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1. Forecast system version
Identifier code: CanESM5.1p1bc
First operational forecast run: 30 June 2024
2. Configuration of the forecast model
Is the model coupled to an ocean model? Yes
Coupling frequency: 3 hours
2.1 Atmosphere and land surface
| Model | CanAM5.1 (atmosphere), CLASS3.6.2 (land), CTEM (terrestrial ecosystem) |
|---|---|
| Horizontal resolution and grid | T63 (~2.8° lat/lon) |
| Atmosphere vertical resolution | 49 hybrid levels |
| Top of atmosphere | 1 hPa |
| Soil levels | 3 Layer 1: 0-10 cm (total soil depth can be shallower than 410 cm) |
| Time step | 15 minutes |
Detailed documentation:
Cole, J. N. S., et al. 2023: The Canadian Atmospheric Model version 5 (CanAM5.0.3). Geoscientific Model Development, 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023
Sigmond, M., et al. 2023: Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1. Geoscientific Model Development, 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023
2.2 Ocean and cryosphere
| Ocean model | NEMO v3.4 (physical ocean) CMOC (ocean ecosystem) |
|---|---|
| Horizontal resolution | ORCA1 |
| Vertical resolution | 45 levels |
| Time step | 1 hour |
| Sea ice model | LIM2 |
| Sea ice model resolution | ORCA1 |
| Sea ice model levels | 1 |
| Wave model | N/A |
| Wave model resolution | N/A |
Detailed documentation:
Swart, N. C., 2019: The Canadian Earth System Model version 5 (CanESM5.0.3). Geoscientific Model Development, 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019.
3. Boundary
...
conditions - climate forcings
| Greenhouse gases | CMIP6 historical (before 2014 inclusive); CMIP6SSP2-4.5 (2015 and after) as described in O'Neill et al. 2016 |
|---|---|
| Ozone | Temporally and spatially varying following Checa-Garcia et al., 2018 |
| Tropospheric aerosols | Parameterized using a prognostic scheme for bulk concentrations of natural and anthropogenic aerosols, including sulfate, black and organic carbon, sea salt, and mineral dust; parameterizations for emissions, transport, gas-phase and aqueous-phase chemistry; and dry and wet deposition accounting for interactions with simulated meteorology |
| Volcanic aerosols | CMIP6 volcanic stratospheric aerosols according to Thomason et al. 2018 |
| Solar forcing | CMIP6 solar forcing according to Matthes et al. 2017 |
Detailed documentation:
Checa-Garcia et al., 2018: Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database. Geophysical Research Letters, 45, 3264-3273, https://doi.org/10.1002/2017GL076770
Matthes, K., et al. 2017: Solar forcing for CMIP6 (v3.2). Geoscientific Model Development, 10, 2247–2302. https://doi.org/10.5194/gmd‐10‐2247‐2017
O'Neill, B. C., et al. 2016: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geoscientific Model Development, 9, 3461–3482, http://www.geosci-model-dev.net/9/3461/2016/
Thomason, L. W., et al. 2018: A global space‐based stratospheric aerosol climatology: 1979–2016. Earth System Science Data, 10, 469–492. https://doi.org/10.5194/essd‐10‐469‐2018
4. Initialization and initial condition (IC) perturbations
4.1 Atmosphere and land
| Hindcast | Forecast | |
|---|---|---|
| Atmosphere initialization | Ensemble of coupled assimilation runs constrained by ERA5 | Ensemble of coupled assimilation runs constrained by ECCC GDPS analysis |
| Atmosphere IC perturbations | Assimilation runs begun from different initial conditions | Assimilation runs begun from different initial conditions |
Land Initialization | Land component forced by assimilating atmosphere | Land component forced by assimilating atmosphere |
| Land IC perturbations | Each ensemble member forced by slightly different atmospheric states constrained by ERA5 | Each ensemble member forced by slightly different atmospheric states constrained by GDPS |
| Soil moisture initialization | Soil moisture forced by assimilating atmosphere | Soil moisture forced by assimilating atmosphere |
| Snow initialization | Snow forced by assimilating atmosphere | Snow forced by assimilating atmosphere |
| Unperturbed control forecast? | No | No |
Data assimilation method for control analysis:
Nudging to (re)analysis 6-hourly temperature, specific humidity and horizontal wind components with 24-hour time constant, filtered to remove spatial scales <~1000 km.
Horizontal and vertical resolution of perturbations:
Perturbations are primarily on spatial scales <1000 km, vertical structure not directly specified.
Perturbations in +/- pairs:
No, all perturbations represent random samples from a distribution.
Detailed documentation:
Merryfield, W. J., et al. 2013: The Canadian seasonal to interannual prediction system. Part I: Models and initialization. Monthly Weather Review, 141, 2910–2945, https://doi.org/10.1175/MWR-D-12-00216.1
Sospedra-Alfonso, R., et al. 2024: Evaluation of soil moisture in the Canadian Seasonal to Interannual Prediction System, Version 2.1 (CanSIPSv2.1). Journal of Applied Meteorology and Climatology, 63, 143-164, https://doi.org/10.1175/JAMC-D-23-0034.1
Sospedra-Alfonso, R., et al. 2016: Representation of snow in the Canadian Seasonal to Interannual Prediction System: Part I. Initialization. Journal of Hydrometeorology, 17, 1467–1488, https://doi.org/10.1175/JHM-D-14-0223.1
4.2 Ocean and cryosphere
| Hindcast | Forecast | |
|---|---|---|
| Ocean initialization |
|
|
| Ocean IC perturbations | Assimilation runs begun from different initial conditions | Assimilation runs begun from different initial conditions |
| Unperturbed control forecast? | No | No |
Detailed documentation:
Dirkson, A., et al. 2017: Impacts of sea ice thickness initialization on seasonal Arctic sea ice predictions. Journal of Climate, 30, 1001–1017, https://doi.org/10.1175/JCLI-D-16-0437.1
Lin, H., et al. 2020: The Canadian Seasonal to Interannual Prediction System Version 2 (CanSIPSv2). Weather and Forecasting, 35, 1317–1343, https://doi.org/10.1175/WAF-D-19-0259.1
Sospedra-Alfonso, R., et al. 2021: Decadal climate predictions with the Canadian Earth System Model version 5 (CanESM5). Geoscientific Model Development, 14, 6863–6891, https://doi.org/10.5194/gmd-14-6863-2021
5. Model Uncertainties perturbations:
| Model dynamics perturbations | No |
|---|---|
| Model physics perturbations | No |
If there is a control forecast, is it perturbed? | No control forecast |
Detailed documentation:
6. Forecast system and hindcasts
| Forecast frequency | 12-month forecast is produced on the last day of each month |
|---|---|
| Forecast ensemble size | 20 (ensemble members 1-10 initialized at 00Z on last day of month, 11-20 at 00Z on 5th to last day of month) |
| Hindcast years | 1980-2023 |
| Hindcast ensemble size | 20 (ensemble members 1-10 initialized at 00Z on first day of month, 11-20 at 00Z on 5th to last day of previous month) |
| On-the-fly or static hindcast set? | static |
| Calibration (bias correction) period | 1991-2020 |
7. Other relevant information
In forecast model version name CanESM5.1p1bc,
- 5.1p1 refers to model sub-version described in Sigmond et al. (2023) https://doi.org/10.5194/gmd-16-6553-2023
- bc refers to run-time bias correction of atmospheric fields and ocean potential temperature and salinity using method of Kharin and Scinocca (2012) https://doi.org/10.1029/2012GL052815 as described in https://events.ecmwf.int/event/241/contributions/3435/attachments/2078/3702/WGNE-WS_Merryfield.pdf
Horizontal interpolation from the native model grids to the C3S 1x1-degree grid: bilinear interpolation with filling/masking for land-only and ocean-only fields
Vertical interpolation pressure levels:
- For temp/phi near the surface, log-linear interpolation (linear in ln(eta)) with the lapse rate of 6.5e-3 deg/m
- For remaining variables near the surface and all variables near the top, constant extrapolation, i.e. keep same value from the closest model level
8. Where to find more information
https://weather.gc.ca/saisons/index_e.html
https://climate-scenarios.canada.ca/?page=seasonal-forecasts