Decadal ENSO-like patterns and the modulation of ENSO teelconnections

1. Decadal ENSO-like patterns and the modulation of ENSO teelconnections

2. Collaborators R. Colman, X. Wang, G. Wang, Bureau of Meteorology M. Haylock, Climatic Research Unit, University of East Anglia, U.K. S. McGregor and N. Holbrook, Macquarie University, Sydney.

3. Thank you Axel, Henk, …

4. Topics we’ll address: • Observed climate variability • Dec modulation of ENSO’s impact on Australia • Modulation coherent with IPO/PDO • CGCM experiments and analysis • Is the IPO/PDO causing the modulation? • What causes ENSO-like decadal patterns? • Predictability of • modulation • off-equatorial “wings”

5. El Niño affects Australian Rainfall JJASON rainfall deciles for El Nino years

6. 20th Century Observations

8. BMRC CGCM (Power et al. 1998; 2006) - seasonal prediction (Wang et al. 2000) • MOM OGCM • Power, Kleeman, Tseitkin and Smith, 1995 • Pacanowski et al. 1991 • L25, 2 deg by (0.5, 6 deg) • hybrid mixing (ml, Ri) • thermodynamic sea-ice • R21 L17 “unified” AGCM Colman 2000 • spectral, Rotstayn (1999) prognostic clouds; Tiedtke (1989) convection; GW drag (Palmer et al. 1986); McAvaney & Hess (1996) BL scheme • Q, Sf flux adjusted

10. 15-year-long Perturbation Experiments were conducted First 4 years only (for illustration)

11. Discovery: Australian response to ENSO is asymmetric in observations and CGCM – this has important implications for seasonal forecasting services and helps to explain modulation of ENSO teleconnections by ENSO-like decadal modes Observations Coupled GCM Since decadal variability in the SOI resembles indices for PDO and IPO, the PDO and IPO can appear to modulate the ENSO’s impact on Australia, even in absence of predictability beyond 1 year Power et al. 2006: J. Climate.

12. Origin of ENSO-like decadal patterns

13. Suppose ELF is a low pass filtered ENSO index, e.g.: 1m ELF = ------------ Σ E t-k., and r(E, SST)= α. m+1k=0 < ELF, SSTLF> Then r(ELF, SSTLF) = ________________________ . (1) √ [ < ELF, ELF > <SSTLF, SSTLF> ] Now < ELF, ELF > = < Et, Et + Et-1 + Et-2 + Et-3 + … + Et-m> / (m+1)2 + < Et-1, Et + Et-1 + Et-2 + Et-3 + … Et-m> / (m+1)2 + … + < Et-m, Et + Et-1 + Et-2 + Et-3 + … Et-m>/ (m+1)2 = (m+1)/(m+1)2=1 / (m+1), (2) where we have used the fact that E is white noise. Similarly < SSTLF, SSTLF > = 1/(m+1), so (3) < SSTLF, ELF > = < SSTt, Et + Et-1 + Et-2 + …+ Et-m>/ (m+1)2 + < SSTt-1, Et + Et-1 + Et-2 + … Et-m> / (m+1)2 + … + < SSTt-m, Et + Et-1 + Et-2 + … Et-m>/ (m+1)2 = (m+1) < SSTt, Et >/ (m+1)2 = α/ (m+1). (4) Using (2)-(4) in (1) then gives r(ELF, SSTLF) = α. Power and Colman, 2005: Climate Dynamics

14. Facts: • The existence of decadal teleconnection patterns in low pass filtered records does not imply decadal predictability • The existence of decadal signals in low pass filtered records does not imply decadal predictability. Power and Colman, Climate Dynamics, 2006

15. Long-standing puzzle:Why do decadal ENSO-like patterns appear meridionally broader than their interannual counterparts? See e.g., Zhang et al., 1997; Power and Colman, 2005; N. Mantua “fat ENSO”

16. Off-equatorial SST: “wings” Power and Colman, Climate Dynamics, 2006

17. ENSO-modifed Hasselmann/Red Noise process • dT/dt = aT + bE +cN • RN with ENSO-like pattern Power and Colman (2006), Newman et al. (2003), Schneider and Miller (2001)

18. Discovery: Off-equatorial sub-surface variability is a low pass filtered version of ENSO variability Decadal-long Perturbation Experiments Discovery: Sub-surface ENSO-driven off-equatorial decadal variability is highly predictable Off-equatorial T(z): “wings”  13 years  Power and Colman, 2006: Climate Dynamics

19. Similar behaviour evident in a wind-forced shallow water (KNMI) model • offeq=lpf(n3) • lag increases with latitude • LF contribution increases with latitude

20. (Weak) Dynamical low pass filtering by eastern boundary reflections Dispersion curves for equatorially trapped modes Incident KWs VLF westward propagating waves

21. Strong low pass filtering, latitude dependence Qiu et al. 1997: response to incident KW trapped to EB => Power and Colman, 2006: Thank you Climate Dynamics reviewer!

22. You can provide plausible qualitative explanations for modulation and wings without need for decadal predictability in ENSO indices

24. First EOFs from Wind-forced Shallow Water Model Forcing applied everywhere Off-equatorial forcing only This meeting: Axel, Shayne, Daniela, Rowan, Tom, Shang-Ping Xie, Marcelo, Robert, Kleeman et al., Nonaka et al., Wang et al., …

25. Conclusions • The ENSO-Australian rainfall relationship is non-linear: • Random changes in ENSO activity (e.g. relative frequency of El Niño/La Niño events) will give a decadal ENSO-like pattern • The same random changes, when coupled with the non-linear ENSO-Australian rainfall relationship can give modulation without predictability on decadal time-scales

26. 4. Not all we have seen can be explained as simply random changes in ENSO activity: e.g. IPO/PDO has broader structure than ENSO pattern 5. This arises because ocean acts as a low pass filter of ENSO forcing (i) dT/dt = -aT + bE + cN; a,b,c > 0 • ENSO drives variability in the ocean that is predictable beyond interannual time-scales 7. Some of the multiyear/decadal variability in ENSO indices might be predictable => so might some of the modulation Conclusions (ii)

27. Key References • Stochastic Theories for IPO/PDO • Power and Colman, 2005: Climate Dynamics • Non-linearity in ENSO teleconnections, predictability of interdecadal changes in ENSO teleconnections • Power, Haylock, Colman and Wang, 2006: Journal of Climate.