Convectively Coupled Tropical Waves and Their Influence on Rainfall in Tropical Australia: Observations and Predictability

Convectively coupled tropical waves (CCTWs) are modes of intra-seasonal variability that affect circulation and rainfall in the tropics. Here, we specifically examine their impact on Australian rainfall and circulation, as well as their representation in sub-seasonal-to-seasonal (S2S) models, and their predictability. Our findings reveal that CCTWs with off-equatorial convective centres, such as equatorial Rossby waves (ER), mixed Rossby-gravity waves (MRG), and tropical depression-type waves (TD-type), significantly increase the likelihood of extreme rainfall (above the 90th percentile) during austral summer. Specifically, ER waves enhance the probability by approximately 1.5 to 2.4 times, while MRG and TD-type waves increase it by 1.4 to 1.6 times relative to the seasonal average. These effects are comparable with the Madden-Julian Oscillation (MJO), which increases the probability of extreme rainfall by around 1.3 – 2.7 times compared to the seasonal probability. The increased likelihood of extreme rainfall is attributed to the increase in moisture convergence and advection driven by wave activity. These findings highlight the potential to improve S2S predictions by incorporating CCTWs, thereby increasing the accuracy of extreme event forecasts in tropical Australia.

                  The representation of CCTWs is then assessed in the operational Australian S2S model, ACCESS-S2, a coupled atmosphere-ocean model. We use a 38-year seasonal hindcast period to evaluate representation of CCTWs. We show that the predictability of ER waves and MJO in the filtered outgoing longwave radiation (OLR) field during austral summer extends out to around 9 and 16 days, respectively (r > 0.5). Meanwhile, other CCTWs have shorter skill forecast periods. Space-time spectral analysis also shows that the representation of CCTWs in the OLR field is underestimated. In particular, the relative OLR spectral power of ER waves, Kelvin waves, and the MJO are 20 – 30% less than observations. Moreover, the MRG waves are nearly non-existent in the model. More skill is identified using the filtered lower-level zonal wind (U850), both in terms of predictability and spectral amplitude. For example, considering the U850 only, predictability extends to around 11 days for ER waves and 18 days for the MJO, and the U850-spectra of ER waves mostly indicates less than 10% difference compared to observations, while Kelvin waves and the MJO show less than around 20% differences. However, the MRG is still non-existent in the U850 field. Further cross-spectral analysis demonstrates that there is a weak convection-circulation coupling bias in the model. Overall, this study highlights the role of CCTWs in driving extreme rainfall in tropical Australia through their coupling with convection and circulation. This also identifies current limitations and emphasizes the need to improve the representation of CCTW variability in S2S models to ultimately enhance extreme rainfall prediction in this region.