Southeastern Australian rainfall outlook
The chances of exceeding the median rainfall are between 40 and 60% over almost all of southeast Australia during the autumn period. This means there is not a strong tendency for either a wetter or drier autumn period for most of southeast Australia.
The El Niño-Southern Oscillation (ENSO) remains neutral, with the majority of atmospheric and oceanic indicators close to their long-term average. Dynamical models surveyed by the Bureau suggest ENSO-neutral conditions are likely to persist at least for the next three months.
Oceans surrounding Australia are generally expected to remain close to their 1981-2010 average. Atmospheric pressures may be below average over some southern areas.
The Indian Ocean Dipole is typically too weak to have a significant influence on the Australian climate during the months from December to April.
How accurate is the outlook?
Outlook accuracy for the autumn period is:
- Moderate over most of NSW and Victoria
- Low over western Tasmania and southern parts of SA
Bureau climatologists continually monitor the climate for any significant developments, with information on the likelihood of El Niño/La Niña and IOD events available fortnightly at the ENSO Wrap-Up. For a summary of Pacific and Indian Ocean outlooks, please see the Climate Model Summary.
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More rainfall outlook maps, tables and graphs
An expanded set of seasonal rainfall outlook maps and tables, including the probabilities of seasonal rainfall exceeding given totals (e.g. chance of receiving at least 200 mm), is available from Water and the Land.
Model accuracy (also known as model confidence or model skill) is a measure of how well a model has performed at that time of year in the past. One way that the Bureau measures the accuracy of its climate models is by comparing how often the outlook favoured a particular category (for example, when above median rainfall was more likely to occur than below median rainfall), and that favoured category was then subsequently observed. This measurement of accuracy is known as "Percent Consistent", and has been tested for the official seasonal outlook model over the period from 1981 to 2010.
The accuracy levels on the maps give an indication of how well the outlooks match the observed outcomes. High accuracy means that tests of the model on historical data show a strong relationship between the most likely outlook category (above or below median) and the subsequent observation (above or below median). In areas with high accuracy, historically the model has performed very well, and hence a high degree of confidence can be placed in future outlooks. On the other hand, low accuracy means the model has not performed well in these regions and therefore the outlook should be used with caution. In the places and seasons where the outlooks are most skilful, the category of the eventual outcome (above or below median) is consistent with the category favoured in the outlook about 75% of the time. In the least skilful areas, the outlooks perform no better than random chance (equivalent to the "flip of a coin").
A random forecast of above median rainfall will be correct about 50% of the time. For this reason, the green shading on the map shows areas where the model has greater than 50% accuracy only. In areas which are not coloured in green on the map, some caution should be taken when using the forecast, notably at times when there is not a strong climate influence (for example, no El Niño or La Niña is present).
The Rainfall outlook has highest accuracy during autumn and spring, while in summer and winter there is lower skill, particularly over central Australia.
As a guide, the Bureau uses the following terminology when referring to the accuracy of the outlooks:
|75% and above - very high|
|65 to 75% - high|
|55 to 65% moderate|
|50 to 55% - low|
|45 to 50% - low|
|Below 45% - very low|
What is normal for this period?
This map shows the median (or 50th percentile) rainfall for the given three months. The median rainfall is calculated from the 1981-2010 period.
The maps will differ from other median maps on the Bureau's website. This is because the dynamical model forecasts use an averaging period of 1981-2010. The quality of the dynamical model forecasts is in-part determined by the coverage and accuracy of the observations fed into it. Therefore, to be consistent from one year to the next, the Bureau has only run the model during the modern satellite era.
About the outlook
Using the outlook
The Bureau's rainfall seasonal climate outlooks are general statements about the likelihood of wetter or drier than average weather over a three-month period. The probabilities are generated from the Predictive Ocean Atmosphere Model for Australia (POAMA), the Bureau of Meteorology's dynamical climate model. It is important to note that they are not categorical predictions about future rainfall, and hence the success or failure of one individual outlook does not infer that the model has low skill. Skill is assessed over multiple runs of the model. Likewise, temperature outlooks give the likelihood or chance of exceeding the average maximum and minimum temperatures over the entire three-month outlook period. Information about whether individual weeks or months may be unusually hot or cold, is presently unavailable.
Probability outlooks should not be used as if they were categorical (yes/no) forecasts. These outlooks should be used as a tool in risk management and decision making. Greatest benefits accrue from long-term use, say over 10 years.
About the model
The seasonal climate outlooks are generated by the Predictive Climate Ocean Atmosphere Model for Australia (POAMA), a dynamical (physics based) climate model developed by the Bureau of Meteorology and CSIRO Marine and Atmospheric Research. This coupled atmosphere-ocean model is a state of the art seasonal forecast system. Read more about POAMA.
The POAMA model is undergoing continuous research and development. Advances in the science of seasonal prediction, improvements in the observations and how they are fed into the model, as well as increases in supercomputing power are just some of the ways the model's accuracy will increase over time.
El Niño and La Niña
Indian Ocean Dipole
Statistical model outlooks
The official dynamical outlooks supercede the statistical outlooks. Statistical outlook maps will continue to be available for a review period: