The Australian monsoon delivers seasonal rain across a vast area of the continent stretching from the far northern tropics to the semi-arid regions. This article provides a review of advances in Australian monsoon rainfall (AUMR) research and a supporting analysis of AUMR variability, observed trends, and future projections. AUMR displays a high degree of interannual variability with a standard deviation of approximately 34% of the mean. AUMR variability is mostly driven by the El Niño-Southern Oscillation (ENSO), although sea surface temperature anomalies in the tropical Indian Ocean and north of Australia also play a role. Decadal AUMR variability is strongly linked to the Interdecadal Pacific Oscillation (IPO), partially through the IPO's impact on the strength and position of the Pacific Walker Circulation and the South Pacific Convergence Zone. AUMR exhibits a century-long positive trend, which is large (approximately 20 mm per decade) and statistically significant over northwest Australia. The cause of the observed trend is still debated. Future changes in AUMR over the next century remain uncertain due to low climate model agreement on the sign of change. Recommendations to improve the understanding of AUMR and confidence in AUMR projections are provided. This includes improving the representation of atmospheric convective processes in models, further explaining the mechanisms responsible for AUMR variability and change. Clarifying the mechanisms of AUMR variability and change would aid with creating more sustainable future agricultural systems by increasing the reliability of predictions and projections.

中文翻译：

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澳大利亚季风降雨的变异性和长期变化：综述

澳大利亚季风为从遥远的北部热带地区延伸到半干旱地区的大陆广大地区带来季节性降雨。本文回顾了澳大利亚季风降雨 (AUMR) 研究的进展，并对 AUMR 变异性、观察到的趋势和未来预测进行了支持性分析。AUMR 显示出高度的年际变化，标准偏差约为平均值的 34%。AUMR 变化主要由厄尔尼诺-南方涛动 (ENSO) 驱动，尽管热带印度洋和澳大利亚北部的海面温度异常也起到了一定作用。年代际 AUMR 变异性与年代际太平洋涛动 (IPO) 密切相关，部分通过 IPO' 对太平洋沃克环流和南太平洋辐合带的强度和位置的影响。AUMR 呈现出长达一个世纪的积极趋势，该趋势很大（每十年约 20 毫米）并且在澳大利亚西北部具有统计显着性。观察到的趋势的原因仍在争论中。由于气候模型对变化迹象的认同度较低，下个世纪 AUMR 的未来变化仍然不确定。提供了提高对 AUMR 的理解和对 AUMR 预测的信心的建议。这包括改进模型中大气对流过程的表示，进一步解释导致 AUMR 可变性和变化的机制。