The Pacific Meridional Mode: Diagnostics and Impacts

1. Dan Vimont Department of Atmospheric and Oceanic Sciences Center for Climatic Research University of Wisconsin, Madison The Pacific Meridional Mode: Diagnostics and Impacts Climate Diagnostics and Prediction Workshop October 21, 2004 Madison, WI John Chiang Department of Geography & Berkeley Atmospheric Sciences Center University of California, Berkeley

2. The Pacific Meridional Mode • Analogies between the Atlantic and Pacific • Modeling the tropical response to mid-latitude forcing • The spatial structure of decadal ENSO-like variability • Conclusions Climate Diagnostics and Prediction Workshop

3. The Pacific Meridional Mode • Analogies between the Atlantic and Pacific • Modeling the tropical response to mid-latitude forcing • The spatial structure of decadal ENSO-like variability • Conclusions Climate Diagnostics and Prediction Workshop

4. The Atlantic Meridional Mode • Dominant statistical mode of tropical Atlantic interannual to decadal variability: • Meridional SST gradient • Cross-gradient boundary-layer flow towards warmer water • ITCZ shift towards warmer hemisphere Climate Diagnostics and Prediction Workshop

5. Cold tongue weighted toward east Tropical Mean States: SST Climate Diagnostics and Prediction Workshop

6. Tropical Mean States: Precip. Mean ITCZ along cold tongue’s northern edge Climate Diagnostics and Prediction Workshop

7. Tropical Seasonal Cycle Atlantic: Pacific: Climate Diagnostics and Prediction Workshop

8. Pacific Meridional Mode: Motivation • Each basin possesses similar mean states and seasonal cycle: cold tongue to the east, similar seasonal cycles of ITCZ and cold tongue (Mitchell and Wallace, 1992) • Model studies without a thermocline-SST feedback produce meridional variability as the dominant mode (e.g. Xie and Saito, 2001) • Similar evidence for mid-latitude forcing of tropical variability in each basin (Curtis and Hastenrath, 1995; Nobre and Shukla; 1996, Xie and Tanimoto; Czaja et al., 2002; Vimont et al., 2001, 2003a, b) Climate Diagnostics and Prediction Workshop

9. Data: NCEP reanalysis 10m winds and SST; CPC merged precipitation Defined over regions (in the Pacific and Atlantic) with similar mean states Best fit linear regression to CTI (ENSO) removed from data Method: Maximum Covariance Analysis (SVD analysis): defines patterns between two fields that are strongly coupled MCA applied to 10m winds and SST Data regressed onto SST expansion coefficient Observational Analysis Climate Diagnostics and Prediction Workshop

10. Analogous Meridional Modes Leading statistically coupled mode for SST and 10m winds Climate Diagnostics and Prediction Workshop

11. Analogous Meridional Modes Precipitation regressed on SST time series from leading MCA mode Climate Diagnostics and Prediction Workshop

12. Temporal evolution Variations occur on many time scales, including interannual and decadal Climate Diagnostics and Prediction Workshop

13. Temporal Evolution Wind time index has maximum variance during boreal winter (NDJF) Climate Diagnostics and Prediction Workshop

14. Temporal Evolution SST time series has maximum variance during boreal spring (MAM) Climate Diagnostics and Prediction Workshop

15. Temporal Evolution Lag correlation peaks when wind time series leads SST time series Climate Diagnostics and Prediction Workshop

16. Meridional Modes • A “meridional mode” of tropical ocean-atmosphere variability is identified in the Pacific. • The Pacific meridional mode resembles the Atlantic meridional mode in both spatial and temporal structure. • The strong similarity between the two basins suggests that the meridional modes arise from analogous processes Climate Diagnostics and Prediction Workshop

17. The Pacific Meridional Mode • Analogies between the Atlantic and Pacific • Modeling the tropical response to mid-latitude forcing • The spatial structure of decadal ENSO-like variability • Conclusions Climate Diagnostics and Prediction Workshop

18. Analogous Meridional Modes Trade wind relaxation Up-gradient flow Climate Diagnostics and Prediction Workshop

19. CCM3 Response to Meridional Mode SST • CCM forced by meridional mode SST: • Up-gradient flow reproduced • Relaxed subtropical trades not reproduced Climate Diagnostics and Prediction Workshop

20. Source of subtropical winds North Pacific Oscillation North Atlantic Oscillation Trades relax in response to NAO in the Atlantic, and NPO in the Pacific Climate Diagnostics and Prediction Workshop

21. Meridional Mode Evolution • Wintertime fluctuations in the strength of the subtropical trade winds affect the subtropical SST through surface heat fluxes • In the deep tropics, the atmosphere responds by producing surface winds that blow towards the warmer SST • Model simulation: we will force a coupled model with heat flux anomalies associated with the NPO during winter, then allow the model to freely evolve. Climate Diagnostics and Prediction Workshop

22. CCM3.10 Experiments • NPO heat flux imposed during winter months: NDJFM • Ensemble simulations allow investigation of coupled variability (forced by NPO) without prohibitively long model integrations Atmosphere Fluxes generated by ATM and SOM 50m Slab Ocean Climate Diagnostics and Prediction Workshop

23. Winter Summer NPO heat flux forces SST anomalies Coupled response alters and prolongs tropical SST anomaly CCM3.10 Coupled Response Climate Diagnostics and Prediction Workshop

24. Coupled response: WES feedback • SST anomaly amplifies slightly during winter (imposed forcing) • Latent heat flux continues to amplify SST anomaly during summer (after imposed forcing is shut off) • Coupled WES feedback enhances persistence and amplitude of SST anomalies Climate Diagnostics and Prediction Workshop

25. Model Results • The meridional mode can be excited by mid-latitude atmospheric variability • Wintertime variations in the trade wind strength associated with the NAO or NPO alter subtropical SSTs through changes in surface heat fluxes • The tropics respond to these SST anomalies during spring and summer • The coupled WES feedback increases the amplitude and persistence of the tropical response Climate Diagnostics and Prediction Workshop

26. The Pacific Meridional Mode • Analogies between the Atlantic and Pacific • Modeling the tropical response to mid-latitude forcing • The spatial structure of decadal ENSO-like variability • Conclusions Climate Diagnostics and Prediction Workshop

27. Interannual & Decadal EOFs Highpass-filtered and lowpass-filtered EOFs reproduce ENSO and ENSO-like variability (Zhang et al., 1997) Climate Diagnostics and Prediction Workshop

28. Reconstructed data • What happens if we reconstruct the lowpass-filtered data using ONLY the highpass-filtered spatial information? • Start by projecting the highpass-filtered EOFs (interannual spatial information) onto the unfiltered data: • Next, apply a lowpass filter to these reconstructed pseudo-PC’s, and reconstruct the data using a subset of these pseudo-PC’s combined with the highpass-filtered EOFs: Climate Diagnostics and Prediction Workshop

29. Reconstructed data • Result: XLPR contains decadal temporal information only, and interannual spatial information only. • Next, perform EOF/PC anlaysis on XLPR. If decadal processes are responsible for generating the meridionally broadened structure of ENSO-like decadal variability, then the EOFs of XLPR should not have an ENSO-like structure Climate Diagnostics and Prediction Workshop

30. EOFs of reconstructed SST EOF1 of the reconstructed SST reproduces the ENSO-like structure Climate Diagnostics and Prediction Workshop

31. HP EOF3: ENSO “leftovers” HP EOF4: ENSO precursor Components of EOFLPRContributions from the interannual EOFs HP EOF1: ENSO Three HP EOF’s contribute to EOFLPR. Each HP EOF has a known relationship to ENSO. Climate Diagnostics and Prediction Workshop

32. ENSO leads PPC3 by 1-12 months PPC4 leads ENSO by 1-12 months Components of EOFLPRTemporal Relationships with ENSO Lagged correlation between peak of ENSO (PPC1) and PPC3 or PPC4: Climate Diagnostics and Prediction Workshop

33. The Pacific Meridional Mode • Analogies between the Atlantic and Pacific • Modeling the tropical response to mid-latitude forcing • The spatial structure of decadal ENSO-like variability • Conclusions Climate Diagnostics and Prediction Workshop

34. Pacific Meridional Mode: Conclusions • A meridional mode of variability is identified in the Pacific • The Pacific meridional mode has very similar spatial and temporal characteristics as its Atlantic counterpart • The Pacific and Atlantic meridional modes evolve via coupled processes in the ITCZ - Cold Tongue region • Both the Pacific and Atlantic meridional modes can be excited by mid-latitude forcing in their respective Northern Basins (perhaps Southern?) • Model results indicate that positive coupled feedbacks enhance the meridional mode persistance and amplitude • The strong similarities between the Pacific and Atlantic meridional modes suggest that the modes are “real” Climate Diagnostics and Prediction Workshop

35. Pacific Meridional Mode: Conclusions • The Pacific meridional mode may be an important contributor to interannual ENSO and decadal ENSO-like variability • Meridional mode variability tends to precede ENSO by 2-4 seasons • The spatial structure of decadal ENSO-like variability is well reproduced as an average over ENSO precursors, the peak of an ENSO event, and ENSO “leftovers”. This suggests that decadal ENSO-like variability is realized through processes associated with the interannual ENSO cycle • Seasonality is very important • Our understanding of climate variability is enhanced by an understanding of the seasonal cycle Climate Diagnostics and Prediction Workshop