1. Preferred Modes of Variability and Their Relationship with Climate Change The Pennsylvania State University Department of Meteorology Seok-Woo Son and Sukyoung Lee

2. - Dominant internal variability of the atmosphere Annular Mode SHNH [u] SLP Thompson et al. 2000  Leading EOF of SLP  Zonally symmetric  Quasi-barotropic  Useful for understanding internal variability  Useful for understanding climate change (?)

3. SH [u] response to global warming SH Annular Mode latitude pressure (hPa) NH Annular Mode pressure (hPa) NH [u] trend 1968-1997 Thompson et al. 2000 Kushner et al. 2001

4. “Spatial pattern” of annular mode ≈ recent trend in the observed and simulated zonal-mean circulation To what extent annular mode is capable of predicting zonal-mean climate change?

5. Purpose and Approaches Annular mode vs. Climate change Annular mode – EOF1 of [u] (regressed against PC1 time series) Climate change – difference of [u] between any two adjacent runs Internal variability of [u] with a help of EOF1 and EOF2 Structure of [u] in the statistically steady state ( [u] )Total 49 simulations by differing radiative heating in a simple GCM Evaluate the predictability of zonal-mean climate change by annular mode in terms of their spatial structures.

6. Numerical Model  A dynamic core of GFDL GCM (symmetric boundary cond.)  Driven by relaxing T toward T e with timescale of 30 days  R30L10 but zonal wave number 15 T e (C,H) = T base + ΔT e (C,H) C : high-latitude cooling (K/day) H : tropical heating (K/day)  Dissipated by linear friction and 8 th order hyperdiffusion

7. Numerical Model (Cont.)  Statistics are derived from the last 4500 days of each 5000-day integration. Data of both hemispheres are used.  Total 49 realizations C (0.00, 0.17, 0.33, 0.50, 0.67, 0.88, 1.00) K/day H (0.00, 0.33, 0.67, 1.00, 1.33, 1.67, 2.00) K/day [u] (C,H)=(0.17,0.33) Single Jet Intermediate Jet Double Jet (C,H)=(0.17,1.67) (C,H)=(0.83,0.33)

8. [u] : Structure of Westerly Jets  Strong C & weak H → Double Jet  H ≥ 1.00K/day → Single Jet SJ WJ DJ

9. One-point correlation of 250-hPa [u]' Internal variability of the jets Transition WJ Poleward Propagation DJ Zonal-index (Jet Meander) SJ [u] & EOFs

10. Time series of PC1 and PC2Correlation PC1 vs. PC2 Transition Poleward Propagation Zonal-index (Jet Meander) WJ DJ SJ Poleward Propagation: i. Correlation between PC1 & PC2 is very high ii. Var(EOF2) is comparable to Var(EOF1)

11. Shading γ ≥ 0.5 Shading χ ≥ 0.5 Collocates with intermediate- and double-jet

12. Annular mode & Climate change in the modeI  Annular mode : EOF1 of [u]  Climate change : Difference of [u] between two adjacent runs δ[u] H (0.50,1.00) = [u] (0.50,1.33) - [u] (0.50,1.00) δ[u] C (0.50,1.00) = [u] (0.67,1.00) - [u] (0.50,1.00) [u] is regressed against PC1 time series, unit of m/s. [u] (0.50,1.00) δ[u] C (0.50,1.00)δ[u] H (0.50,1.00)

13. EOF1 & δ[u] C EOF1 & δ[u] H Predictability of Climate change by Annular mode Predictability is always poor in a poleward propagation regime. I. Global measure : pattern correlation between EOF1 and δ[u] from 150-950 hPa and 10-80 ˚ Shading correlation ≥ 0.8

14.  Annular mode in the model is associated with eddy fluxes. Increase of H → enhances subtropical baroclinicity and intensifies Hadley circulation Poor predictability of δ[u] H in a zonal-index regime  δ[u] H is associated with both eddy fluxes and mean-meridional circulation. Increase of C → enhances extratropical baroclinicity  δ[u] C is associated with eddy fluxes.  Predictability of δ[u] C would be better than that of δ[u] H.

15. Summary Strong C & weak H → Double Jet H ≥ 1.00 K/day → Single Jet Structure of Westerly Jet Internal Variability Strong C & weak H → Poleward propagation (Comparable effect of EOF2) Weak C & strong H → Zonal index (Dictated by EOF1) Broad transition zone Dependent on the dominant internal variability Relative good in a transition regime Predictability of Climate change by Annular mode

16.  Internal variability Both poleward propagation and zonal index (e.g., Feldstein 1998; Hartmann and Lo 1998) with γ ≈ 0.5 and χ ≈ 0.3 (Son and Lee 2005b). Application to the Southern Hemisphere [u]: structure of the jet SH  Applied to the SH climate change at equinoctial condition Global warming at SH → ENSO-like tropical heating & enhanced extratropical baroclinicity (Son and Lee 2005a) → increase of H and C.  Structure of the jet Wide range of interannual variability from single- to double-jet states EOF1 & δ[u] C SH EOF1 & δ[u] H SH

17. Application to the Southern Hemisphere (Cont.)  Predictability is marginally good in the SH-like parameter regime.  Annular mode may not be useful for understanding paleoclimate change. EOF1 & δ[u] C SH EOF1 & δ[u] H SH Slight climate drift to the poleward propagation regime → poor predictability.

18. Any comment and suggestion are welcome. Thank you! Contact information Seok-Woo Son: sus141@psu.edu

19. Dependency of internal variability to the mean flow  The meridional radiation of the waves is prohibited if the PV gradient of the ambient flow is sufficiently sharp (e.g., Hoskins and Ambrizzi 1993)  Poleward propagation of westerly anomalies may occur only when the PV gradient is relatively weak and broad. The latitudinal distance over which the value of 250-hPa quasi-geostrophic PV gradient ([q] y ) is greater than 60% of its maximum value. Shading for ≥ 35˚.

20. Prediction of Climate-change ‘Direction’ by Annular mode? [u] (0.50,100) δ[u] C (0.50,100)δ[u] H (0.50,100)  Climate change direction (positive or negative phase of annular mode) is determined not by the annular mode but by the nature of external forcing.  Climate change associated with C increase (broadening of extratropical baroclinic zone) → positive phase of annular mode (in phase).  Climate change associated with H increase (warming at tropics) → negative phase of annular mode (out of phase). + -

21. Prediction of Climate-change ‘Direction’ ? (Cont.) SH [u] response to global warming SH Annular Mode Kushner et al. 2001 Climate change in SH is in phase with SH annular mode. By the overwhelming effect of enhanced baroclinicity (C) over tropical warming (H) ? Climate change in SH: tropical warming & enhanced extratropical baroclinicity (Son and Lee 2005a) → increase of H and C.

22. A δφ C II. Local measure : latitudinal distance between extrema of EOF1 and δ[u] at 250 hPa δφ C : between EOF1 and δ[u] C EOF1 & δ[u] C (line A) δφ H : between EOF1 and δ[u] H measured at both subtropics and extratropics Predictability of Climate change by Annular mode

23. δφ C (low-latitude) δφ C (mid-latitude) δφ H (low-latitude) δφ H (mid-latitude) Shading δφ ≤ 2˚  Weak latitudinal dependency of δ[u] C prediction by annular mode.  Poor predictability of δ[u] H in a zonal-index regime is due to the mid-latitudes. Shading γ ≥ 0.5  Predictability is generally good when γ ≤ 0.5 or Var(EOF1) ≥ 2Var(EOF2)

24. A δφ C II. Local measure : Compare amplitude of 250-hPa |EOF1| and |δ[u]| at 250 hPa EOF1 & δ[u] C (line A) Prediction of Climate-change ‘Amplitude’ by Annular mode?

25. shading: δφ C ≤ 2˚shading: δφ H ≤ 2˚ ratio |δ[u]|/|EOF1| difference (|δ[u]| - |EOF1|) Predictable? No theories yet! Ratios vary only by a factor of two! Ratios of |δ[u] C | to |EOF1| are 0.3 to 0.8. Ratios of |δ[u] H | to |EOF1| are 1.0 to 2.5