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Modelling Climate Change – Southern Livestock Adaptation 2030

Modelling Climate Change

Projecting into the future is always difficult and trying to assess the likely impact of global warming can be particularly so. There is no way of making direct measurements of the future so the only way we can assess what future climates might hold is to use the past as a guide and apply the knowledge of climate science.

There are numerous web sites that discuss potential future climate change relating to agriculture (see sites listed at right under Links & Resources):

So how are potential future climates determined? There are 3 key steps.

1. Global Circulation Models (GCM’s)

Scientists use (GCM’s) to understand changes happening in our atmosphere and seek to predict their likely impacts on regional weather patterns.  These models predict seasonal changes in temperature and rainfall as deviations from long-term averages.  There is reasonably strong agreement amongst these models about future temperature changes across Australia, with an expectation that minimum and maximum temperatures across much of southern Australia will rise by 0.6 – 1.0 0C by 2030.  The models aren’t so consistent about the impact of climate change on seasonal rainfall.  Four climate models were selected for this study to provide a range of likely outcomes.  The models were chosen carefully as they are the best performers for southern Australia.

Global Circulation Model (GCM)


In this Project

GFDL (Geophysical Fluid Dynamics Laboratory)


2030 Climate USA 1

ECHAM (European Centre for Medium-Range Weather Forecasts, Hamburg)


2030 Climate Germany

CCSM (Community Climate System Model)


2030 Climate USA 2

HadGEM (Hadley Centre Global Environment Model)


2030 Climate UK

See more information on GCM’s.

2. Turning projections into weather data?

Farm system modelling generally requires daily weather data as input to the model calculations. The weathermaker model from CSIRO uses the GCM regional monthly projections and the characteristics of historical weather data at a locality to produce projected daily weather sets.  Historical weather averages and distributions are in line with the regional climate projections for particular GCM’s.

See more information on Projecting local weather based on GCM’s.

3. Turning future weather into pasture and livestock production

Daily weather sets for a period in time (say 2030) are then applied to sophisticated livestock production model such as Grassgro and SGS. See more information on Modelling Climate Change in Grazing Systems.