1. Evolution of the 2006-07 El Niño : The Role of Intraseasonal to Interannual Time Scale Dynamics Michael J. McPhaden NOAA/PMEL Seattle, Washington CLIVAR ENSO Workshop Guangzhou, China 26-28 November 2007

2. Correo - Perú 2 August 2006 “ENSO-neutral conditions are expected to continue for the next one to three months, with a 50% chance that weak El Niño conditions will develop by the end of 2006.” NCEP, 10 Aug 2006

3. Ni ñ o-3.4 Predictions from July 2006 Initial Condition Compiled by the International Research Institute for Climate and Society “ENSO-neutral conditions are expected to continue for the next one to three months, with a 50% chance that weak El Niño conditions will develop by the end of 2006.” NCEP, 10 Aug 2006 “Despite considerable efforts in model and forecast system development, progress in improving prediction skill has been very modest in recent years…” Science, 15 Dec 2006

4.  Build up of excess heat content along equator is a necessary precondition for El Niño to occur.  The time between El Niños is determined by the time to recharge.  El Niño purges excess heat to higher latitudes, which terminates the event. Upper Ocean Heat Content (Based Recharge Oscillator Theory of Jin, 1997) Warm Water Volume (WWV): An Index for Upper Ocean Heat Content Meinen & McPhaden, 2000 WWV based on BMRC analysis of TAO/TRITON, XBT and Argo data

5. 2006-07 El Ni ñ o

6. January 2006-September 2007 NCEP Forecast, 9 Mar ‘ 06: “ La Ni ñ a conditions are expected to continue during the next 3-6 months. ” What happened in the next 3-6 months: Unexpected episodic relaxation of the trade winds triggers onset of El Ni ñ o

7. January 2006-September 2007 Aug-Oct ‘06: Strong westerly wind bursts and downwelling Kelvin waves amplify warming.

8. MJO Convection Indian | Pacific | Atlantic Mar 2006 Feb 2007 cloudy/wet clear/dry Cloudiness & Rainfall (OLR, 5°N-5°S) Slow eastward progression of convection along the equator punctuated by episodic intraseasonal convective flair ups. Some of the intraseasonal variability originates over the Indian Ocean in the form of the “Madden- Julian Oscillation.”

9. Peak Conditions

11. January 2006-September 2007 Late Dec ‘06-Feb ‘07: Sudden demise linked to strengthening trade winds and rapid thermocline shoaling. NCEP Forecast, 7 Dec ‘06: “El Niño conditions are likely to continue through May 2007.”

12. Demise: Indian Ocean Influence?

13. Linear Equatorial Wave Model (McPhaden and Yu, 1999) Purpose: Compare magnitude of Kelvin waves generated at the western boundary via Rossby wave reflection (“delayed oscillator”) vs directly wind force upwelling Kelvin wave  Daily ECMWF wind forcing, 1979-2007  Rectangular basin, 80°W-120°E  Kelvin plus 6 Rossby waves (long wave approximation)  4 vertical modes  Linear damping (12 mon time scale for first vertical mode)  Boundary reflections 80% efficient.  Anomalies relative to mean seasonal cycle  Detrend wind forcing and sea level output

14. Model and Observations SST Heat Content T/P-Jason SL Model SL TAO/TRITON

15. Model Wind-Forced and Boundary Generated Kelvin and Rossby Waves Rossby Kelvin Kelvin Rossby Wind-Forced W. Boundary Wind-Forced E. Boundary

16. Summary  The 2006-07 El Ni ñ o was a weak-to-moderate amplitude “dateline” event.  Ocean heat content provided 1-2 season lead time forecast skill during developmental phase. However, onset, amplitude, and demise were not well predicted.  Intraseasonal MJO was a significant source of high frequency atmospheric and oceanic variability and one of the factors confounding attempts to forecast the evolution of the event.  Strongest westerly wind bursts in Aug & Oct 2006 occurred after onset of warming, consistent with the idea of “ state dependent stochastic forcing. ”  Strongest MJO event occurred coincident with basin scale warming in December 2006 following the termination of the IOD event.  MJO-related easterlies in Dec 2006 forced an upwelling Kelvin wave response that abruptly accelerated the demise of the El Ni ñ o.

17. Conclusions  One path to improved ENSO forecast skill is to improve the representation of high frequency atmospheric variability, especially that related to the MJO, in forecast models.  It’s important to accurately represent tropical Indian Ocean variability and Indo-Pacific atmospheric teleconnections in seasonal forecasts models.