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Interactions between the Madden- Julian Oscillation and the North Atlantic Oscillation Hai Lin, Gilbert Brunet Meteorological Research Division, Environment.

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Presentation on theme: "Interactions between the Madden- Julian Oscillation and the North Atlantic Oscillation Hai Lin, Gilbert Brunet Meteorological Research Division, Environment."— Presentation transcript:

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 (J. Climate) Intraseasonal variability in a dry GCM Lin et al (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: 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: Extended winter, November to April (36 pentads)

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

7 Pentads in MJO phases Extended winter from 1979 to 2004 Phase Number of pentads Mean amplitude

8 Lagged composites of the NAO index Phase Lag Lag Lag Lag Lag 1 Lag Lag Lag Lag Lag Lag

9 Lagged composites of the NAO index Phase Lag Lag Lag Lag Lag 1 Lag Lag Lag Lag Lag Lag

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

23


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