Observed and projected intra‐seasonal variability of Australian monsoon rainfall

Abstract

Indices derived from daily rainfall time series are used to measure “burst” features of the northern Australia monsoon, corresponding to one or more days of heavy rainfall. These indices include number of burst days, numbers and durations of burst events, and average intensity. The results using observational data show how these features can vary from one year to the next, and how they can vary from the station scale (Darwin) to the regional scale (northern Australia). The results from Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model simulations under both historical and future greenhouse gas conditions have also been analysed and indicate how well models can capture these features and how they might change by the end of the 21st century under a high emissions scenario. While most models provide a reasonable simulation of present‐day burst features, there is little consensus for a significant change to seasonal rainfall totals when looking at the full CMIP5 ensemble. A subset of models with detectable skills with respect to the Madden‐Julian Oscillation shows evidence for an increase in the seasonal total rainfall amount and most other monsoon metrics, except a slight decrease in the number of burst events. This is consistent with a basic thermodynamic response to warming and consistent with findings elsewhere. However, the Australian monsoon is strongly influenced by the large‐scale circulation and there remains some doubt about whether we can confidently diagnose all the changes to monsoon bursts that could occur given the limited ability of many of the current generation of models to simulate tropical cyclones, the Madden‐Julian Oscillation and other relevant features.

Intraseasonal variability of global land monsoon precipitation and its recent trend

“…In SH, the AU monsoon 20-70-day ISV is dominantly affected by the MJO convection over the Arafura Sea (Supplementary Fig. 7c), as demonstrated by previous works 28,28,87 . The MJO modulates other monsoon regions primarily by exciting Kelvin waves.…”

The drivers of extreme rainfall event timing in Australia

“…We use the daily Australian Water Availability Project (AWAP; Jones et al, 2009) data, also known as the Australian Gridded Climate Data (AGCD) version 1, at 0.25 × 0.25 resolution over the period 1911-2017. The AWAP dataset is widely used for studying rainfall in Australia (King et al, 2013a;Alexander and Arblaster, 2017;Dey et al, 2019;Moise et al, 2019); also, previous research shows that AWAP can replicate extreme rainfall characteristics when compared against station data (King et al, 2013b). However, due to scarce station density, areas of central Australia are often masked to avoid regions where there is low confidence in the dataset.…”

“…The dominant large‐scale drivers modulating rainfall in the north are ENSO, MJO, and ITCZ (Dey et al ., 2019). These drivers influence rainfall characteristics in the north, such as monsoonal bursts (Moise et al ., 2019), tropical cyclones (Lavender and Abbs, 2013), and local convection due to the diurnal cycle (Rauniyar and Walsh, 2011), causing the majority of the rain to fall in summer. The cooler months are usually dry in the north of Australia.…”

Intraseasonal variability of global land monsoon precipitation and recent change

“…In SH, the AU monsoon 20-70-day ISV is dominantly affected by the MJO convection over the Arafura Sea (Supplementary Fig. 7c), as demonstrated by 28,84 . The MJO modulates other monsoon regions primarily by exciting convectively coupled Kelvin waves.…”