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During March 2021, large regions of Eastern Australia experienced prolonged heavy rainfall and extensive flooding. The maximum daily mean column integrated water vapor transport (IVT) over Sydney during this event was within the top 0.3% of all days since 1980, and the 10-day mean IVT was in the top 0.2%. In this study, we have examined the change in frequency of extreme IVT events over Sydney in 16 climate models from the Coupled Model Intercomparison Project 6 under two Shared Socioeconomic Pathways (SSP245 and SSP585). Generalized Extreme Value modeling was used to further analyze the change in frequency of extreme IVT events. We found the probability of long duration high IVT events is projected to increase by 80% at the end of the century, but the future change in IVT is correlated to the rate of global and regional warming in each model.

Extended warning of above‐average and extreme precipitation is valuable to a wide range of stakeholders. However, the sporadic nature of precipitation makes it difficult to forecast skilfully beyond one week. Subseasonal forecasting is a growing area of science that aims to predict average weather conditions multiple weeks in advance using dynamical models. Building on recent work in this area, we test the hypothesis that using large‐scale horizontal moisture transport as a predictor for precipitation may increase the forecast skill of the above‐median and high‐precipitation weeks on subseasonal time‐scales. We analysed retrospective forecast (hindcast) sets from the Australian Bureau of Meteorology's latest operational subseasonal‐to‐seasonal forecasting model, ACCESS‐S2, to compare the forecast skill of precipitation using integrated water vapour transport (IVT) as a proxy, compared to using precipitation forecasts directly. We show that ACCESS‐S2 precipitation generally produces more skilful forecasts, except over some regions where IVT could be a useful additional diagnostic for warning of heavy precipitation events. [ABSTRACT FROM AUTHOR]