# About the climate outlooks

## About the outlooks

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- The rainfall and temperature climate outlook maps show the percentage chance of experiencing wetter/drier (and warmer/cooler) than median
weather at different timescales for the upcoming four months. Outlooks are available for weeks, fortnights, months and three-months ahead.^{1} - For the monthly to seasonal timescales, the outlook issued closest to the end of a calendar month provides the Bureau's best advice on the likely temperature and rainfall patterns for the three months ahead. For example, outlooks issued in the last week of June, for the three months July to September, will generally be more accurate than outlooks issued earlier in June.
- Additional information on the likelihood of rainfall exceeding particular totals is provided (e.g., the chance of receiving at least 10 mm), as well as the specific chances (e.g., rainfall totals that have a 75% chance being exceeded). These types of outlooks are particularly useful for the weekly to fortnightly timescale.

Details: Rainfall scenarios - Additional outlook information for temperature is provided for timescales shorter than one month. 'Difference from average' (anomaly) maps show how far above or below the 1981–2018 average the temperature is likely to be (1981–2018 is the model period; see Medians tab). The values provided are the middle of the predicted scenarios—also known as the ensemble mean.
- Additional information on the likelihood of unusually cool/warm or wet/dry conditions is provided by the chance that the outlook will result in conditions in the top or bottom 20% of historical observations.

Details: Extremes - The climate outlooks are generated from the Australian Community Climate Earth-System Simulator–Seasonal (ACCESS-S), the Bureau's dynamical (physics based) 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 cannot be this specific. This is because the further we look ahead, the more small, random changes can amplify into different weather patterns. However, longer-term forecasts of seasonal statistics, such as whether rainfall or temperature will generally be above or below median, are possible to accurately predict. Advances in modelling and computing power have allowed us to look at shorter timescales, making possible accurate predictions for sub-monthly timescales.

Details: Past accuracy - Probability-based outlooks are designed to be used as one of several planning tools within risk management and decision-making. The greatest benefits of using Bureau climate outlooks will accrue from use over a number of seasons or years.

Read our blog: What to expect from the climate when the outlooks are neutral Median is a measure of what is considered typical rainfall or temperature for a specific location; similar to mean. The median is the middle value when a set of values are ranked from lowest to highest. Due to the high variability of rainfall, and that in some locations just one or two extremely wet years can substantially change the overall average, using the median is the best representation of typical rainfall that would be expected.^{1}

Details: Medians

### Outlook update schedule

- One and two week outlooks: Mondays around 5pm and Thursdays around 3pm AEST/AEDT.
- One and three month outlooks: Thursdays at 3pm AEST/AEDT.
- Climate and water outlook videos: twice a month on Thursdays.

Download schedule as calendar file (ICS).

## Rainfall Outlooks

- Climate outlooks are given as a probability (or chance) of exceeding a specific threshold. For the Bureau’s rainfall outlook, it is provided as the chance of rainfall being above median, expressed as a percentage.
- For those interested in specific rainfall amounts (e.g. 200 mm for the season), or who make decisions at specific probabilities (e.g. if there is a 75% chance it will be drier than average), the Bureau uses the spread of possible rainfall amounts from the climate outlook model to transform output into rainfall scenarios that can be viewed in two different ways:
- Chance of at least: the chances that rainfall for the selected outlook period will exceed particular thresholds, e.g., chance of at least 200 mm over the coming three months, or 10 mm in a week.
- Outlook scenarios: rainfall amounts that are likely at a particular percentage chance, e.g., 25% chance of receiving the given rainfall amount for the period.

- The climate outlook data is prepared on a 60 km by 60 km grid. For the 'chance of at least' and 'outlook scenario' maps, a statistical technique is used to interpolate to a smaller 5 km by 5 km region. This is the resolution of the outlook scenario and chance of at least maps.

## Outlook scenario maps

- Outlook scenario maps present the climate outlook information as 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 September to 30 November 2019. 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 northwest Victoria, has a 75% chance of receiving at least 25 mm and possibly up to 50 mm of rain.

## Chance of at least maps

- Chance of at least maps also show the seasonal rainfall outlook, by displaying the chance of receiving a specified rainfall amount. You can choose from 15 different rainfall amounts (in mm) for the different time periods. To illustrate, the map to the right shows the chance of receiving a total rainfall amount of at least 50 mm during 1 September to 30 November 2019. The colours on the map show the percentage chance of 50 mm of rain occurring. The location highlighted with the black circle in northwest Victoria has a 50 to 75% chance of receiving 50 mm of rain 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 50 mm of rainfall is 50 to 75%, which is consistent with the outlook scenario which shows a 75% chance of at least 25 mm, and possibly up to 50 mm.

## Rainfall and temperature medians

- Median is a measure of what is considered typical rainfall or temperature for a specific location - similar to the mean. Due to the high variability of rainfall, and that in some locations, one very wet year can substantially change the overall mean, using the median (the middle number when you rank past rainfall or temperature from lowest to highest) is the best representation of typical rainfall.

- The medians (which are the same as the 50th percentile) for Bureau climate outlooks are calculated over the 1981 to 2018 period, as this is the period for which the climate model has been run in historical (or hindcast) mode.
- Median maps for the 1981 to 2018 period for all months and seasons are available from the climate outlook Map archive and Average maps. The median maps on the climate outlooks website will differ slightly from other median maps on the Bureau's website. This is because the dynamical model forecasts use a period of 1981 to 2018 to calculate medians, while other median maps typically use the full Bureau climate record (which extends for more than 100 years).
- The 20th percentile maps are also provided for the 1981 to 2018 period. Rainfall totals or temperature which falls below the 20th percentile are considered unusually dry or unusually cool by the Bureau, with the 20th percentile one of the two thresholds used in the extremes maps. This means that the forecast extremes fall into the bottom 20% of observations. Typically, it would be expected that these would occur roughly once every five years under a normal climate so for example, the coolest June out of five years, or the driest spring in five years. The 20th percentile maps are available on the climate outlook Average maps page.
- Similarly, the 80th percentile maps are also provided for the 1981 to 2018 period. Rainfall totals or temperature which are above the 80th percentile are considered unusually wet or unusually warm and are the upper threshold used in the extremes maps. This means the forecast extremes fall into the top 20% of observations. Typically, it would be expected that these would occur roughly once every five years under a normal climate so for example, the warmest June out of five years, or the wettest spring in five years. The 80th percentile maps are available on the climate outlook Average maps page.

## Chance of extremes maps

- Climate outlooks are able to be expressed as a percentage likelihood of extreme rainfall or temperature for those interested in possible weather extremes.
- Chance of extremes maps show the likelihood of unusually wet or dry, or warm or cool conditions. They are displayed by the chance that the outlook will result in rainfall or temperature in the top or bottom 20% of historical observations for the selected outlook period. In addition to the percentage chance of this occurring, the legend also shows how this could be displayed as the number of times more likely. For example, a 40% chance of being in the lowest 20% of rainfall records is also two times the usual level of likelihood. A 60% chance would mean it is three times as likely.
- Rainfall totals or temperatures which fall below the 20th percentile are considered unusually dry or unusualy cool by the Bureau. This means the forecast extremes fall into the bottom 20% of observations. Typically, it would be expected that these would occur roughly once every five years under a normal climate. For example, the coolest June out of five years, or the driest spring in five years.
- Rainfall totals or temperature which are above the 80th percentile are considered unusually wet or unusually warm. This means the forecast extremes fall into the top 20% of observations. Typically, it would be expected that these would occur roughly once every five years under a normal climate. For example, the warmest August out of five years, or the wettest spring in five years.
- The climate model uses a 60km by 60km grid. For these outlooks the forecasts are calibrated to observations on a 5km by 5km grid.

## Extremes pop-up bar charts

- The location-based bar charts (available via clicking on the outlook maps) show the forecast probability of rainfall/temperature being in a particular climatological range for your selected location. Specifically, they show the likelihood of being in the bottom 20% (decile 1 and 2) of historical records, the top 20% (decile 9 and 10), or the three ranges in between: decile 3 and 4; decile 5 and 6; and decile 7 and 8.
- The long-term average probability ("usual chance") for each category is 20% (shown by the horizontal dashed line) and the forecasts show the shift in likelihood compared to usual.
- In the example shown here for November to January rainfall for Kingsdale, the odds are stacked towards having a wetter season than usual in Kingsdale, with about double the usual likelihood of having decile 9 or 10 rainfall (i.e., greater than 242 mm). There is a reduced chance of having a very dry season.
- The rainfall bar charts are less useful for areas that are very dry. In these areas, the median rainfall (and even the higher thresholds) are often close to zero and dividing them into 5 categories is not as meaningful.
- The information above the bar charts shows the historical median for the selected location for the 1981-2018 period. Underneath this are the percentage chance of experiencing unusually dry (cool) conditions, the chance of exceeding the median, and the chance of experiencing unusually wet (warm) conditions. In the case of rainfall for example, a higher chance of experiencing unusually wet conditions would also typically mean a high chance of exceeding the median rainfall. Similarly, a high chance of experiencing unusually dry conditions would typically mean a low chance of exceeding the median rainfall.
- The stars refer to the accuracy of the outlook. If the model has performed well in forecasting for that location/period/time of year in the past, it will be indicated by three solid stars–meaning high past accuracy. If the model has low past accuracy for that outlook period, it will only have one solid star and two open stars. Refer to the Past Accuracy tab for more information on accuracy.
- Like the extremes maps, the pop-up boxes use a 5km by 5km grid. Pop-up boxes use the closest 5km grid box.

## The model

The Bureau of Meteorology's climate forecast system for weekly to seasonal and longer-range climate outlooks is called the Australian Community Climate Earth-System Simulator – Seasonal (ACCESS–S). It is a state-of-the-art dynamical (physics-based) forecast modelling system, which uses ocean, atmosphere, ice and land observations to initiate outlooks for the season ahead. The ACCESS–S climate model is a collaboration between the Bureau of Meteorology and the UK Meteorological Office (UKMO).

The atmosphere and land model components of ACCESS–S operate at an approximate resolution of 60 km in the Australian region. At this resolution, the model can represent the markedly different climates of the Great Dividing Range and the eastern seaboard in Australia's east.

The ocean model component of ACCESS–S operates at an approximate resolution of 25 km in the Australian region. At this resolution, the model can resolve small-scale currents and eddies.

ACCESS-S outlooks are based on a 99-member ensemble. This is a common climate forecasting technique where the model is run 99 times with slightly different initial conditions to capture a range of likely future scenarios.

Being a dynamical model, ACCESS–S 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.

ACCESS–S replaced POAMA in August 2018. POAMA, also a dynamical climate model, was used for official Bureau climate outlooks from May 2013 until ACCESS–S was brought into operation. Prior to 2013, the Bureau used a statistical method to generate climate outlooks.

For more technical details on ACCESS–S, see: Hudson, D. et al, 2017: ACESS-S1: The new Bureau of Meteorology multi-week to seasonal prediction system. Journal of Southern Hemisphere Earth Systems Science, 67:3 132-159

Read more about ACCESS-S.

## 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. The Bureau measures the accuracy of its climate models 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 climate outlook model over the period from 1981 to 2018.

## Accuracy assessment for chance of exceeding median outlooks

- The accuracy measure of the chance of exceeding median outlooks is based on the percent correct approach, but is weighted by the size of the observed difference from median. This accuracy measure looks at the percentage of time the outlooks correctly predicted being above or below median during the 1981–2018 period for any given location, and is then weighted by the size of the observed difference from the historical median.
- So if the model correctly favoured an area that had an anomalously large rain event, it scores highly, but if it misses that event, points are deducted from the weighting calculation.

More information on the weighted percent correct accuracy metric. - Weighted percent consistency is only one of the ways the Bureau assesses its climate outlooks, and it is presented here as it is one of the simplest and most informative measurements of accuracy of the chance of exceeding the median outlooks. Other aspects of overall model ability (skill) are also routinely assessed.

## Accuracy assessment for extreme outlooks

- A different measure of accuracy is used to assess the ability of the model to correctly predict the occurrence of an extreme or historically unusual condition (for rainfall or temperature). The relative operating characteristic (ROC) is a skill score which measures the ability of the model to get the correct outcome for each forecast probability. A correct extreme outlook is known as a "hit", and an extreme outlook that was forecast but did not eventuate is known as a "false alarm". These hits and false alarms are assessed over the 1981–2018 period. A "ROC curve" is then plotted using pairs of hit rates and false alarm rates across the range of forecast probabilities (0–100%). The ROC curve shows the ability of the model to consistenty forecast a higher probability of occurrence of extreme conditions than it would do for a non-occurrence. The area under the curve (AUC) varies from 0 (model has no skill) to 1 (model has perfect skill), or from 0 to 100% in the percentage sense. More information on the ROC curve.

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 |

- To make things simpler, the past accuracy of the model is presented on the same scale for all products (although different evaluation methods are used).
- Past accuracy maps for all months and seasons are available from the climate outlook Map archive and Accuracy maps. On these maps, the higher the percentage 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 shaded have a lower 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 accuracy for the second month ahead is generally less than the accuracy for the first month ahead. This is to be expected as the second month looks further into the future and is further from when the outlook period starts. Similarly, the accuracy for one and three month outlooks issued closest to when the outlook period starts is typically higher than the accuracy for outlooks issued earlier in the month. This same principle can be applied to weekly and fortnightly outlooks; the first week or fortnight typically has higher accuracy than the second week or fortnight.

## Climate drivers

- Australia's climate can vary greatly from one year to the next. The links below, present some key influences that drive the Australian climate. They have varying levels of impact in different regions and at different times of year. See: Australian climate influences.