The 2024 Asian–Australian monsoon (AAM) year, defined as April 2024 to March 2025, was notable. Based on available data, a prolonged rainy season was observed in most parts of the AAM region, except for the Meiyu Region, which corresponds to the area affected by the second stage of the East Asian summer monsoon. The rainy season also featured elevated near-surface air temperatures, a boreal summer rainfall surplus of approximately 20% across South, East, and Mainland Southeast Asia, an austral summer rainfall deficit of approximately 30% in Northern Australia, and a surplus of approximately 30% in the Maritime Continent. During boreal winter, a strong East Asian winter monsoon circulation led to below-average precipitation along East Asia’s climatological rain belt, including South China and Japan, accompanied by above-average near-surface air temperatures. Meanwhile, the 2024 AAM exhibited notable subseasonal variability, with abrupt alternations between dry/drought and wet/flood conditions, as well as between warm and cold episodes over many regions. It was also characterized by widespread extreme events, including but not limited to heavy rainfall, heatwaves, cold surges, and tropical cyclones. Such AAM-associated variability and extremes exerted considerable social impacts and caused substantial economic losses, highlighting the ongoing challenges in understanding and predicting the AAM at regional scales and multiple timescales.

This study revisits the influence of the quasi-biennial oscillation (QBO) on the Northern Hemisphere surface climate during the boreal winter by using the QBO index based on the empirical orthogonal function (EOF) of stratospheric equatorial winds. When the QBO is defined with eight phases, the tropospheric anomalies significantly project onto the negative Arctic Oscillation (AO) in phase 1 and onto the positive AO in phases 5 and 6. The underlying mechanism can be partially explained by the Holton–Tan relationship and the associated planetary wave–mean flow interactions. Compared with the known QBO indices defined with the single-level winds, the EOF-based index better captures the AO-like response to the QBO. This may be because the vertical structure, particularly the depth of the QBO’s stratospheric easterly or westerly, is essential for the QBO’s extratropical influence, which is better described by the EOF-based metric. The results remain robust in phases 1 and 5 and become more significant in phase 6 when the El Niño–Southern Oscillation (ENSO) effects are linearly removed. This result suggests that the two-dimensional QBO index is more useful than the one-dimensional index for monitoring and predicting QBO-related tropospheric circulation changes.

Despite significant advances in subseasonal-to-decadal prediction, predicting the East Asian surface climate one season ahead remains a formidable challenge. This study proposes a hybrid dynamical–statistical model to improve East Asia’s springtime surface air temperature (SAT) prediction by incorporating the Quasi-Biennial Oscillation (QBO) forecasted by decadal climate prediction systems. The QBO, a dominant interannual variability in the tropical stratosphere, shows a significant negative correlation with the East Asian SAT in March. During the westerly QBO phase, the Asia–Pacific jet shifts equatorward and induces a large-scale cyclonic circulation anomaly over the North Pacific. This leads to a cold SAT anomaly in East Asia, especially in western and central China. The decadal climate prediction systems reliably predict the QBO up to 18 months in advance but have poor prediction skills for the East Asian SAT, even at a few months’ lead time. The hybrid dynamical–statistical model, which combines the QBO forecast from decadal climate prediction models and the QBO–East Asian SAT relationship in the observations, significantly improves the East Asian SAT prediction at a 5-month lead time. This approach suggests that improving the multi-year QBO prediction may enable the East Asian SAT prediction even one year in advance.