Regional seasonal forecasting requires accurate simulation of the variability of local climate drivers. The South Pacific Convergence Zone (SPCZ) is a large region of low-level convergence, clouds and precipitation in the South Pacific, whose effects extend as far as northeast Australia (NEA). The location of the SPCZ is modulated by the El Niño-Southern Oscillation (ENSO) which causes rainfall variability in the region. Correctly simulating the ENSO-SPCZ teleconnection and its interplay with local conditions is essential for improving seasonal rainfall forecasts. Here we analyse the ability of the ACCESS-S1 seasonal forecast system to predict the SPCZ’s relationship with ENSO including its latitudinal shifts, zonal slope and rainfall magnitude between 1990 and 2012 for the December–January–February (DJF) season. We found improvements in ACCESS-S1’s SPCZ prediction capability compared to its predecessor (POAMA), although prediction of the slope is still limited. The inability of ACCESS-S1 to replicate seasons with a strong anti-zonal SPCZ slope is attributed to its atmospheric model. This has implications for accurate seasonal rainfall forecasts for NEA and South Pacific Islands. Future challenges in seasonal prediction facing regional communities and developers of coupled ocean–atmosphere forecast models are discussed.

区域季节预报需要精确模拟当地气候驱动因素的变化。南太平洋汇聚区（SPCZ）是南太平洋低水平汇聚，云层和降水的大区域，其影响范围一直延伸到澳大利亚东北部（NEA）。SPCZ的位置受厄尔尼诺-南方涛动（ENSO）的影响，这会引起该地区降雨的变化。正确模拟ENSO-SPCZ远程连接及其与当地条件的相互作用对于改善季节性降雨预报至关重要。在这里，我们分析了ACCESS-S1季节预报系统预测SPCZ与ENSO的关系的能力，包括其1990年至2012年12月至1月至2月（DJF）季节的纬度变化，纬度斜率和降雨量。我们发现与前身（POAMA）相比，ACCESS-S1的SPCZ预测能力有所提高，尽管对斜率的预测仍然有限。ACCESS-S1无法复制具有强烈反区域SPCZ斜率的季节，这归因于其大气模型。这对NEA和南太平洋群岛的准确季节性降雨预报有影响。讨论了区域社区和海洋-大气耦合预测模型的开发者面临的季节性预测的未来挑战。