1. Ocean Processes and Pacific Decadal Climate Variability Michael Alexander Earth System Research Lab Physical Science Division NOAA

2. Why should we look to the ocean for low-frequency (> 1 season) variability? Thermal Inertia –4 m of ocean holds as much heat as atmosphere above Water takes a long time to heat up and cool down Temperature anomalies once created persist Dynamical Processes –Some very slow Currents slow (1 m/sec) –Advection of temperature anomalies can take many years Adjustment of midlatitude currents (~5 years - decades) Exchanges with the deep ocean can take decades to centuries! Important Implications –Marine Ecosystems (fisheries) –Atmospheric Circulation ( SSTs => Atmosphere?)

3. Midlatitude SST Variability There are many ways that SST anomalies form –We will explore just a few mechanisms –Ones that are part of larger Pacific climate signals Mechanisms for generating midlatitude SST anomalies –Surface heat fluxes - Climate Noise –Upper Ocean mixing processes –“Atmospheric Bridge”: Teleconnections with ENSO –Changes in ocean currents Wind driven (through ocean Rossby waves) Thermal/salt driven: Thermohaline (Atlantic) - next week

4. Simple model for generating SST variability “stochastic model” Heat fluxes associated with weather events, “random forcing” Ocean response to flux back heat which slowly damps SST anomalies SST anomalies form Air-sea interface Fixed depth ocean No currents Bottom

5. The Simple Ocean’s SST Anomaly Variability time SSTA Complex behavior with decadal anomalies! 10 yrs SST n+1 = *SST n +  =constant;  = Random number Log plot of SSTA Spectra Period 1yr 10 yr No damping SSTA Variance 1 mo Atm forcing

6. Simple Ocean Model: correspondence to the real world? Observed and Theoretical Spectra for a location in the North Atlantic Ocean Theoretical spectra of Simple ocean model Observed OWS Temperature Variance 1 year1 month (Hz) is the frequency period: Atmospheric forcing and ocean feedback estimated from data

7. Seasonal cycle of Temperature & MLD in N. Pacific Reemergence Mechanism Winter Surface flux anomalies Create SST anomalies which spread over ML ML reforms close to surface in spring Summer SST anomalies strongly damped by air-sea interaction Temperature anomalies persist in summer thermocline Re-entrained into the ML in the following fall and winter Q net ’ Alexander and Deser (1995, JPO), Alexander et al. (1999, J. Climate) MLD

8. Reemergence in three North Pacific regions Regression between SST anomalies in April-May with monthly temperature anomalies as a function of depth. Regions

9. “The Atmospheric Bridge” Meridional cross section through the central Pacific (Alexander 1992; Lau and Nath 1996; Alexander et al. 2002 all J. Climate)

10. Mechanism for Atmospheric Circulation Changes due to El Nino/Southern Oscillation Horel and Wallace, Mon. Wea Rev. 1981 Latent heat release in thunderstorms Atmospheric wave forced by tropical heating

11. El Niño – La Niña Composite: DJF SLP Contour (1 mb); FMA SST (shaded ºC) Model Obs Impact midlatitude SSTs: modest ~2 mb SLP And complex - varies with season

12. Ocean Surface Currents Surface currents mainly driven by wind Subtropical Gyre Subtropical Gyre Subtropical Gyre

13. Leading Pattern (1st EOF) of North Pacific SST + Phase - Phase K Mantua et al. (BAMS 1997) PC 1 SST North Pacific The Pacific Decadal Oscillation (PDO)

14. Extratropical Signature Tropical Linkages “NP” Index (Nov-Mar) 1900-2002 Trenberth and Hurrell (1994) Pacific Decadal Atmospheric Variability EOF1 SLP Pacific/Arctic PC: Regressed on full field Independent of the Atlantic

15. Wet Precipitation (land only) Dry 180° Warm Cold Surface Air Temperature 180° Precipitation and Temperature Patterns Associated with NP Index

16. Alaska – Japan Alaska/Canada SST PC 1 2000 254777 (- NP Index) 1900 PRECIP SLP AIR T North Pacific Climate Indices (Winter) Deser et al. (J. Climate, 2004)

17. What Causes the PDO? and Pacific Decadal Variability in General? Random forcing by the Atmosphere –Aleutian low => underlying ocean Signal from the Tropics? –Perhaps associated with decadal variability in the ENSO region Midlatitude Dynamics –Shifts in the strength/position of the ocean gyres –Could include feedbacks with the atmosphere

18. Aleutian Low Impact on Fluxes & SSTs in (DJF) Leading Patterns of Variability AGCM-MLM EOF 1 SLP (50%) SLP PC1 - Qnet correlation SLP PC1 - SST correlation EOF 1 SST (34%)

19. PDO or slab ocean forced by noise? From David Pierce 2001, Progress in Oceanography

20. - NP Index 19002000 254777 (Boreal Winter) Climate Indices Indian Ocean SST (poleward side) (C Eq Pac)  Cloud  SLP (“SOI”) (Indian – Pac) - SPCZ Rain (eq’ward side) SPCZ Rain Tropical

21. “ Decadal” variability in the North Pacific: tropical (ENSO) Connection? Observed SST Nov-Mar (1977-88) – (1970-76) MLM SST Nov-Mar (1977-88) – (1970-76)

22. Wind Generated Rossby Waves West East Atmosphere Ocean Thermocline ML L Rossby Waves 1)After waves pass ocean currents adjust 2)Waves change thermocline depth, if mixed layer reaches that depth, cold water can be mixed to the surface

23. Observed Rossby Waves & SST Schneider and Miller 2001 (J. Climate) March KE Region: 40°N, 140°-170°E SST OB S T 400 SST fcst Correlation Obs SST hindcast With thermocline depth anomaly Forecast equation for SST based on integrating wind stress (curl) forcing and constant propagation speed of the (1 st Baroclinic) Rossby wave

24. Ocean Response to Change in Wind Stress Contours: geostrophic flow from change in wind stress Shading: vertically integrated temperature (0-450 m): 1982-90 – 1970-80 Deser, Alexander & Timlin 1999 J. Climate SLP 1977-88 - 1968-76

25. Response to Midlatitude SST Anomalies SST Anomaly (°C) specified as the Boundary Condition in an AGCM CI = 0.5°C 2.5 Peng et al. 1997 J Climate; Peng and Whittaker 1999, J. Climate

26. Response to Midlatitude SST anomalies 30 120W120E Cross Section of heights along 40ºN CI = 5m Heights 250 mb CI = 5m 200 500 1000 40 30 120W120E -20

27. PDO: Multiple Causes? Newman, Compo, Alexander 2003, Schneider and Miller 2005, Newman 2006 (All in Journal of Climate) Interannual timescales: –Integration of noise (Fluctuations of the Aleutian Low) –Response to ENSO (Atmospheric bridge) Decadal timescales (% of Variance) –Integration of noise (1/3) –Response to ENSO (1/3) –Ocean dynamics (1/3) –Predictable out to (but not beyond) 1-2 years We developed a statistical method gives skillful PDO prediction out ~1 year Trend –Most Prominent in Indian Ocean and far western Pacific –Likely associated with Global warming

28. Prediction of the PDO Monthly values PDO Index 1998 Transition? Curve Extrapolation

29. Summary Climate noise –Expect decadal variability when looking at SST time series Atmospheric Bridge –Cause and effect well understood –Tropical Pacific => Global SSTs –Influence of air-sea feedback on extratropical atmosphere complex PDO (1 st EOF of North Pacific SST) –Thermal response to random fluctuations in Aleutian Low –A significant fraction of the signal comes from the tropics Extratropical ocean integrates (reddens) ENSO signal Decadal variability in tropics – impact atmosphere & ocean –Ocean currents & Rossby waves in western N. Pacific –extratropical air-sea feedback: modest amplitude Other Processes/modes of variability –Other variability besdies PDO, focused on west Pacific –Extratropical => tropical interactions

30. Extratropical => Tropical Connections Meridional cross section through the central Pacific Subduction Upwelling +entrainment (SFM: Vimont et al. 2003; Subduction: Schneider et al. 1999 JPO) Seasonal Footprinting Mechanism (SFM) Winter: Intrinsic atmospheric variability Spring-Summer: atmosphere Responds to subtropical SSTs Winds drive ocean Leads to ENSO

31. Seasonal Footprinting Mechanism

32. Subduction and the Subtropical Cell Subtropical Cell Ekman McPhaden and Zhang 2002 Nature

33. Change in Subduction Rate Transport at 9ºN & 9ºSConvergence & SST

34. Subduction Colored contours -0.3C anomaly isotherms for 3 different pentads Black lines – mean isopycnal surfaces (lines of constant density) Central North Pacific Averaged over 170ºW-145ºW

35. Do subducting anomalies reach the equator and influence ENSO? Year Latitude a)b)c)d)

36. Additional Information Processes that influence SSTs PDO verses ENSO Reemergence as a function of time Ocean Dynamics: –Rossby waves, –Ocean Rossby waves –Latif & Barnett Hypothesis for decadal variability –Subduction

37. SST Tendency Equation e.g. Frankignoul (1985, Reviews of Geophysics) Variables T m – mixed layer temp (SST) T b – temp just beneath ML Q net – net surface heat flux Q swh – penetrating shortwave radiation h – mixed layer depth w – mean vertical velocity w e – entrainment velocity v - velocity (current in ML) v ek – Ekman + v g - geostrophic A –horizontal eddy viscosity coefficient

38. Process that Influence SST V ek important on all time scales V g associated with eddies (~50km) & large-scale Rossby waves

39. Model Experiments to Test Bridge Hypothesis Specified SSTs

40. Influence of Air-sea Feedback on the atmospheric response to ENSO

41. Atmospheric Response to ENSO over the North Pacific El Niño – La Niña 30-day Running Mean Composite 500 mb height anomaly (176ºE-142ºW; 32ºN-48ºN) Aleutian Low

42. Basin-wide Reemergence Alexander et al. 2001, Progress in Oceanography

43. Evolution of the leading pattern of SST variability as indicated by extended EOF analyses Alexander et al. 2001, Prog. Ocean. No ENSO; Reemergence ENSO; No Reemergence

44. Upper Ocean: Temperature and mixed layer depth El Niño – La Niña model composite: Central North Pacific Alexander et al. 2002, J. Climate

45. Forecast Skill: Correlation with Obs SST Wave Model & Reemergence Wave ModelReemergence years Schneider and Miller 2001 (J. Climate)

46. PDO: The Latif and Barnett Hypothesis Coupled atmosphere-ocean interaction in the extratropics causes variability with a period of ~20 years Key processes: Atmosphere strongly responds to SST anomalies near Japan. Atmospheric circulation maintains SST through surface heat fluxes but drive changes in the ocean surface currents which reverse the SSTs ~5-10 years later. Time scale determined by oceanic Rossby waves.

47. Mechanisms for North Pacific Decadal Variability Air-sea interaction within the North Pacific basin –stochastic forcing (null hypothesis, simple slab) –Ocean dynamics (Latif and Barnett 1994, 1996) Time scale set by changes in ocean currents (oceanic Rossby waves). Relies on strong atmospheric response to midlatitude SST anomalies. Tropical-extratropical interactions –Subduction: ocean transport from N. Pacific to tropics; atmospheric teleconnections from Tropics to midlatitudes close the loop (Gu and Philander. Observations indicate this pathway is unlikely (Schneider et al., 1999). –Air-sea interaction within the Tropical Indo-Pacific basin, with atmospheric teleconnections to the North Pacific as a by-product Tropical Ocean has ENSO + Reemergence => PDO (Null hypothesis II) Tropical ocean has a mechanism for decadal variability

48. SLP & SST Patterns of Pacific Variability What process are involved? ENSOPDO Regressions: SLP – Contour; SST Shaded Mantua et al. 1997, BAMS

49. Schematic of the Latif and Barnett Hypothesis Warm SSTs Positive air - sea feedback H wind ~5yrs to cross Weakens warm Kuroshio Current

50. Impact of Ocean Currents on the Atmosphere 15 Wm -2 Prescribed ocean heat flux convergence in a slab ocean model coupled to a AGCM Mimics ocean heat transport anomalies in Kuroshio region eq 30N 60N SLP (mb x 100) 500 mb (m) From Yulaeva et al., 2001, J Climate

51. PDO Null hypothesis II: ENSO + Reemergence + Noise? Newman et al, 2003, J. Climate Obs PDO ENSO Model PDO, Ensemble Ave Model PDO, 95% confidence interval Model PDO, Ave of 20% closest to PDO “Model”: PDO n+1 =  PDO n +  *ENSO n+1 +   and  are constants estimated from data, then ran model 1000 times

52. “Forecast” of Annual Mean Anomalies PDO vs. observed PDO Correlation = 0.74  =0.58;  =0.58 Newman et al. 2003, J. Climate

53. Skill of Seasonal Statistical PDO predictions by verification season during 1971-2000 PDO (1st EOF of N. Pacific SST)Nino 3.4 Correlation between prediction and observed time series.

54. PDO & ENSO combined influence on SLP signal? a) El Niñob) La Niña e) El Niño Low PDO c) El Niño High PDOd) La Niña High PDO f) La Niña Low PDO -8.5 -4.5 -1.5 1.5 3.5 Gershunov and Barnett (1998, J. Climate)

55. Testing the PDO’s influence on the ENSO SLP signal High-Low PDO, El NiñoHigh-Low PDO, La Niña Pierce (2002, J. Climate) Obs 300 yr Coupled GCM Fixed SSTs

56. 1900:24 1925:46 minus 1947:76 1977:97 1947:76 1925:46 minus Wet Dry Winter Epoch Differences: High – Low SLP North Pacific Land Precipitation Deser et al. (In preparation)

57. Land PrecipitationMarine Cloudiness DryWetDryWet Deser et al. (In preparation) 180° 00-24 minus 25-46 47-76 minus 77-97 0°0° 30° N 30° S 0°0° 30° N 30° S 47-76 minus 25-46 0°0° 30° N 30° S Winter Epoch Difference: High-Low SLP North Pacific