Through the Collaboration for Australian Weather and Climate Research (CAWCR), we're creating systems for predicting Australia's air quality, weather and climate.

The challenge

Accurate and timely weather and environmental information

Weather and environmental conditions impact nearly every aspect of our lives. We need information on these conditions to make decisions about our day-to-day activities and well-being. Governments and industry need the information to protect people and property, and to make operational decisions. For better planning and management we need accurate, timely information.

Our response

Prediction systems for air quality, weather and climate

We develop prediction systems for air quality, weather and climate, particularly for processes occurring from minutes to days to years, and from regional spatial scales down to local scales of tens of metres. These systems have a range of applications:

Storm clouds over the Gippsland Lakes, Victoria

  • supporting the Bureau of Meteorology's weather services and forecast high impact weather events such as cyclones, severe storms and environmental hazards such as bushfires and air pollutants (smoke, dust, odour and pathogens)
  • investigating the effects of future development and climate change scenarios on these events
  • producing operational weather forecasts and warnings
  • contributing to water resource management and nowcasting
  • forecasting wind, fog and volcanic ash for the aviation and renewable energy sectors.

Modelling tools

Much of our atmospheric modelling is underpinned by the Australian Community Climate and Earth-System Simulator (ACCESS). Our other tools include the Conformal-Cubic Atmospheric model (CCAM), The Air Pollution Model (TAPM), and the Chemical Transport Model (CTM).

The modelling systems developed by our researchers are used to:

  • make specialised predictions for tropical cyclones, ozone and UV index, and Antarctic weather
  • downscale climate projections to get a better understanding of future regional climate and weather (including extremes)
  • provide weather and wind forecasts for sporting events such as the Olympic Games and the America's Cup
  • predict the concentrations of chemical pollutants and particulates in urban airsheds
  • simulate wind and solar energy fields for renewable energy prediction
  • develop and test technologies for grid distribution and energy storage.

Ultimately the research leads to more accurate, informative, and timely weather and environmental information for users in government, industry, and the public.


By bringing together the skills of CSIRO and Bureau of Meteorology scientists, we can direct our resources to tackling Australia's most significant weather and environmental challenges:

  • Synoptic and mesoscale meteorology: understanding the nature of weather events and developing improved techniques for the prediction of high impact weather.
  • Weather forecasting (tools, practices, procedures and user requirements): building advanced tools to assist weather forecasters in providing timely and detailed weather and warning information for the Australian public.
  • Regional scale weather and climate modelling: simulating the detailed weather and climate in the Australian region, Antarctica, and other regions of interest.
  • Dynamic downscaling: translating coarse resolution global weather and climate predictions into fine-scale regional weather and climate fields using a nested modelling approach.
  • Ensemble-based forecasting: deriving probabilistic forecasts and uncertainty estimates based on the output of many model runs, to aid decision makers in the forecast office and weather-sensitive industries.
  • Tracer and chemical transport and dispersion modelling (integrated with observations): applying dispersion and chemical transport models to regional, urban, and local scale air quality issues.
  • Physical, chemical and mathematical sciences: integrating theoretical and empirical science to answer a variety of meteorological questions.
  • Model evaluation, interpretation, and uncertainty estimation: evaluating the accuracy and usefulness of model forecasts through quantitative comparisons with observations, to provide users with information on how to interpret the forecasts.
  • Data visualisation: developing software systems to visualise and interpret complex meteorological information from observations and forecasts in an intuitive and effective way.

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