Understanding and predicting the strong Southern Annular Mode and its impact on the record wet east Australian spring 2010

Abstract

In 2010 eastern Australia experienced its wettest spring on record, which has been largely attributed to a strong La Niña event in conjunction with an extraordinary positive excursion of the Southern Annular Mode (SAM). La Niña impacts would be expected to have been predictable months in advance, but predictability of the occurrence of the strong SAM is less known. We explore the predictability of the strong SAM in austral spring 2010 and its contribution to the extreme wet conditions in eastern Australia, using the Australian Bureau of Meteorology’s dynamical seasonal forecast system (POAMA2). Seasonal forecasts from POAMA2 were skilful in predicting the wet conditions over eastern Australia at up to 2 month lead time as a result of a good prediction of the impacts of the ongoing La Niña and the development of a strong positive excursion of the SAM. Forecast sensitivity experiments on initial conditions demonstrate that (1) the strong La Niña was a necessary condition for promoting the positive phase of SAM (high SAM) and the anomalous wet conditions over eastern Australia during October to November 2010; but (2) internal atmospheric processes were important for producing the moderate strength of the high SAM in September 2010 and for amplifying the strength of the high SAM forced by La Niña in October to November 2010; and (3) the strong high SAM was an important factor for the extremity of the Australian rainfall in late spring 2010. Therefore, high quality atmosphere and ocean initial conditions were both essential for the successful prediction of the extreme climate during austral spring 2010.

Appendix

Anomalous behaviour of tropical eastern Pacific SSTs and the SAM in 2010 (See Fig. 11).

Fig. 11

Observed monthly evolution of the SAM and the Niño3.4 SST in 2010. The standardized anomalies of the SAMI and the Niño3.4 index were computed by using the monthly climatology and standard deviation computed over the period of 1980–2009

1.1 Zonal-mean zonal momentum balance

In order to gain insight into the dynamical forcing of the SH atmospheric circulations by ENSO and the SAM, we examine the regression of each term of the zonal-mean zonal momentum budget onto the inverted Niño3.4 index and the SAM index (Fig. 12). Following Seager et al. (2003), the zonal mean zonal momentum equation can be written as:

Fig. 12

Terms on the rhs of the zonal-mean momentum budget regressed onto a SAMI and b inverted Niño3.4 index for Oct–Nov mean. Terms have been vertically integrated (200–300 hPa). In the legend labels, horizontal and vertical are abbreviated as h_ and v_, and transient and stationary eddy momentum flux convergence are abbreviated as TEMFC and SEMFC, respectively. MMC represents mean meridional circulation. The sum of all terms on the rhs of the equation except for $f\left[ {\bar{v}} \right]$ is shown as the thick black dotted line. All lines except for the line representing all terms are displayed only if the regression coefficients are statistically significant at the 50 % confidence level for improved visual presentation

$$\frac{{\partial [\bar{u}]}}{\partial t} = f[\bar{v}] - [\bar{v}]\frac{{\partial [\bar{u}]}}{R\partial \varphi } - [\bar{\omega }]\frac{{\partial [\bar{u}]}}{\partial p} - \frac{1}{{Rcos^{2} \varphi }} \frac{\partial }{\partial \varphi }\left( {\left[ {\overline{{u^{*} v^{*} }} } \right]cos^{2} \varphi } \right) - \frac{\partial }{\partial p}[\overline{{u^{*} \omega^{*} ]}} - \frac{1}{{Rcos^{2} \varphi }} \frac{\partial }{\partial \varphi }([\overline{{u^{{\prime }} v^{{\prime }} ]}} cos^{2} \varphi ) - \frac{\partial }{\partial p}[\overline{{u^{{\prime }} \omega^{{\prime }} ]}} + D$$

Here, square brackets indicate a zonal mean, overbars indicate a time mean, asterisks indicate departures from zonal means, primes indicate departures from time means (monthly means in this study). f is the Coriolis parameter, R is the radius of the earth, φ is latitude, p is pressure; u, v, are zonal, meridional winds, respectively, and ω is vertical velocity. On the right hand side of the equation, the first term represents the Coriolis torque; the second and third terms represent the zonal-mean time mean winds advected by the mean meridional circulation; the fourth and fifth terms represent the forcing by horizontal and vertical convergence of momentum flux by stationary eddies, respectively; the sixth and seventh terms represent the forcing by horizontal and vertical convergence of momentum flux by transient eddies, respectively; and D represents damping.

Assuming a steady state (i.e. $\frac{{\partial [\overline{u]} }}{\partial t} = 0)$, Fig. 12 displays that the Coriolis torque is well balanced by the forcing by the mean meridional circulation in the tropics and by the eddy driven circulation in the SH extratropics during both SAM and ENSO. Furthermore, Fig. 12b shows that during La Niña, there is a substantial easterly forcing by both horizontal and vertical convergence of stationary eddy momentum flux on the mean westerlies over 15–25°S (i.e. the equatorward side of the subtropical jet; statistically significant at the 90 % confidence level). On the other hand, strong forcing is exerted to the mean flow by horizontal convergence of transient eddy momentum flux in the mid-high latitudes, but the contribution by the vertical counterpart is found to be minor. Therefore, in Sect. 4 we analyse only horizontal momentum flux convergence by transient eddies but analyse both horizontal and vertical momentum flux convergence by stationary eddies for the regression analyses associated with SAM and ENSO and for 2010.