About the climate outlooks

About the outlook

Video demonstration of the climate outlooks   Audio    Transcript   

Video about climate outlooks    Audio    Transcript   

  • The rainfall and temperature climate outlook maps show the likelihood, as a percentage, of experiencing wetter/drier (and warmer/cooler) than median weather for the upcoming three months. Outlooks for separate months are also provided.
  • For rainfall, additional information on the likelihood of rainfall exceeding particular totals, as well as the rainfall totals that have a specific chance of occurring are also provided.
    Details: Rainfall totals
  • The probabilities (or chances) are generated from the Predictive Ocean Atmosphere Model for Australia (POAMA), the Bureau's dynamical climate model.
    Details: Outlook model
  • While weather forecasts can tell you what the temperature will be tomorrow and how much rain to expect, climate outlooks can not be this specific. This is because they are looking further ahead and because of the chaotic nature of the climate. However, longer-term forecasts of seasonal statistics, such as medians are possible with accuracy.
    Details: Past accuracy
  • Probability based outlooks should be used as one tool only in risk management and decision making. The greatest benefits of using Bureau climate outlooks will accrue from long-term use, for example over a 10 year period.

Outlook update schedule

The outlooks are updated each month at 10 am AEST/AEDT.

Rainfall scenarios

  • Climate outlooks are given as a probability (or chance) of exceeding a specified threshold. In the case of the Bureau’s primary rainfall outlook, it is given as the chance of rainfall being above median. However, many people are interested in specific rainfall amounts (e.g., 200 mm for the season), or are prepared to make decisions at specific probabilities (e.g., if there is a 75% chance it will be drier than normal). To accommodate for this need, the Bureau has used a statistical technique to transform output from the climate outlook model into rainfall scenarios that can be viewed in two different ways:
    • Chance of at least (the chances that the three-month or separate month rainfall will exceed particular thresholds, e.g. 200 mm)
    • Outlook scenarios (the three-month or separate month rainfall amounts that have a specific chance of occurring, e.g. 25%).
  • 75% chance of exceedingThe climate outlook data is prepared on a 2.5° by 2.5° grid (or roughly 250 km by 250 km). So chance of above median forecasts are calculated for a region of approximately 250 km by 250 km, not for the specific longitude and latitude displayed in the pop-up boxes. However, in the case of the chance of at least and outlook scenario maps, a statistical technique is used to transfer the chances for the larger region to a smaller 25 km by 25 km region (the Bureau's rainfall data set is used, which has a 25 km by 25 km resolution). This is the resolution of the outlook scenario and chance of at least maps (including the chance of at least information shown in the graphs in the location pop-up boxes). An example of a pop-up box is shown on the right, the chance of at least information is displayed by graph.

Outlook scenario maps

  • 75% chance of exceedingOutlook scenario maps convert the seasonal climate outlook into the rainfall amounts which have a 75%, 50% or 25% chance of occurring. To illustrate, the map on the right shows the rainfall outlook from 1 July to 30 September 2008. The colours on the map show the amount of rainfall (mm) that has a 75% chance of occurring during this period. The location highlighted with the black circle in western Victoria, has a 75% chance of receiving at least 100 mm and possibly up to 200 mm of rain.

Chance of at least maps

  • Chance of at least 150 mmChance of at least maps present the seasonal rainfall outlook in a different way. You can choose from 12 different rainfall amounts (in mm) for the coming season. The map displays the chance of receiving that amount. To illustrate, the map to the right shows the chance of receiving a total rainfall amount of at least 150 mm between July and September 2008. The colours on the map show the percentage chance of 150 mm of rain occurring. The location highlighted with the black circle in western Victoria has a 65 to 75% chance of 150 mm of rain occurring during the period.
  • Chance of at least rainfall outlook maps are consistent with the Outlook scenarios. For the same location in the examples above, the chance of at least 150 mm of rainfall is 65 to 75%, which is consistent with the outlook scenario which shows a 75% chance of at least 100 mm, and possibly up to 200 mm.

Rainfall and temperature medians

  • The medians (or 50th percentile) for Bureau climate outlooks are calculated from the 1981 to 2010 period. The quality of dynamical model forecasts is partly determined by the coverage and accuracy of the observations fed into the model. Therefore, to be consistent from one year to the next, the Bureau has only run its model during the modern satellite era, which is why medians are calculated post-1980 for climate outlooks.
  • Median maps for the 1981 to 2010 period for all months and seasons are available below. The median maps on the climate outlooks pages will sometimes differ from other median maps on the Bureau's website. This is because the dynamical model forecasts use a period of 1981 to 2010 to calculate medians (as explained above), while the median maps located on other parts of the Bureau's website use the full Bureau climate record (which extends for more than 100 years).

Median rainfall and temperature maps

About the model

  • 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 division. This coupled atmosphere-ocean model is a state of the art seasonal forecast system.
  • The dynamic 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.
  • The model maps and text are typically updated once a month, on a Thursday at 10am. The outlook is issued for the coming three months. For example, the outlook for winter (June to August) will be issued in late May. Outlooks are also available for the first two individual months within the three-month outlook period.
  • The climate outlook data is prepared on a 2.5° by 2.5° grid (or roughly 250 km by 250 km). So chance of above median forecasts are calculated for a region of approximately 250 km by 250 km, not for the specific longitude and latitude displayed in the pop-up boxes. However, in the case of the chance of at least and outlook scenario maps, a statistical technique is used to transfer the chances for the larger region to a smaller 25 km by 25 km region (the Bureau's rainfall data set is used, which has a 25 km by 25 km resolution). This is the resolution of the outlook scenario and chance of at least maps (including the chance of at least information shown in the graphs in the location pop-up boxes).
  • The 250 km by 250 km (or 25 km by 25 km for rainfall scenarios) data grids are smoothed to produce realistic looking contours on the maps. Occasionally, close to contour lines, the values in the pop-up may differ slightly from that displayed on the underlying maps. This is because the pop-up takes information from the data grid, while the map is displaying contours that have been slightly smoothed.

Statistical and dynamical model outlooks

  • In May 2013 the Bureau changed the model it uses for its climate outlook service to a dynamical model. Outlooks were previously based on a statistical system which used only historical climate as a guide to the future.
  • POAMA has been shown to have greater forecasting accuracy for Australia than the statistical system. Moving to POAMA also means future increases in accuracy are likely as new science, better modelling techniques, more observations and greater computer power are introduced. Continuing with a statistical system, where the skill is increasingly difficult to gauge due to our changing climate, offers little opportunity for significant improvements in forecast accuracy.

Past accuracy

  • Model accuracy (also known as model confidence or model skill) is a measure of how well the 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 real outcomes matched the forecast. This measurement of accuracy is known as percent consistent (or past accuracy), and has been tested for the Bureau's seasonal outlook model over the period from 1981 to 2010.
  • Past accuracy is not the only way the Bureau assess climate models, but it is presented here as it is one of the simplest and most informative measurements of accuracy. Other methods that test other aspects of overall model ability are also routinely assessed at the Bureau.
Past accuracy legend
      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
  • Past accuracy maps for all months and seasons are available below. On these maps, the higher the percent consistent value for an area (i.e. the greener/darker the map) the greater the accuracy of outlooks has been in that area for that time of year and the more confidence can be placed in future outlooks. Areas of the map that are not green/coloured do not have a good record of accuracy in that area for that time of the year. In the least accurate areas, the outlooks perform no better than random chance (equivalent to the flip of a coin). As a guide, the Bureau uses the terminology in the table on the right when referring to the accuracy of the outlooks.
  • The rainfall outlook has highest accuracy during autumn and spring. In summer and winter there is lower accuracy, particularly over central Australia. The maximum temperature outlook has good accuracy for most of the year, with the lowest point during the winter seasons. Of the variables predicted (rainfall, 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.
  • The accuracy for the second month ahead will generally be less than the accuracy for the first month ahead, this is to be expected as the second month is looking further into the future.

Outlook past accuracy maps

The accuracy of a particular monthly, or seasonal, outlook will vary, depending on how long before the start of the month or season it was generated. Generally, the closer to the start of the time period an outlook is produced, the higher the accuracy will be. For example, an April outlook generated 10 days prior to the start of April (i.e., generated around March 20) will have higher accuracy than the April outlook generated 40-days prior to the start (i.e., generated around February 18). View accuracy information by selecting options from the lists below.

Monthly rainfall outlook assessment: January (generated 10 days earlier)