Seasonality of the ENSO Recharge Oscillator

1. EGU 2005 Vienna, April 2005 Seasonality of theENSO Recharge Oscillator Gerrit Burgers1, Geert Jan van Oldenborgh1 and Fei-Fei Jin21Royal Netherlands Meteorological Institute2Florida State University, Tallahassee

2. Natural variables TE 1st natural variable hequatorial zonal mean thermocline depth 2nd natural variable Jin, JAS 1997: recharge oscillator picture Kessler, GRL2002: Is ENSO a cycle or a series of events? McPhaden, GRL2003: h and persistence barriers Clarke and Van Gorder, GRL 2003: Improving ENSO forecasts

3. ENSO Recharge oscillator From Jin JAS 1997 After Kessler GRL 2002

4. Four- and two-variable form h=0.5(hE+hW)  • Four-variable form (, hW, hE and TE) • has pair of oscillating modes + mode that decays • On “slow” manifold, hE lin. comb. of h and TE • Two-variable form (hand TE) follows from reduction • of two-variable form to slow manifold (Burgers, van Oldenborgh and Jin, in preparation)

5. Simplest description of ENSO From direct fit of 2-variable system to observations*). Agrees with independent fit of 4-variable system. TE and h normalized on 1. Simplest picture of ENSO *) monthly time series over 1980-2002 of TE ,  , hE , hw , h anomalies

6. Seasonality • Niño3 peaks • around Christmas • phase locking • “spring barrier” in TE • “winter barrier” in h • (McPhaden, GRL 2003)  Let us consider seasonal recharge oscillator fit

7. Seasonal fit on 1-month forecasts of Seasonal recharge oscillator fit NB: noise driven system then gives automatically right amplitudes TE and h seasonal cycle matrix elements seasonal cycle amplitudes

8. Seasonal cycle in  and  , (month-1) seasonal cycle in frequency and decay constants

9. Spring barrier in observations Spring barrier in observed seasonal correlation (after McPhaden, GRL2003):

10. Spring barrier recharge oscillator NB: at zero lag, fit gives automatically right correl-ation TE and h  Spring barrier in seasonal correlation of seasonal recharge oscillator system obs 

11. potential predictability *) seasonal recharge oscillator   skill ECMWF operational forecast 1987-2001  Spring barrier: predictability *) is NOT forecast skill, but predictability of linear system with parameters and noise properties from seasonal fit

12. Residues for fit on 1-month forecasts Seasonal cycle in goodness of fit TE • dashed lines: normalized on amplitude T, h • solid lines: normalized on amplitude monthly change in T, h h In August, recharge oscillator adds very little to persistence Skill in predicting changes in spring

13. Spectra: multiple time scales (1)? Annual mean version: single peak Seasonal version: slight shoulder around 0.7 cpy

14. Spectra: multiple time scales (2)? 23 years 2000 years width spectral peak increases comparedtofixed ,  case simulation with phase dependent ,  [  =0.15+0.04cos ,  =0.040.06cos(/4) ]

15. Phase dependent recharge oscillator II I I I I III IV N 99 65 41 71 start DJF JFMA 2/ 52 35 33 45 1/ 12 200 90 10  0.8 0.7 0.4 0.6 III IV start = season when phase usually starts  = normalized error of seasonal dependent fit

16. Phase as a function of time T  4 year

17. h Phase and season T  IV III II I 1988 IV 1987 III 1986 II I

18. TE and h natural variables • Simplest formulation of • ENSO recharge oscillator: • Seasonal recharge oscillator describes spring barrier well • Predictability estimate if ENSO would be pure recharge oscillator • 12 - 18 months, depends on season • Both variations in decay/growth  and phase propagation  • in recharge oscillator framework • - Phase propagation in spring, decay in winter • - Growth before El Nino, phase propagation at El Niño Conclusions