Southeastern Australian temperature outlook
The chances that the August to October maximum temperature outlook will exceed the median maximum temperature are greater than 60% over most of NSW, Victoria, Tasmania, southeast SA. Chances are greater than 80% over southern Victoria and Tasmania. So for every ten August to October outlooks with similar odds to these, about six to eight of them would be warmer than average over these areas, while about two to four would be cooler.
Across the northern half of SA and the far northwest of NSW the chances of a warmer or cooler August to October are roughly equal.
The chances that the average minimum temperature for August to October 2014 will exceed the long-term median are greater than 60% over southeast Australia. Chances rise to greater than 80% over southern Victoria, Tasmania, and southeast NSW (see map).
Warming of the tropical Pacific Ocean over the past several months has primed the climate system for an El Niño in 2014. However, in the absence of the necessary atmospheric response, Pacific Ocean temperatures have either stabilised or some cooling has occurred. Despite some easing in the model outlooks, a majority of international climate models still indicate El Niño is likely to develop during spring 2014.
The Indian Ocean Dipole (IOD) index has been below −0.4°C (the negative IOD threshold) since mid-June. Model outlooks suggest the IOD is likely to return to neutral by spring. A negative IOD typically brings wetter winter and spring conditions to inland and southern Australia. It is possible that the effects of the Indian Ocean and Pacific are competing to some degree, and hence are cancelling each other out.
How accurate is the outlook?
Maximum temperature outlook accuracy for the August to October period is:
- Moderate to high over most of NSW, Victoria, Tasmania and central and eastern districts of SA
- Low to very low over western and northern parts of SA
- Moderate over western and northeast parts of South Australia and Tasmania
- Low to very low throughout most of NSW, Victoria, and northern and southeast SA
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 maximum temperature outlook accuracy is good for most of the year, with the lowest point during the winter seasons. Of the variables predicted (i.e. rainfall, and maximum and minimum temperature), maximum temperature performs best. The minimum temperature outlook accuracy peaks during summer, late autumn and late spring. Accuracy is lowest during late summer and late winter.
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?
These maps show the median (or 50th percentile) maximum and minimum temperature for the given three months. The median temperatures are 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: