1. Interactions between the Madden- Julian Oscillation and the North Atlantic Oscillation Hai Lin, Gilbert Brunet Meteorological Research Division, Environment Canada Jacques Derome McGill University TTISS, Monterey, September 14, 2009

2. Outlines Observed MJO – NAO connection Lin et al. 2009 (J. Climate) Intraseasonal variability in a dry GCM Lin et al. 2007 (J. Atmos. Sci.)

3. NAO and MJO connection NAO: dominant large scale pattern in the extratropics with significant influence on weather from eastern North America to Europe MJO: dominant tropical intraseasonal mode, coupled with convections and variability in diabatic heating One-way impact, or two-way interaction? A possible mechanism for both the NAO and MJO

4. Data and methodology Definition of the NAO: 2 nd REOF of monthly Z500 NAO index: projection of pentad Z500 anomaly onto this pattern Period: 1979-2003 Extended winter, November to April (36 pentads each winter)

5. Data and methodology Definition of the MJO: combined EOF of OLR, u200 and u850 in the band of 15°S – 15°N (Wheeler and Hendon, 2004) NAO index: RMM1 and RMM2 Period: 1979-2003 Extended winter, November to April (36 pentads)

6. Composites of tropical Precipitation rate. Winter half year November-April Xie and Arkin pentad data, 1979-2003

7. Pentads in MJO phases Extended winter from 1979 to 2004 Phase 12345678 Number of pentads 557978 63718766 Mean amplitude 1.671.661.811.781.661.701.621.75

8. Lagged composites of the NAO index Phase12345678 Lag 5 0.390.28 Lag 4 0.260.28 Lag 3 0.29 Lag 2 0.26 Lag 1 Lag 0 0.41 Lag +1 0.260.270.260.250.35 Lag +2 0.340.360.310.330.29 Lag +3 0.35 0.41 Lag +4 0.350.31 Lag +5 0.27

9. Lagged composites of the NAO index Phase12345678 Lag 5 0.390.28 Lag 4 0.260.28 Lag 3 0.29 Lag 2 0.26 Lag 1 Lag 0 0.41 Lag +1 0.260.270.260.250.35 Lag +2 0.340.360.310.330.29 Lag +3 0.35 0.41 Lag +4 0.350.31 Lag +5 0.27

10. Lagged probability of the NAO index Positive: upper tercile; Negative: low tercile Phase12345678 Lag 5 35%40%+49% Lag 4 +52%+46% Lag 3 40%+46% Lag 2 +50% Lag 1 Lag 0 +45%42% Lag +1 +47%+45%46% Lag +2 +47%+50%+42%41% 42% Lag +3 +48%41%48% Lag +4 39%48% Lag +5 41%

11. Tropical influence

12. Wave activity flux and 200mb streamfunction anomaly

13. Lagged regression of 200mb U to NAO index Extratropical influence

14. Lagged regression of 200mb U to NAO index Extratropical influence U200 composites

15. Tropical intraseasonal variability (TIV) in a dry GCM

16. Model and experiment Primitive equation AGCM (Hall 2000). T31, 10 levels Time-independent forcing to maintain the winter climate (1969/70-98/99) all variabilities come from internal dynamics No moisture equation, no interactive convection 3660 days of integration

17. Unfiltered data 20-100 day band-pass Zonal propagation 10S-10N Model Result Stronger in eastern Hemisphere

18. TIV in the dry model Kelvin wave structure Phase speed: ~15 m/s (slower than free Kelvin wave, similar to convective coupled Kelvin wave, but there is no convection)

19. What causes the TIV in the dry model? 3-D mean flow instability (Frederiksen and Frederiksen 1997) Tropical-extratropical interactions (all wave energy generated in the extratropics) Moisture and convection related mechanisms are excluded Possible mechanisms

20. ISO in a dry model Linked to tropical eastward propagation in the eastern Hemisphere Global propagation of low-frequency wave activity 250 hPa PV and wave activity flux

21. Summary Two-way interaction between the MJO and the NAO Increase of NAO amplitude 5~15 days after the MJO-related convection anomaly reaches western Pacific Certain MJO phases are preceded by strong NAOs TIV generated in a dry GCM Tropical-extratropical interactions are likely responsible for the model TIV

22. Implication to the MJO A possible mechanism for the MJO: triggering, initialization Contribution of moisture and tropical convection: spatial structure, phase speed