About the climate extremes analyses
Extreme climate indices used
Extreme climate events such as heat waves, cold snaps, floods and dry spells have significant impacts on society. To examine whether such extremes have changed over time a variety of extreme climate indices can be defined, such as the number of days per year which exceed, or fail to exceed, fixed thresholds. However, since people tend to adapt to their local climate, a threshold considered extreme in one part of Australia could be considered quite normal in another. To overcome this problem, thresholds based on percentile values can also be defined.
The 27 extreme temperature and rainfall indices used here are based on those defined by the WMO Expert Team on Climate Change Detection Monitoring and Indices. Some of the extreme temperature indices have been modified for Australian purposes.
| Extreme temperature indices | Definition |
|---|---|
| Very hot days | Annual count of days with maximum temperature > 40°C |
| Hot days | Annual count of days with maximum temperature > 35°C |
| Very hot nights | Annual count of nights with minimum temperature > 25°C |
| Hot nights | Annual count of nights with minimum temperature > 20°C |
| Cold days | Annual count of days with maximum temperature < 15°C |
| Very cold days | Annual count of days with maximum temperature < 10°C |
| Cold nights | Annual count of nights with minimum temperature < 5°C |
| Frost nights | Annual count of nights with minimum temperature < 0°C |
| Warm days | Percentage of days with maximum temperature > 90th percentile |
| Warm nights | Percentage of nights with minimum temperature > 90th percentile |
| Cool days | Percentage of days with maximum T < 10th percentile |
| Cool nights | Percentage of nights with minimum T < 10th percentile |
| Highest maximum temperature | Annual maximum value of daily maximum temperature |
| Highest minimum temperature | Annual maximum value of daily minimum temperature |
| Lowest maximum temperature | Annual minimum value of daily maximum temperature |
| Lowest minimum temperature | Annual minimum value of daily minimum temperature |
| Extreme precipitation indices | Definition |
|---|---|
| Wet days | Annual count of days with daily precipitation ≥ 1 mm |
| Heavy precipitation days | Annual count of days with daily precipitation ≥ 10 mm |
| Very heavy precipitation days | Annual count of days with daily precipitation ≥ 30 mm |
| Maximum 1-day precipitation | Annual maximum 1-day precipitation total |
| Maximum 5-day precipitation | Annual maximum consecutive 5-day precipitation total |
| Very wet day precipitation | Annual total precipitation when daily precipitation > 95th percentile |
| Extremely wet day precipitation | Annual total precipitation when daily precipitation > 99th percentile |
| Annual total wet day precipitation | Annual total precipitation on wet days (daily precipitation ≥ 1 mm) |
| Simple daily intensity | Annual total precipitation divided by the number of wet days (daily precipitation ≥ 1 mm) |
| Consecutive dry days | Maximum number of consecutive days with daily precipitation < 1 mm |
| Consecutive wet days | Maximum number of consecutive days with daily precipitation ≥ 1 mm |
Percentile calculations
Percentile-based threshold levels are calculated for 5-day windows across the annual cycle using the standard 1961 to 1990 normal period i.e. daily rainfall and temperatures values are compared relative to varying thresholds throughout the year. So it is possible to have warm days during winter, cold days during summer, or extreme precipitation recorded at any time of the year.
Trend maps available
Australian extreme climate trend maps are available for periods starting from the beginning of each decade from 1900 to 1980 for rainfall, and from 1910 to 1980 for temperature. Analysis periods starting after 1980 are considered too short to calculate meaningful trend values. Trend maps for the extreme temperature indices for the earlier periods (e.g. 1910-present) show fewer calculated trends than for the periods starting from 1960, since fewer locations had digitised data in the earlier period.
Interpreting the trend maps
Trends in extreme indices are presented using "bubble" plots, rather than analysed fields, due to the sparse network of locations for which some indices are relevant. Trend values are only calculated for a particular location if its series of annual extreme values are non-zero for at least 50% of years for temperature indices, and at least 25% for rainfall indices. Consequently trend values are not calculated or plotted for some indices in some regions eg. frost nights in northern Australia. Trends in extreme values also tend to be "noisier" than for the mean climate making them more difficult to analyse onto a continuous field.
The trend maps are a useful way to compare how climate extremes have changed in different regions of Australia over time. They are also interesting to compare with changes in the mean climate over the same period. However, they need to be interpreted with caution. Trend values have been determined from a linear (straight line) fit to the data, but the change may not have been gradual. For example, a calculated trend could be due to a relatively rapid "step" change, with the remainder of the series being fairly flat. Also, trend values are highly dependent on the start and end dates of the analysis. Consequently trend maps starting in different decades can look remarkably different. Users are advised to keep in mind the period over which trend values have been calculated.
In addition, the trend values calculated here using past observations should not be used to imply future rates of change. Due to the complex interactions between the natural and human drivers of climate change and variability, the climate of any location is always changing. Future rates of change will depend on how these drivers interact in future, which will not necessarily be the same as in the past.
Data used
The extreme climate analyses are calculated from homogeneous and high-quality temperature and rainfall datasets respectively. The homogeneous temperature dataset, known as the Australian Climate Observations Reference Network - Surface Air Temperature, or ACORN-SAT, dataset) was developed specifically for monitoring long-term trends and variability in the Australian climate. This dataset employs the latest analysis techniques and takes advantage of newly digitised observational data to provide a daily temperature record over more than 100 years. This data will enable climate researchers to better understand long-term changes in monthly and seasonal climate, as well as changes in day-to-day weather. The high-quality daily rainfall dataset is based on a historical rainfall dataset (Lavery et al. 1992), which involved identifying and removing problem records using statistical techniques, visual checks and station history information (metadata).
Please note that any use of these data should be acknowledged to the Bureau of Meteorology. Apart from the purposes of study, research, criticism and review, no part of these data may be reproduced, or redistributed for any commercial purposes, or distributed to a third party for such purpose, without written permission from the Director of Meteorology.
Further information
More information about the homogenised temperature dataset, including additional data, station details, the methods used and a peer review of the dataset can be found on the ACORN-SAT page.
Haylock, M. and Nicholls, N. 2000. Trends in extreme rainfall indices for an updated high quality data set for Australia. International Journal of Climatology, 20, 1533-1541.
Lavery, B., Kariko, A. and Nicholls, N. 1992. A historical rainfall data set for Australia. Australian Meteorological Magazine, 40, 33-39.
