily mean near-surface relative humidity (hurs) [%]
Hurs (with respect to liquid water) is derived from specific humidity, temperature and ps (Bolton, 1980). A logit transformation was applied to hurs before the adjustment.
- Daily mean surface air pressure (ps) [Pa]
- Daily mean near-surface (10 metre) wind speed (sfcWind) [m s−1]
- Daily mean surface downwelling shortwave radiation (rsds) [W m−2]
- Daily mean surface downwelling longwave radiation (rlds) [W m−2]

Data Access

The files are accessible through the Government of Canada’s Open Data Portal.

References

Cannon, A.J., Alford, H., Shrestha, R.R., Kirchmeier-Young, M.C., Najafi, M.R., 2022. Canadian large ensembles adjusted dataset version 1 (CanLEADv1): Multivariate bias‐corrected climate model outputs for terrestrial modelling and attribution studies in north america. Geosci. Data J. 9, 288–303.