1. Pacific vs. Indian Ocean warming: How does it matter for global and regional climate change? Joseph J. Barsugli Sang-Ik Shin Prashant D. Sardeshmukh NOAA-CIRES Climate Diagnostics Center Boulder, Colorado NOAA Photo Library

2. Global Mean Surface Air Temperature DJF Global Mean Precipitation DJF A: Opposing Temperature and Precipitation Sensitivity to Tropical SSTs across 110E Q: How does it matter for global (DJF) climate change?

3. Q: How does it matter for regional (NH Wintertime) climate change? A: Opposing PNA and NAO Sensitivity to Tropical SSTs across 110-120E, with PNA emphasizing the central and eastern Pacific more.

4. Method and Context (How did we get these plots and why do we believe them?) Understanding Opposing T, p sensitivity Seasonal cycle in T, p sensitivity PNA and NAO sensitivity with application to 50 year trend.

5. SST Patch Experiments with NCAR CCM3.10 43 SST anomaly patches total. 2K maximum anomaly Indo-Pacific 32 ensemble members (16 Warm, 16 Cold) 18 month runs (2 winters, 1 summer) Atlantic 40 ensemble members (20 warm, 20 Cold) 25 month runs Climatology 100 year fixed climo-SST run 1 K 0.5K

6. NCAR CCM3.10 w/CCM3.6 physics T42, 18 level resolution Default parameter values for current climate Smoothed Topography (as in CAM2) CCM3 vs. NCEP MRF9 Larger patch area in Indo-Pacific. 2K vs. 1.5K peak SST anomaly. Seasonal cycle vs. perpetual January All Tropical oceans vs. Indo-pacific only. Comparison of the present study to Barsugli and Sardeshmukh, 2002 Atmosphere GCM

7. Think of this as an “empirical linearization” about a given climate. For a grid of T, or for a set of patches this becomes: Note the Area Factor. This means that the grid-independent Green Function (and sensitivity) has units of Indo-Pacific Patches ~ 12 SSTU; Atlantic Patches ~ 7.5 SSTU Green Function approximation

8. Barsugli and Sardeshmukh, 2002

9. Simmons, Wallace, and Branstator, 1983 Barotropic vorticity forcing “nodal line” for Pacific target? This is similar to patterns in Branstator et al, 1985 from explicit Green function approach. Hmmm, what about the forcing of North Atlantic…. Newman and Sardeshmukh, 1998. Strong seasonal dependence of sensitivity.

10. Ting and Sardeshmukh, 1993 Linear Baroclinic Model. Deep heating. Remote response switches sign across 120E. Little remote response near “nodal line” at 120E. Local (rotational) response moves with forcing Heating is used as forcing, not SST. Nodal line not found when GFDL model basic state is used.

11. Hoerling et al. (2004). Indian ocean SST’s force 50 year trend in North Atlantic “NAO”-like pattern. Found in 3 models. Branstator(2004) Circumglobal Waveguide Pattern responds more to forcing at the date line than to forcing at 150 W. The latter forcing results in a more isolated PNA pattern.

12. Temperature and Precipitation Sensitivity Global Mean Precipitation DJF

13. Global Mean Surface Air Temperature DJF Regions for Composites

14. Composite Surface Air Temperature Indian Ocean West Pacific Ocean

15. Composite Precipitation Indian Ocean West Pacific Ocean

16. Indian Ocean Patch Composite Surface Latent Heat Flux U-Wind Stress V-Wind Stress 500 hPa Omega

17. W. Pacific Ocean Patch Composite Surface Latent Heat Flux U-Wind Stress V-Wind Stress 500 hPa Omega

18. Precipitation Sensitivity – Seasonal Cycle ANNUAL MAM DJF JJA SON

19. Surface Temperature

20. 850 hPa Temperature

21. Annual Mean Temperature at different levels

22. NAO, PNA and Trends

23. NAO and PNA sensitivity PNA MRF9 PNA - NAO

24. PNA in detail

25. 1950-1999 Trend in 500 hPa Z – NCEP Reanalysis Pacific Sector Atlantic Sector

26. Z500 trend from CCM3 TOGA and GOGAFixed SST Trend Pattern

27. PAC ATL TOTAL TREND Projection of Z500 trend onto each patch experiment

28. Pattern Correlation

29. Conclusions … There is opposing sensitivity to SST anomalies across longitude ~110E for global mean temperature and precipitation. E.g. warm SST anomalies in most of the Tropical Indian Ocean lead to a global mean cooling of the surface ( mainly land), cooling at 850 mb, and a reduction in global mean precipitation. The opposing temperature sensitivity is confined to the DJF season and is largest in the northern continents. The opposing sensitivity for precipitation is evident all year, and there is an additional area of negative sensitivity in the Eastern Pacific, south of the Equator. There is opposing sensitivity to SST anomalies across the same “nodal line” for the NAO and PNA pattern. Compared to the NAO, the PNA shows more sensitivity to SST’s at and east of the dateline. Therefore, the relative warming of the Indian and West Pacific warm pools will have a large impact on both global and (Northern Hemisphere) regional response to Tropical SST changes in DJF. Prediction (or past and paleo- reconstruction) of this broad spatial pattern of SST change is essential to get the global and regional picture correct.

30. … Conclusions Because the “nodal line” was seen in BS2002 and earlier, more idealized dynamical studies, we believe it to be a robust structure in the atmosphere of dynamical origin. The temperature sensitivity follows from the circulation anomalies. However, the origin of the coincident nodal line in Tropical precipitation remains uncertain. The Tropical Atlantic SST’s are generally more influential in JJA …for the global mean quantities. The full picture of Tropical-Extratropical interaction is a) more complicated than just ENSO, but not that much more complicated: 2-3 regions do pretty well to capture the changes that have a big global impact. Prashant will elaborate on the big picture at tomorrow’s talk.