1. Developing the next generation ECCC seasonal forecasting system
Hai Lin
RPN, ECCC
FORCAII, Beijing Climate Center
April 24-26, 2017
Acknowledgements: contributions of many RPN/CMC and CCCma colleagues 

2. Outlines Early generations of the ECCC seasonal system
Current operational system: CanSIPS
Contribution to NMME
The GEM coupled model
Hindcast verifications
Summary

3. Seasonal forecasts in CMC
Sept – 2003: based on 12-member ensemble of 2 atmospheric models (GCM2, SEF) (2-tier system).
Multi-model approach: 1 climate models and 1 NWP models;
Forecast range limited to 3 months
2003 – Nov. 2011: based on 40-member ensemble of 4 atmospheric models (GCM2, GCM3, SEF, GEM) (2-tier system).
Multi-model approach: 2 climate models and 2 NWP models;
Forecast range limited to 4 months
Since Dec. 2011: based on 20-member ensemble of 2 coupled atmosphere-ocean-land physical climate models (CanSIPS);
Multi-model approach: 2 climate models;
Forecast range up to 12 months.
Pioneered in MME 3

4. Current Seasonal System (CanSIPS)
2-coupled models (CCCma models)
AGCM3 (T63L31) -> CanCM3
AGCM4 (T63L35) -> CanCM4
coupled with CanOM4 (1.41°× 0.94° / L40) ocean model
1-tier system
10 members for each model
1-12 month forecast issued every month
Hindcast period: 4

5. CanSIPS contribution
to the NMME

6. NMME Model History Forecast release months  Aug 2011 Aug 2012 Year 1
NCEP CFSv1 NCEP CFSv2
IRI ECHAM4f
IRI ECHAM4i
GFDL CM2.1
NASA GEOS5
NCAR CCSM3
CMC1/CanCM3
CMC2/CanCM4
NCEP CFSv1
Year 1
Year 2
Aug 2013
Aug 2014
GFDL FLOR
NCAR CCSM4
Year 3
Year 4

7. User/applications Community
NMME
Operational Centers
Research Centers
NCEP EC
GFDL
NASA
NCAR
8th of each month
Hindcasts
Real-time Forecasts
Research Community
User/applications Community

8. Niño3.4 Plumes (Nov-Jun 2014-15)
Ensemble means for each model

9. Real time verifications – summary statistics
init Aug 2011 – Jul 2012
init Aug 2012 – Jul 2013

10. Plan for next system Multi-model (currently already CanCM3+CanCM4)
Climate model + NWP
Development of GEM coupled model

11. Coupled GEM model
Coupled system of
Atmosphere + Land
Ocean
Sea ice

12. Atmospheric Model Global Environmental Multiscale (GEM)
Horizontal resolution: 256 x 128 (~1.4° × 1.4° )
79 levels, top at hPa
Time step: 1 hour
Land surface scheme: ISBA
Deep convection scheme: Kain-Fritsch (KFC)

13. Ocean + Sea ice
NEMO
Horizontal resolution: 1° × 1° , 1/3 degree meridionally near the equator
50 levels
Time step: 30 minutes
coupled with sea ice --- CICE

14. GEM-NEMO Seasonal System
Two components:
1) Hindcast (model statistics, verification)
2) Real time forecast 14

15. Hindcast: initial conditions
Atmosphere: ERA-interim
pefield of GEPS to generate 10 members
(random isotropic perturbations)
Ocean: ORAP5 from ECMWF: ocean T, S, H, U, V
Land: off-line SPS forced by ERA-interim atmosphere
Sea ice concentration: ORAP5
Sea ice thickness: ORAP5

16. Hindcast
12 month integrations
10 members
31 years of

17. Real-time Start at beginning of each month, 10 members
12 month integrations
Atmosphere: 10 members from ENKF of GEPS
Land: SPS forced by CMC analysis
Ocean: CMC GIOPS
Sea ice concentration: CMC GIOPS
Sea ice thickness: CMC GIOPS

18. May 1
Start

19. DJF T2m
lead=1 month

20. JJA T2m
lead=1 month

21. Nov 1
Start

22. DJF PR
lead=0

23. JJA PR
lead=0

24. Lead months
Lead months
Lead months
Lead months

25. NAO skill
1 for JFM, 2 for FMA, etc

26. PNA skill

27. MJO skill

28. Seasonal forecast system
Current operational system (CanSIPS):
CM3+CM4
Possible next system
option 1: GEM+CM4
option 2: GEM+CM3+CM4

29. TAS, Land, seasonal mean, vs. ERA-Interim
GEM+CM4
CanSIPS
GEM
GEM+CM3+CM4
CM4
CM3

30. TAS, N.America, seasonal mean, vs. ERA-Interim

31. PR, Globe, seasonal mean, vs. GPCP2.3

32. PR, N.America, monthly mean, vs. GPCP2.3

33. Summary ECCC continues to develop MME in seasonal forecasting
GEM in general has a higher skill for T2m and PR than CM3 and CM4. CM3 has the least skill.
Better MJO and NAO skill in GEM
Combining GEM with CM4 gives better skill than CanSIPS. Adding CM3 does not improve the skill.