This project used high-resolution modelling, together with a range of meteorological data, to better understand and predict important meteorological natural hazards, including fire weather, tropical cyclones, severe thunderstorms and heavy rainfall. The outcomes from the project are contributing to reducing the impact and cost of these hazards on people, infrastructure, the economy and the environment.

Specific case studies undertaken included the New South Wales Blue Mountains bushfires of 2013; ember transport by fire plumes; pyrocumulus cloud simulation and prediction, and the NSW April 2015 East Coast Low.

Ember transport

The study developed an understanding of how fire embers generated during bushfires can be lifted into the atmosphere and carried by winds ahead of a fire front, potentially starting new fires downwind. The team undertook simulations for ember transport for a wide range of wind speeds and ember fall speeds. It is important to consider a range of fall speeds, since different types of embers have different densities and aerodynamic properties which affect how far they are carried.

Pyrocumulonimbus

Plume modelling has also been utilised to study pyrocumulonimbus clouds (PyroCb). Intense fire plumes in suitably moist environments can lead to PyroCb development, with the possibility of strong downbursts which can exacerbate already extreme fire conditions. A survey of current understanding and forecast techniques was completed, and the team has worked towards developing improved techniques.

Blue Mountains bushfire

A detailed case study of the Blue Mountains fires of October 2013 was undertaken, focusing on 17 October when some 200 houses were destroyed. Analysis uncovered a weather phenomenon known as mountain waves which contributed to the severe fire behaviour. Mountain waves are atmospheric oscillations that occur due to air flowing over hills or mountains. They can arise in several different ways, some more predictable than others. Often they cause strong downslope winds on the lee slope of the hill or mountain.

April 2015 East Coast Low

Collectively, the ensemble weather simulations accurately predicted the position and intensity of the low, the strong winds and the rainfall. The differences between them give insight as to the forecast uncertainty, the overall envelope of areas at some risk, and the areas at highest risk. The ensemble also enables insight into the processes that lead to the rapid intensification of these systems. The team is continuing to learn from ensemble simulations about predictability of East Coast Lows and how to use this information to benefit both forecasters and the emergency services.

Specific outcomes of this project have:

• improved the scientific understanding of severe weather phenomena in Australia
• improved the knowledge of how to best predict these phenomena, including model configuration and interpretation
• contributed to the post-event analysis and lessons learned of selected severe events that occur during the course of the project
• informed the development of numerical weather prediction systems specifically for severe weather.