Variability of the South Pacific Convergence Zone on intraseasonal and interannual timescales

1. Variability of the South Pacific Convergence Zone on intraseasonal and interannual timescales Presented by, Matthew Widlansky School of Earth and Atmospheric Sciences, Georgia Institute of Technology November 10, 2006

2. The South Pacific Convergence Zone (SPCZ): ITCZ SPCZ • Region of abundant precipitation which extends from New Guinea towards the SH Mid-latitudes. (Vincent 1994) • Named the SPCZ by Trenberth (1976) who noted that the zonal portion is forced by SST gradients. • The diagonal region is controlled by interactions with the higher latitude circulation. (Kiladis, et al. 1989)

3. SPCZ Seasonal Cycle: • Regions with OLR values less than 230 W m-2 (Vincent) are experiencing deep atmospheric convection. • Seasonal convection patterns are driven by the meridional shift of the West Pacific Warm Pool (Karoly et al. 1998). • SPCZ reaches strongest intensity during the austral summer months (DJF).

4. Mean State of the SPCZ • Surface Convergence 2) • Inertial Instability (Tomas and Webster 1997)

5. Motivation: Understand Variability • The SPCZ is characterized by significant variability (OLR standard deviation ~40 W m-2). • This can be the difference between floods and droughts or whether the region has severe tropical cyclones or a spectacular tourist season. Our focus today will be to look at changes on MJO (25-80 day) and ENSO (3-5 year) time periods. Photos from: “Breathtaking-Photos”, “Digital-Typhoon”, and the “BBC”

6. Wavelet Analysis • OLR time series from five locations along the SPCZ and three locations over the Central South Pacific which usually receive minimal precipitation. • Determine the timescales of variability and when they were most dominant. (Torrence and Compo, 1998) Zonal SPCZ +30˚E Mid-latitude Influences

7. Significant variability on MJO timescales. MJO variability repeats almost every year.

8. EOF Analysis • We will now use an Empirical Orthogonal Function Analysis to observe: • When MJO variability propagates from the Indian Ocean towards the SPCZ Region. • How MJO variability “pre-conditions” the SPCZ for enhanced convection.

9. EOF Analysis Timescales of variability for the two leading principal components is significant in the 40-60 day range. • PC 1 and 2 represent the same mode of variability with PC 1 “leading” by about 15 days (Matthews 2000). • PC 2 is used in the Composite Analysis because it measures variability closer to the SPCZ.

10. Composite Analysis • PC2 values >1.0 std from the mean are retained. • Only peak dates during DJF are used for this composite analysis. • 16 MJO events

11. Composite Analysis Daily OLR anomaly regressed onto PC2 Max Dates (DJF): Day 0 anomaly is similar to the second EOF spatial pattern:

12. MJO Composite Analysis Zonal Wind anomaly regressed onto PC2 Max Dates (DJF): Increased Convergence Increased Convection

13. Moving East MJO variability is only significant during the El Nino events of 1983, 1992, and 1998.

14. Conclusions: • The SPCZ is a pronounced region of abundant precipitation which can not be considered stationary in time or space. • Moderate cross-equatorial low level winds provide additional vorticity and enhance storms caused by moisture convergence at the surface. • Significant variability in SPCZ convection exists on MJO timescales which can be explained in part by the associated change in low level convergence. • The ENSO cycle has a strong influence on how far east the convective signal of the MJO propagates.

16. References: Folland, C., Renwick, J., Salinger, M., and Mullan, A., 2002: Relative influences of the Interdecadal Pacific Oscillation and ENSO on the South Pacific Convergence Zone. Geophysical Research Letters, 29(13), 21-1 to 21-4. Folland, C., Salinger, M., Jiang, N., Rayner, N., 2003: Trends and variations in South Pacific island and ocean surface temperatures. J. Clim., 16, 2859-2874. Griffiths, G., Salinger, M., and Leleu, I., 2003: Trends in extreme daily rainfall across the South Pacific and relationship to the South Pacific Convergence Zone. Int. J. Climatol., 23, 847-869. Grotjahn, R., 2004: Remote weather associated with South Pacific subtropical sea-level high properties. Int. J. Climatol., 24, 823- 839. Karoly, D. and Vincent, D., 1998: Meteorology of the Southern Hemisphere. Meteorological Monographs, 27(49), 101-117. Kiladis, G., Vonstorch, H., Vanloon, H., 1989: Origin of the South-Pacific Convergence Zone. J. Clim., 2(10), 1185-1195. Matthews, A., Hoskins, B., Slingo, J., et al., 1996: Development of convection along the SPCZ within a Madden-Julian oscillation. Quarterly J. Royal Meteorological Soc. 122(531): 669-688. Miyakoda, K., Navarra, A., and Ward, M., 1999: Tropical-wide teleconnection and oscillation. II: The ENSO-monsoon system. Quarterly J. Royal Meteorological Soc. 125(560): 2937-2963. Trenberth, K., 1986: An assessment of the impact of transient eddies on the zonal flow during a blocking episode using localized Eliassen-Palm flux diagnostics. J. Atmos. Sci., 43, 2070-2087. Vincent, D., 1985: Cyclone development in the South-Pacific Convergence Zone during FGGE, 10-17 January 1979. Quarterly J. Royal Meteorological Soc. 111(467), 155-172. Vincent, D., 1994: The South Pacific convergence zone (SPCZ): A review. Mon. Wea. Rev. 122, 1949-1970. Vitart, F., 2006: Seasonal forecasting of tropical storm frequency using a multi-model ensemble. Quarterly J. Royal Meteorological Soc. 132(615): 647-666. Yoshikane, T. and Kimura, F., 2003: Formation mechanism of the simulated SPCZ and Baiu front using a regional climate model. J. Atmos. Sci., 60, 2612-2632. Zhang, C. and Dong, M., 2004: Seasonality in the Madden-Julian Oscillation. J. Clim., 17, 3169-3180.

17. ENSO Composite Analysis El Nino Anomaly La Nina Anomaly

18. ENSO Composite Analysis El Nino Anomaly La Nina Anomaly

19. Mean State of the SPCZ