• Energy Research

Abstract When a record hot month occurs, timely and credible attribution and contextualisation information can enhance public understanding and future preparedness. This is particularly effective if provided in real time by a National Meteorological and Hydrological Service (NMHS). Many NMHSs are working to integrate research-based attribution methods into their operational services. In this study, researchers and climate service staff collaborated to assess the feasibility of delivering such information swiftly and aligned with standard NMHS data and procedures. The record warm July (winter) temperatures of Tasmania, Australia in 2023 were chosen to illustrate the trial. Rapid results were available three days after the event. Approximately half of the unusual warmth was attributed to climate change, with the likelihood of breaking the previous record at least 17 times higher in the current climate compared to a stationary pre-industrial climate (14% vs. 0.4%). The warming trend became evident in the 1980s, and by 2060, average July temperatures in Tasmania match the record temperature of July 2023 under a high emissions scenario. However, average July minimum temperatures were not well modelled, necessitating the addition of a higher-resolution forecast-based attribution method. In subsequent analysis, almost all the forecast temperature anomaly, and reduced storm activity, was attributable to climate change. Statistical analysis revealed that a weak El Niño partly offset the unusual warmth. To expedite these additional approaches, information drawn from real-time forecasts could be used. Lessons learnt from this trial include technical improvements to align better with NMHS protocols including using consistent datasets and baselines, and refining and automating the method suite. Logistical and communication enhancements included training staff to run the suite, improving communication materials, and developing delivery channels. These learnings provide key considerations for NMHSs as they move towards providing timely and credible climate attribution and contextualisation information as part of their operational services.

This study was driven by a need to inform how extreme precipitation might change in the future by considering guidance based on how it has already changed. Hourly precipitation data from eight high quality precipitation gauges from 1958 to 2014 in Victoria (Australia) were used. Variations in the magnitude and frequency of extreme precipitation events as well as their proportion of total precipitation were examined. On average, we found an 89% increase in hourly precipitation events exceeding 18 mm/h in the latter half of the study period as compared to the earlier half. The most extreme precipitation events increased in intensity by more than more moderate extremes, with larger increases during the warm season. The proportion of precipitation that could be attributed to extreme precipitation events during the warm season has increased in recent decades while annual precipitation totals have been declining.Extreme value modeling was performed to estimate how the 2, 10 and 100 year precipitation events have changed. A statistically significant increase could only be claimed for two sites for the 2 year return period precipitation event. However, the mean estimates of the 100 year return period precipitation events at five of the eight stations from 1987 to 2014 exceeded the 90% confidence intervals of the 100 year return period precipitation events from 1958 to 1985, while little change was observed at the other three sites. Our findings have implications for improved planning and resilience around intense rainfall and associated hazards such as flash flooding in Australia.