1. 1 Assessment of the CFSv2 real-time seasonal forecasts for 2013 Wanqiu Wang, Mingyue Chen, and Arun Kumar CPC/NCEP/NOAA

2. 2 - Real-time skill assessment - Improve forecast through post-processing - Impact of initial condition - Systematic errors Relevance Diagnostics/monitoring of CFS real-time forecasts

3. 3 Outline 1. SST indices 2. Spatial maps 3. Anomaly correlation skill 4. Prediction of sea ice extent minimum

4. 4 1. SST indicies

5. 5 Nino34 DMI MDR SST indices Nino34  Stronger amplitude of both positive and negative phases  Delayed transition of ENSO phases at longer lead-time DMI  Good forecast for 2010 negative DMI.  Failed to reproduce positive DMI in 2012 MDR  Underestimate the amplitude of warm anomalies during Jan-Jul 2011  Too warm at the beginning of 2014.

6. 6 CFSv2 Nino34 SST raw anomalies Nino3.4 SST is near normal during 2013.

7. 7 CFSv2 Nino34 SST with amplitude correction Because of the weak amplitude, the correction does not have significant impact on the predicted Nino3.4 SST index.

8. 8 CFSv2 Nino34 SST with PDF correction Because of the weak amplitude, the correction does not have significant impact on the predicted Nino3.4 SST index.

9. 9 2. Spatial maps CFSv2 forecast is at a lead of 20 days or so. For example, forecast for Jun-Jul-Aug is from initial conditions of May 1-10 th. Impacts of atmospheric initial conditions should be largely removed. Anomaly = Total – Clim 1999-2010

10. 10 Forecast for MAM 2013  Weak anomalies in the Tropical Pacific. Relatively larger SST anomalies in the Tropical Atlantic.  Westward shift of observed pattern in N. Pacific  Larger amplitude of negative rainfall anomalies in equatorial Central Pacific. Incorrect rainfall parrern over the Nordeste and equatorial Atlantic.

11. 11 Forecast for MAM 2013  Good forecast of negative T2m anomalies over northwest of North America. Poor forecast for Eurasia..  Poor forecast of the Z200 anomaly pattern.

12. 12 Forecast for JJA 2013  CFSv2 failed to capture the spatial coverage of cold SST anomalies in the Tropical eastern Pacific.  CFSv2 produced reasonable pattern of tropical precipitation anomalies.

13. 13 Forecast for JJA 2013  CFSv2 failed to capture the observed warm anomalies over North America and Europe.  CFSv2 failed to capture the assicated Z200 anomaly patter.

14. 14 Forecast for SON 2013  CFSv2 captured the overall SST warmth and spatial anomaly patter..  Precipitation is reasonable, although the amplitude is small in both observation and forecast.

15. 15 Forecast for SON 2013  T2m anomalies in CFSv2 are too weak.  Overall Z200 pattern is not captured by CFSv2, although the model reproduced the positive anomalies in North Pacific.

16. 16 Forecast for DJF 2013/2014  CFSv2 reproduced the observed pattern but with weaker amplitude for the tropical negative anomalies.  CFSv2 predicted the observed above normal rainfall in the Tropical western Pacific and below normal rainfall in the Tropical central Pacific

17. 17 Forecast for DJF 2013/2014  CFSv2 captured overall T2m pattern in North America but failed to produced the observed anomalies in Eurasian continent.  CFSv2 captured the positive Z200 anomalies in polar regions but failed to reproduce the variability in mid-latitudes. It is interesting to see that Z200 anomalies in high latitudes are well reproduced in AMIP runs as well as the 0-day-lead forecasts. Since the AMIP simulation is quite reasonable, does the erroneous Z200 anomalies at 20-day-lead time mean the ocean surface conditions became erroneous after 20 days?

18. 18 Forecast for OND 2013  CFSv2 produced erroneous warm anomalies in the equatorial Central-Eastern Pacific.  CFSv2 incorrectly predicted below (above) normal rainfall over Maritime continent (western Pacific).

19. 19 Forecast for JFM 2014  CFSv2 failed to reproduce the observed negative anomalies.  Yet, the CFSv2 predicted reasonable rainfall pattern in the tropical Pacific, while the prediction of rainfall anomalies in the Indian Ocean and Atlantic is poor.

20. 20 3. Anomaly correlation skill

21. 21 Pattern correlation over tropical Pacific 20S-20N Incorrect rainfall anomaly pattern in the Pacific (slide 19)

22. 22 Pattern correlation over tropical Indian Ocean 20S-20N

23. 23 Pattern correlation over tropical Atlantic 20S-20N

24. 24 Pattern correlation over tropical oceans 20S-20N

25. 25 Pattern correlation over NH  T2m skill is very changeable with successful prediction for MAM 2012 and low skill for many other periods.  Very low precipitation skill for most of the period  Moderate PNA skill after SON 2011, except for 2013 Spring. 20N-80N

26. 26 4. Artic September sea ice extent

27. Obs=5.35 CFSv2

28. CFSv2 predicted sea ice extent for September 2013 (10 6 km 2 ) Obs=3.61 Observation  CFSv2 underestimated sea ice extent in the prediction from Jan – Aug 2013 initial conditions.