1. Progress in Seasonal Forecasting at NCEPM C
Progress in Seasonal Forecasting at NCEP
Hindcast Skill in the New Coupled NCEP Ocean-Atmosphere Model
MJO Forecast Experiments

2. E M C Hindcast Skill in the New Coupled NCEP Ocean-Atmosphere Model
Suranjana Saha, Wanqiu Wang, Hua-Lu Pan
and the NCEP/EMC Climate and Weather Modeling Branch
Environmental Modeling Center, NCEP/NWS/NOAA
Special Acknowledgements : Sudhir Nadiga, Jiande Wang, Qin Zhang, Shrinivas Moorthi, Huug van den Dool

3. Introduction
A new global coupled atmosphere-ocean model has recently been developed at NCEP/EMC.
Components
a) the T62/64-layer version of the current NCEP atmospheric GFS (Global Forecast System) model and
b) the 40-level GFDL Modular Ocean Model (version 3)
Note:
Direct coupling with no flux correction
This model will replace the current operational NCEP coupled model (CMP14) for SST prediction in 2004.

4. AMIP run: Rotated EOF (Nov-Mar) Z200
NCEP Reanalysis AMIP

5. NCEP Global Ocean Data Assimilation System (GODAS)
Implemented September 2003
Real time global ocean data base
ARGO (1000 reports/month), altimeter, XBTs, buoys, SST
Community access to ocean data
Standardized formats with embedded QC meta data
Global ocean data assimilation system
Salinity analysis (improved use of altimeter observations)
Upgraded GFDL-MOM ocean model (MOM-3)
Prepare for GODAE

6. Coupled Model
Simulation
38 Year Mean
SST Bias

7. Observed
Coupled
Red: monthly bias

8. Composite Warm and Cold Events
Events exceed ERSST variance by
1.0 SD (warm)
0.75 SD (cold)
Heavy black line is mean
- 36 mo
+36 mo
Peak

9. SST Climatology on Equator
Red: coupled
model

10. Hindcast Skill Assessment
5-member ensemble over 22 years from
January and April initial conditions
Other months to follow
9 month runs
Initial atmospheric states 0000 GMT 19, 20, 21, 22, and 23 for each month
Reanalysis-2 archive .
Initial ocean states NCEP GODAS (Global Ocean Data Assimilation System) 0000 GMT 21st of each month
Same for all runs
GODAS operational September 2003

11. Hindcast Skill Assessment (cont)
So far 220 runs have been made
Hindcast skill
Estimated after doing a bias correction for each year
Uses model climatology based on the other years
Anomaly correlation skill score for Nino 3.4 region SST prediction
Skill maps
Global SST
U.S. temperature and precipitation.
Comparisons with CMP14 and CASST

12. Ensemble Mean
CASST
CMP14
April IC

13. CASST
Ensemble Mean
January IC
CMP14

14. Observed
6 Month Lead
(November)
from April IC
SST anomaly
for
Note Amplitudes

15. Observed
6 Month Lead
(August)
from January IC
SST anomaly
for
Note Amplitudes

16. Seasonally (3 month) Averaged SST Anomaly Correlation
Hindcast
Seasonally (3 month) Averaged
SST Anomaly Correlation
April IC
Note: large & persistent skill in tropics

17. SST Anomaly Correlation
Hindcast
Monthly Averaged
SST Anomaly Correlation
April IC
June-September
Left: New Coupled System
Right: CMP14

18. SST Anomaly Correlation
Hindcast
Monthly Averaged
SST Anomaly Correlation
April IC
October-January
Left: New Coupled System
Right: CMP14

19. Seasonally (3 month) Averaged SST Anomaly Correlation
Hindcast
Seasonally (3 month) Averaged
SST Anomaly Correlation
January IC
Note: large & persistent skill in tropics

20. SST Anomaly Correlation
Hindcast
Seasonally Averaged
SST Anomaly Correlation
January IC
Left: New Coupled System
Right: CMP14

21. U. S. Surface Temperature
Hindcast
3 month Averaged
U. S. Surface Temperature
Anomaly Correlation
April IC
Note: areas of persistent skill
> 60% at up to 6 month lead

22. U. S. Surface Temperature Hindcast Skill 3 Month Averages April IC
Comparison with CPC
CCA Method
Note: Coupled System skill
Has different geographical
Distribution than CCA

23. U. S. Surface Temperature Hindcast Skill 3 Month Averages January IC
Comparison with CPC
CCA Method
Note: Coupled System skill
Has different geographical
Distribution than CCA

24. Note: areas of persistent skill > 60% at up to 6 month lead
Hindcast
3 month Averaged
U. S. Precipitation
Anomaly Correlation
April IC
Note: areas of persistent skill
> 60% at up to 6 month lead

25. Note: Coupled System skill
U. S. Precipitation
Hindcast Skill
3 Month Averages
April IC
Comparison with CPC
CCA Method
Note: Coupled System skill
complementary to CCA

26. Note: Coupled System skill
U. S. Precipitation
Hindcast Skill
3 Month Averages
January IC
Comparison with CPC
CCA Method
Note: Coupled System skill
complementary to CCA

27. MJO Forecasts (W. Wang) Experiments
damp: GFS03 with damped SST anomalies
clim: GFS03 with climatological SSTs
amip: GFS03 with observed SSTs
coup: CFS03 with MOM3 ocean analysis
All forecasts to 45 days
Composite results

28. (Max pos. ampl. Over IO) (Decay) (Initiation) (Max pos. ampl.
Over WPAC)
Phase 3
(Max pos. ampl.
Over IO)
Phase 2
Phase 4
Phase 1
(Decay)
(Initiation)

29. Note: coupling necessary for propagation in Phases 1-3
Days 1-30
Observed
SST Expt.
Damped
Climo
AMIP
Coupled
Note: coupling necessary for propagation in Phases 1-3

30. Summary and Conclusions
CFS03 hindcast skill for January and April initial conditions ( ) have been evaluated
For April, the SST AC skill over Nino 3.4 is better than CMP14 and CASST at all leads
For January, the SST AC skill over Nino-3.4 is better than CMP14 and CASST for all leads, except lead 2

31. Summary and Conclusions (cont)
Ensemble mean forecasts for U.S. temperature and precipitation show comparable skill to CPC’s CCA method.
This skill may be complementary to CCA as it manifests itself in different geographical areas and can be used in CPC’s operational seasonal consolidated forecast.
Hindcasts for the rest of the calendar months are being performed
Implementation is being planned for late 2004

32. Backup Slides

33. New Climate Positions at NCEP/EMC
UCAR Visiting Scientist Position at NCEP/EMC
Work with NCEP Coupled Model
NCEP Climate Team Leader (GS-15)
Coordinate development activities with community
Provide strategic guidance on NCEP’s Climate Numerical Modeling activities
Participate actively in development activities with EMC staff

35. RMS Error
April

36. RMS Error
January