R/V Revelle over Kuroshio Extension, May’05

1. Coupled Decadal Variability in the North Pacific: An Observationally-Constrained Idealized Model B. Qiu, N. Schneider and S. Chen Department of Oceanography University of Hawaii at Manoa R/V Revelle over Kuroshio Extension, May’05

2. North Pacific mean SSH field (Niiler et al. 2003) Points • Observed decadal variability in the Kuroshio Extension _(KE; bimodal states, connections to surface forcing) • KE’s impact on the regional SSTs • Is the observed decadal variability a coupled mode?

3. North Pacific mean SSH field (Niiler et al. 2003) Altimeter-derived SSH variability

4. Semi-monthly KE paths (1.7m SSH contours) (Jan-Aug)

5. Annually averaged SSH field (1994-2005)

6. Jet path length Eddy kinetic energy Jet position

7. PDO index EKE level

8. PDO index EKE level

9. PDO index EKE level

10. PDO index EKE level cf. Deser et al. (1999) found a similar lag (~4 yr) between the KE intensification and wind forcing from ’70s to ’80s

11. Pacific Decadal Oscillations(Mantua et al. 1997) • Center of action of wind forcing is in the eastern half of the N Pacific basin • Positive (negative) phase of PDO generates – (+) local SSH through Ekman divergence (convergence)

12. Nonseasonal NCEP wind stress curl EOF mode 1 (17.8%) spatial pattern weighting function

13. EKE level SSH anomalies along 34°N PDO index center of PDO forcing

14. SSH vs. wind stress forcing

15. Observed vs modeled SSH anomalies along the 32-34°N band

16. Observed vs modeled SSH anomalies along the 32-34°N band The linear Rossby wave model hindcast well the transitions of the KE’s dynamic state; it underestimates the responses associated with the stability of the jet.  Taguchi’s talk

17. Point 1: forcing vs response scales Although the y-scale of wind stress curl anomalies in the eastern N Pacific is large (>20°lat.), the forced oceanic signals in the west can have a much smaller y-scale due to the y-dependent Rossby wave speed -TcR2 W = (2X+TcR)∂cR/∂y Qiu (2003, JPO)

18. Yearly-averaged SSH anomalies

19. Point 2: ocean is an effective “integrator” For SSH signals averaged in the KE, only the first two spatial modes of the wind forcing are important hKE: full forcing hKE: forcing with n=1,2

20. Point 2: ocean is an effective “integrator” For SSH signals averaged in the KE, only the first 2 spatial modes of the wind forcing are relevant hKE: full forcing hKE: forcing with n=1,2 cumulative hKE variance cumulative curl variance

21. SST anomaly time series in the KE region

22. SST anomaly time series in the KE region 10 yr 1 yr

23. Impact of the KE variability on the regional SST signals SST anomalies SSH anomalies (proxy for KE strength) Position of KE axis

24. Impact of the KE variability on the regional SST signals SST anomalies are caused by both the lateral migration and strength change of the KE jet e.g. Qiu (2000, JPO); Vivier et al. (2002, JPO); Kwon and Deser (2006, JCl)

25. SST anomaly time series in the KE region 10yr 1 yr Climate noise model

26. SST anomaly time series in the KE region 10yr 1 yr Climate noise model hindcast by linear Rossby wave model

27. Is ocean merely a passive “integrator”? Atmosphere wind stresses SST KE jet advection lateral shift

28. Wintertime (JFM) rms net surface heat flux variability (NCEP reanalysis) Wintertime (JFM) precipitation (proxy for winter stormtracks)

29. Does the KE SST anomalies affect the atmosphere? Atmosphere ? stormtracks Qnet wind stresses SST KE jet advection lateral shift

30. SST’s impact from the lagged correlation approach (Czaja and Frankignoul 1999, 2002) Let an atmospheric variable C(t) be: C(t) = f(t) + F( T ) ~ f(t) + b T(t) where f represents intrinsic atmospheric processes, b, the dynamic feedback coefficient, and T, SST anomalies. Taking lagged correlation with T(t-m) and ensemble average: {T(t-m)C(t)} = {T(t-m)f(t)} + b{T(t-m)T(t)} if m > a few weeks The covariance between SST and C(t) when SST leads is proportional to the strength of the feedback. 0

31. Lagged correlation between KE SSTA and NP curl (tau) field • NCEP reanalysis data (1948-2005) • ENSO signals (Nino 3.4) regressed out • Different curl patterns with +/- lag • 95% conf. level = 0.22 (57 samples) p’ > 0; curl(tau) <0 p’ < 0; curl(tau) >0

32. Lagged correlation between KE SSTA and NP curl (tau) field • NCEP reanalysis data (1948-2005) • ENSO signals (Nino 3.4) regressed out • Different curl patterns with +/- lag • 95% conf. level = 0.22 (57 samples) p’ > 0; curl(tau) <0 p’ < 0; curl(tau) >0

33. An air-sea coupled system (cf. Jin 1997): intrinsic feedback x=-W x=-W+L x=0

34. Parameter values appropriate for N. Pacific: band of action bandconfiguration advection parameter oceanic damping timescale power of stochastic wind stress forcing(n=1) power of stochastic wind stress forcing(n=2) power of stochastic heat flux forcing air-sea coupling parameter

35. W1 (t) W2 (t)

36. Uncoupled case (b=0) where with n=1,2

37. Uncoupled case (b=0) AR-1

38. Uncoupled case (b=0) AR-1 N.B. This result includes the “spatial resonance mechanism” (Jin 1997; Frankignoul et al. 1997; Neelin and Weng 1999). Spatially-varying wind forcing alone is not sufficient.

39. Coupled case (b=0) amplification coefficient

40. Schematic for the coupled oscillation W L w Ekman divergence h<0 time H C half of the optimal period ~ (W/2)/cR

41. Coupled case (b=0)

42. Coupled case (b=0)

43. How large is the SST-induced wind forcing? (in the eastern half of the NP along the KE band) 1.44 vs 1.23

44. Summary • SST and other oceanic variables in the KE region are dominated by changes with a period of ~10 yr. • Ocean dynamics alone “reddens” the SST spectrum, but generates no observed decadal spectral peak. • SST anomalies in the KE region induce an overlying-high and downstream-low pressure anomaly. This feedback favors a resonant, air-sea coupled mode with a preferred time scale of ~10 yr. • While the variance explained by this coupled mode is small for atmosphere, it is the driving force for the bimodal changes of the KE system (SST, eddy level, RG and path). • Nonlinear WBC dynamics is important for the intensity of the coupled mode, but not critical to the existence of the mode itself. (JCl preprint: www.soest.hawaii.edu/oceanography/bo)

45. EKE level SSH anomalies along 34°N PDO index center of PDO forcing

46. Coupled oscillation: a different interpretation v’Ty<0 L H C W h<0 W C h>0 L H v’Ty>0 Jin (1997) L H W C h<0 cold adv. this study

48. PDO time series

49. Concurrent TMI and scatterometry measurements Warm (cold) SST ↓ High (low) wind speed Enhanced evaporation under high wind speed forms cool SST In-phase relationship of SST & wind suggests ocean’s influence on atmosphere Nonaka and Xie (2003, JCl)

50. Sutton and Mathieu (2002) cf. Yulaeva et al. (2001); Liu and Wu (2004)