As of December 2022, the highest recorded temperature in Australia was at Onslow Airport in Western Australia, where the temperature was **** degrees Celsius. This was matched by the highest temperature recorded at Oodnadatta Airport, South Australia, in 1960. What is causing increasing temperatures? The annual mean temperature deviation in the country has increased over the past century. In 2024, the annual national mean temperature was **** degrees Celsius above average. Climate experts agree that the major climate driver responsible for the heat experienced in Australia was a positive Indian Ocean Dipole (IOD). This is where sea surface temperatures are cooler in the eastern half of the Indian Ocean than the western half. The discrepancy in temperatures led to drier, warmer conditions across Australia. Global warming due to greenhouse gas emissions has been linked to the warming of sea surface temperatures and the IOD. Social change While the topic of global warming is undoubtedly controversial, many people perceive global warming as influencing Australia’s climate. In 2023, around ** percent of Australians believed climate change was occurring. Furthermore, around **** of Australians agreed that their government was not doing enough in terms of climate change action.

Temperature in Australia increased to 22.77 celsius in 2024 from 22.31 celsius in 2023. This dataset includes a chart with historical data for Australia Average Temperature.

This statistic displays the average minimum and maximum temperatures in Australia in 2015. According to the source, in Queensland, the hottest temperature was ***** degrees on average in 2015.

In 2024, the mean temperature deviation in Australia was 1.46 degrees Celsius higher than the reference value for that year, indicating a positive anomaly. Over the course of the last century, mean temperature anomaly measurements in Australia have exhibited an overall increasing trend. Temperature trending upwards Global land temperature anomalies have been fluctuating since the start of their measurement but show an overall upward tendency. Australian mean temperatures have followed this trend and continued to rise as well. Considered the driest inhabited continent on earth, this has severe consequences for the country. In particular, the south of Australia is predicted to become susceptible to drought, which could lead to an increase in bushfires as well. The highest temperatures recorded in Australia as of 2022 were measured in South Australia and Western Australia, both exceeding 50 degrees. The 2019/2020 bushfire season Already prone to wildfires due to its dry climate, the change in temperature has made Australia even more vulnerable to an increase in bushfires. One of the worst wildfires in Australia, and on a global level as well, happened during the 2019/2020 bushfire season. The combination of the hottest days and the lowest annual mean rainfall in 20 years resulted in a destruction of 12.5 million acres. New South Wales was the region with the largest area burned by bushfires in that year, a major part of which was conservation land.

In 2023, the observed annual average mean temperature in Australia reached 22.32 degrees Celsius. Overall, the annual average temperature had increased compared to the temperature reported for 1901. Impact of climate change The rising temperatures in Australia are a prime example of global climate change. As a dry country, peak temperatures and drought pose significant environmental threats to Australia, leading to water shortages and an increase in bushfires. Western and South Australia reported the highest temperatures measured in the country, with record high temperatures of over 50°C in 2022. Australia’s emission sources While Australia has pledged its commitment to the Paris Climate Agreement, it still relies economically on a few high greenhouse gas emitting sectors, such as the mining and energy sectors. Australia’s current leading source of greenhouse gas emissions is the generation of electricity, and black coal is still a dominant source for its total energy production. One of the future challenges of the country will thus be to find a balance between economic security and the mitigation of environmental impact.

The Bureau of Meteorology provides the Australian and international maritime communities with weather forecasts, warnings and observations for coastal waters areas and high seas around Australia. Generally most of these services are provided routinely throughout the day, while marine weather warnings may be issued at any time when the need becomes apparent. Because of the complex nature of the sea, the Bureau of Meteorology uses advanced computer models to predict the physical characteristics of the ocean. These computer forecasts are used by meteorologists in the preparation of marine forecasts and warnings. The forecasts include wind, weather, sea and swell and are intended to describe the average conditions over specified areas. Marine forecasts have been enhanced by the inclusion of ocean currents and sea-surface temperature forecasts through the BLUElink ocean forecasting initiative. The Sea Surface Temperature Browse Service provides access to browse images (1:5 resolution) of satellite derived Daily Sea Surface Temperature data available from 30 December 1998. The Bureau currently uses measurements from the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) series of polar orbiting satellites to derive SSTs for the Australian region. The data is calibrated and quality controlled against SST data collected from ships and drifting buoys. The SSTs are used in real time operations and also archived as the data as part of Australia's National Climate Record.

This record also provides links to BOM Ocean Analysis data including Daily/Weekly/Monthly records of Australian and Global Sea Surface and Subsurface Temperatures.

We must understand the natural cycles of the oceans to understand the evolution of our climate through geological time. Core MD 032607 was obtained in 2003 off the coast of Sumatra (36.9606 S, 137.4065 E). By investigating the properties and components of this core we are able to reveal some information regarding past oceanographic and climatic systems. Information obtained or inferred from the core include the isotopic composition of oxygen and carbon through time, an age vs. depth profile of the core (revealing sedimentation rates), the relative abundance of planktonic foraminifera over time, and estimates of historical sea-surface temperatures.

Australian Bureau of Meteorology assembled this dataset of 191 Australian rainfall stations for the purpose of climate change monitoring and assessment. These stations were selected because they are believed to be the highest quality and most reliable long-term rainfall stations in Australia. The longest period of record is August 1840 to December 1990, but the actual periods vary by individual station. Each data record in the dataset contains at least a monthly precipitation total, and most records also have daily data as well.

The maximum temperature of the hottest month (the maximum temperature of any monthly maximum temperature)

In 2023, the observed annual average maximum temperature in Australia reached 29.67 degrees Celsius. Overall, the annual average maximum temperature had increased compared to the temperature reported for 1901.

This record links to Bureau of Meteorology "Precis forecast" information for Western Australia, available through an ftp download. The Bureau of Meteorology's "Precis forecast - Western Australia" …Show full descriptionThis record links to Bureau of Meteorology "Precis forecast" information for Western Australia, available through an ftp download. The Bureau of Meteorology's "Precis forecast - Western Australia" product contains a 7 day forecast, per location across Western Australia, with daily projected values for temperature, rainfall and weather conditions. Data (7-day precis forecast data, for Western Australia) is available in XML format. (The plain text and html formats were withdrawn in Feb 2016). Place Names in the xml are the same as those that were used in the plain text and html format files. The XML file uses the AAC location code (and location name), rather than the StationID code. The coordinates related to each AAC code/ location name, in the XML formatted file, are listed in the PointPlaces [IDM00013.*] data files, available from ftp://ftp.bom.gov.au/anon/home/adfd/spatial/IDM00013.dbf [open the dbf file, using Excel]. Note that the precis forecasts relate to an area surrounding the nominated location, the coordinates of which are intended to be the "centre of town" for that location ( as derived from Geoscience Australia's placename Gazetteer)". Data content As well as forecast values [per day, across 7 days] for minimum and maximum temperature, rainfall (range and probability), and a precis of expected weather conditions for locations in Western Australia, the dataset (latest forecast only) also contains information on when the file was created, and the timespan that a value applies to.

IOCI3, a climate research collaboration between CSIRO, the Bureau of Meteorology (BoM) and the Western Australian Government, produced maps of mean hot spell intensity, frequency and duration for the 1958-2010 period using estimates derived from statistical models. They also produced maps of trends in hot spell intensity, frequency and duration for this time period. In addition they provided maps of mean hot spell thresholds, intensity, frequency and duration for the 1981-2010 period using estimates derived from statistical models, and projections of these characteristics for the 2070-2099 period under the A2 greenhouse gas (GHG) emissions scenario (described in the IPCC Special Report on Emissions Scenarios [SRES]), as well as the difference between these two periods." Results are provided in the JPEG file format. Lineage: High quality station data as well as quarter-degree gridded (0.25°× 0.25° resolution) daily maximum temperature data from BoM Australian Water Availability Project (AWAP) were used to produce these results. Hot spell temperature thresholds were selected using statistical methods. Hot spell occurrence (frequency) was modelled by a Poisson process, hot spell intensity by a generalized Pareto distribution, and hot spell duration through a geometric distribution. The Generalized Linear Model framework was used to estimate the parameters in the model for hot spells. This method was applied to daily maximum temperature data simulated from the CSIRO Cubic Conformal Atmospheric Model (CCAM) for both the present-day and possible future climate under the SRES A2 GHG emissions scenario. The CCAM was nested in the CSIRO Mk3.0 Global Climate Model host for the SRES A2 scenario. Caveats & limitations: The hot spell projections should be seen as initial estimates only, and they should not be used for making impact, vulnerability and risk assessments. They were made using only one climate model (CCAM); more work using an ensemble of global and regional climate model results is required to provide more robust projections of hot spells in Western Australia.

Extreme events are by definition rare, and analysis relies on partial (extreme) datasets (e.g., daily maximum temperatures higher 35 °C). In addition, estimating extremes necessitates extrapolating beyond such relatively small observed records. Consequently, the uncertainty associated with these projections of extremes is large, especially when extrapolating from a small dataset. To produce these projections we used AWAP data was used to overcome data shortages. However, the methods used to construct the AWAP dataset (interpolation) may smooth out some extreme values; this may lead to an underestimation of extremes in some cases. To these uncertainties are added the uncertainties inherent in the use of climate models.

The development of the Australian geothermal industry over the last decade owes much to compilations of drill hole temperature data undertaken in the early 1990s in Canberra. The portrayal of this data on maps of predicted temperature at five kilometres depth, and contained heat resource calculations from this data, have shifted the perception that because Australia does not have significant current magmatic activity there is no geothermal potential. The Australian geothermal industry arguably now leads the world in terms of development of amagmatic geothermal systems for electricity generation. Work at the Bureau of Mineral Resources Geology and Geophysics (now Geoscience Australia) provided a brief compilation of open-file drill hole temperature data, and a map of thermal gradient (Nicholas et al. 1980). The work of Somerville et al. (1994) provided a much larger compilation, and included a significant study into the resource potential that could be accessed by Hot Dry Rock technology. Finally, Chopra and Holgate (2005 Austherm version) further extended the dataset and produced an image of the predicted temperature at 5 km that has become very widely distributed. (Figure 1). OZTEMP is the result of work undertaken to refine the Austherm database, and to utilise new datasets within a GIS for the extrapolation of temperature to 5 km depth and the interpolation between these datapoints. The method, which is largely derivative from that of Chopra and Holgate (2005), and the areas of new work, is described briefly below.

Max Temp of Warmest Month (Bio05) raster for southeastern Australia.Input file used to model the species distributions of 40 reptile species in Victoria, Australia.File obtained from the WorldClim (https://worldclim.org/) version 2 database, at a spatial resolution of ~1 km2Cell size - 250 x 250Original file has been clipped to southeastern Australia.Methods used to generate the input files and perform modelling are outlined in the methods section of the abovementioned publication.Citation - Fick, S.E. and Hijmans, R.J. (2017), WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol, 37: 4302-4315. https://doi.org/10.1002/joc.5086

This record provides a listing of meteorological data collected in the Australian Antarctic Territory by members of the Australian Antarctic program (and it's predecessors) and the Bureau of Meteorology. The data have been obtained by manual observations and by automatic weather stations.

All data are available from the Bureau of Meteorology, and are considered to be the authoritative source of weather data in the Australian Antarctic Territory (as they have been quality checked). Raw data directly from the automatic weather stations at the stations is available at https://data.aad.gov.au/aws.

The data available here includes:

• Automatic Weather Station data from 7 sites - Casey, Davis, Macquarie Island, Mawson, Wilkins, Davis Whoop Whoop, and Casey Skiway South. Data resolution varies, but is approximately every 30 minutes.

• Daily weather data from 48 sites. Note - not all of these sites are still operational.

• Synoptic weather data from 53 sites. Note - not all of these sites are still operational.

• Terrestrial soil data from 4 sites. Note - not all of these sites are still operational.

• Upper air data from 5 sites. Note - not all of these sites are still operational.

• High resolution, 1 minute automatic weather station data from 7 sites - Casey, Davis, Macquarie Island, Mawson, Wilkins, Davis Whoop Whoop, and Casey Skiway South.

• Daily and Synoptic data from a number of decommissioned sites.

Site details of 24 sites. For full site listings, seeing the file for station details within each dataset ("HM01X_StnDet").

Meteorology data from Wilkes Station, Antarctica 1960 - 1968 - data collected include: temperature (maximum and minimum; dry bulb; wet bulb; dew point), air pressure, wind (direction,speed and maximum gust; run (greater than 3 m)), phenomena, sunshine, cloud.

Meteorology data from Casey Station (current) (300017), Antarctica 1989 ongoing, surface measurements - location 66.2792 S, 110.5356 E, with a barometric height of 42.3m. Data collected include the following: temperature (maximum and minimum; dry bulb), air pressure, wind (direction;speed), humidity, rainfall, sunshine, cloud, visibility. An AWS is now in operation at Casey station.

Meteorology data from Davis Station (300000), Antarctica 1957 ongoing, surface measurements - location 68.5772 S, 77.9725 E, with a station height of 16.0m and a barometric height of 22.3m. - location 66.2792 S, 110.5356 E, with a barometric height of 42.3m. Data collected include the following: temperature (maximum and minimum; dry bulb; terrestrial minimum, soil temperature), air pressure, wind (direction, speed; run), rainfall, sunshine, cloud, humidity, visibility. An AWS is now in operation at Davis station.

Meteorology data from Mawson Station (300001), Antarctica 1954 ongoing, surface measurements - location 67.6014 S, 62.8731 E, with a station height of 9.9m and a barometric height of 16.0m. Data collected include the following: temperature (maximum and minimum; dry bulb), air pressure, wind (direction,speed), humidity, cloud, rainfall, sunshine. An AWS is now in operation at Mawson station.

Meteorology data from Macquarie Island Station (300004), 1948 ongoing, surface measurements - location 54.4997 S, 158.9522 E, with a station height of 6.0m, a barometric height of 8.3m and an aerodrome height of 6.0m. Data collected include the following: temperature (maximum and minimum; dry bulb; wet bulb; terrestrial minimum; soil 10cm,20cm,50cm,100cm), air pressure, wind (direction; speed; run), rainfall, sunshine, cloud, visibility, humidity, sea state, radiation. An AWS is now in operation at Macquarie Island station.

Meteorology data from Heard Island (Atlas Cove) Station (300005), first installed 1948 - location 53.02 S, 73.39 E, with a station height of 3.0m, and a barometric height of 3.5m. Data collected include the following: temperature, air pressure, rainfall.

Meteorology data from Heard Island (The Spit) Station (300028), installed 1992 - location 53.1069 S, 73.7211 E, with a station height of 12.0m and a barometric height of 12.5m. Data collected include the following: temperature (air and minimum terrestrial), air pressure, humidity, wind direction, sunshine, cloud.

Meteorology data from Casey Station (current) (300017), Antarctica 1989 ongoing, upper atmosphere measurements - location 66.2792 S, 110.5356 E, with a barometric height of 42.3m. Data collected include the following: upper atmospheric temperature (via a radiosonde), upper atmospheric wind (using a wind find radar).

Meteorology data from Davis Station (300000), Antarctica 1957 ongoing, upper atmosphere measurements - location 68.5772 S, 77.9725 E, with a station height of 16.0m and a barometric height of 22.3m. Data collected include the following: upper atmospheric temperature (using radiosonde), upper atmosphere wind (using wind find radar).

Meteorology data from Mawson Station (300001), Antarctica 1954 ongoing, upper atmosphere measurements - location 67.6014 S, 62.8731 E, with a station height of 9.9m and a barometric height of 16.0m. Data collected include the following: upper atmosphere temperature and wind (using sounding processor and GPS).

Meteorology data from Macquarie Island Station (300004), 1948 ongoing, upper atmosphere measurements - location 54.4997 S, 158.9522 E, with a station height of 6.0m, a barometric height of 8.3m and an aerodrome height of 6.0m. Data collected include the following: upper atmosphere temperature and wind (collected using wind find radar and radiosondes).

Meteorology data from Knuckey Peaks Station (300009), 1975 - 1984 - location 67.8 S, 53.5 E.

Meteorology data from Heard Island (Atlas Cove) Station (300005), first installed 1948, upper atmosphere measurements - location 53.02 S, 73.39 E, with a station height of 3.0m, and a barometric height of 3.5m. Data recorded include: upper atmosphere temperature, upper atmosphere wind.

Meteorology data from Mount King Satellite of Mawson Station (300010), Antarctica, 1975 - 1984 - location 67.1 S, 52.5 E, with a station height of 112.5m. Data recorded include: temperature (dry bulb), air pressure, humidity, visibility, and some upper atmosphere measurements.

Meteorology data from Lanyon Junction Station (300011), Antarctica 1983 to 1987 - location 66.3 S, 110.8667 E, with a station height of 470.0m. Observational records include: humidity charts, thermograph charts, pilot balloon flights, and surface observations.

Meteorology data from Haupt Nunatak (Casey) Automatic Weather Station (site 300012), installed 1994 - located at 66.5819 S, 110.6939 E near Casey station, with a station height of 81.4m and a barometer height of 83.4m. Data recorded include: barometric pressure, wind direction, speed and gust, and air temperature.

Meteorology data from Depot Peak site (300013), Antarctica, installed 1990 - location 69.05 S, 164.6 E, and has a station height of 1600 m. Instruments at the site include: barometer, cup anemometer and humicap (temperature and humidity).

Meteorology data from Edgeworth David (Bunger Hills) Station (300014), Antarctica, 1986 to 1989 - location 66.25 S, 100.6036 E, with a station height of 6.0m and a barometric height of 7.0m.

Meteorology data from Law Base Station (300015),Antarctica, 1989 - 1992 - location 69.4167 S, 76.5 E, with a station height of 77.0m.

Meteorology data from Dovers Station (300016), Antarctica, 1988 to 1992 - located at 70.2333 S, 65.85 E, with a station height of 1058.0m and a barometric height of 1059.0m. Data recorded include: Air pressure, air temperature, humidity, wind speed and direction, cloud, visibility and upper atmosphere data.

Meteorology data from Balaena Island Automatic Weather Station (300032), installed 1994 - location 66.017 S, 111.0833 E, 22.21 Nm NE of Casey, with a station height of 8.0m and a barometric height of 10m. Data collected from this AWS include: Wind speed and direction, wind gust, air temperature and barometric pressure.

Meteorology data from Snyder Rocks Automatic Weather Station (300033), Antarctica, installed 1994 - located at 66.55 S, 107.75 E, with a station height of 40m and a barometric height of 42m. Data collected include: air temperature, barometric pressure, wind speed, direction and gust.

Meteorology data from Law Dome Summit South Automatic Weather Station (300034), Antarctica, installed 1995 - location 66.717 S, 112.9333 E, with a station height of 1375.0 m. Data collected include: air pressure, air temperature, wind speed and direction.

Meteorology data from Casey(old) Station, Antarctica 1969 - 1989. Data collected include: temperature (maximum and minimum; dry bulb; wet bulb; dew point), air pressure, wind (direction,speed and maximum gust; run (greater than 3 m)), phenomena, sunshine, cloud, radiation (global,diffuse).

The maximum temperature of the hottest month (the maximum temperature of any monthly maximum temperature)

This weather data package comprises weather data for automatic weather stations situated at 13 sites separated by distances of between 5 and 80 km. The weather stations record temperature and rainfall (in 2010, one weather station was set up so that it also began recording wind speed and direction). The air temperature, rainfall, wind speed and wind direction data are recorded in a data logger housed within the instrument stand. The network program uses a core of 12 sites and aims to quantitatively track long-term shifts in biodiversity and ecological processes in relation to key drivers, including unpredictable rainfall and droughts, fire, feral predators and grazing. A synopsis of related data packages which have been collected as part of the Desert Ecology Plot Network's full program is provided at http://www.ltern.org.au/index.php/ltern-plot-networks/desert-ecology

Given the rising frequency of thermal extremes (heatwaves and cold snaps) due to climate change, comprehending how a plant’s origin affects its thermal tolerance breadth becomes vital. We studied juvenile plants from three biomes: temperate coastal rainforest, desert, and alpine. In controlled settings, plants underwent hot days and cold nights in a factorial design to examine thermal tolerance acclimation. We assessed thermal thresholds (Tcrit-hot and Tcrit-cold) and thermal tolerance breadth (TTB). We hypothesised that: 1) desert species would show the highest heat tolerance, alpine the greatest cold tolerance, with temperate species intermediate; 2) all species would increase heat tolerance post hot days and cold tolerance after cold nights; 3) combined exposure would broaden TTB more than individual conditions, especially in the desert and alpine species. We found that biome responses were minor compared to the responses to the extreme temperature treatments. All plants increased thermal tolerance in response to hot 40°C days (Tcrit-hot increased by ~3.5°C) but there was minimal change in Tcrit-cold in response to the cold -2°C nights. In contrast, when exposed to both hot days and cold nights, on average plants exhibited an antagonistic response in TTB, where cold tolerance decreased and heat tolerance was reduced, and so we did not see the bi-directional expansion we hypothesised. There was, however, considerable variation among species in these responses. As climate change intensifies, plant communities, especially in transitional seasons, will regularly face such temperature swings. Our results shed light on potential plant responses under these extremes, emphasizing the need for deeper species-specific thermal acclimation insights, ultimately guiding conservation efforts. # Acclimation of thermal tolerance in juvenile plants from three biomes is suppressed when extremes co-occur https://doi.org/10.5061/dryad.cz8w9gjbg ## Thermal tolerance data This Excel file contains the data from the paper 'Acclimation of thermal tolerance in juvenile plants from three biomes is suppressed when extremes co-occur' Test Whether the metric was tcrit hot, tcrit cold, or thermal tolerance breadth (TTB) ID Not a true ID, but gives you the date, block, plate a or b, and what test it was Block Replicate group of species from 1-5. Smaller plants were in blocks 2 and 4 sp Species name combined with what treatment it went in Plant_ID ID that tells you the block number, species, and treatment Species Species name Measurement_Day If plants were measured on day 3 or day 5 Biome Which biome: temperate, desert or alpine Treatment The treatment type: warming, cooling, combination or control Warming Either yes or no: e.g. control would be no but heatwave would be yes Cooling Either yes or no: e.g, control would be no, and heatwave would be no PAMID The area of interest recorded on the PAM to get F0 values (not unique and not useful in analysis at this point) Tcrit Derived from tcrit extraction script in R Tmax Derived from tcrit extraction script in R NT Calculated from thermocouple temperature output when an exothermic reaction occurs (release of heat during ice formation) and tells you the time/temp when ice formed TTB Tcrit hot minus tcrit cold gives you the thermal tolerance breadth (TTB) Growth_Form Type of growth form the plants are Delta_Tcrit Tcrit of treatment minus the control treatment Type The treatment combination type: warming, cooling, combination or control NA = failed tcrit or missing data due to error Title: Methods for Assessing Thermal Tolerance in Plants from Different Australian Biomes Summary: This study compared the responses of plants from temperate rainforest, alpine, and desert biomes in Australia to hot days and cold nights using temperature-dependent increases in chlorophyll a fluorescence. For each biome, eight species were selected based on seed availability and family representation. Seeds were obtained from conservation seed banks, sown, and grown under common conditions in glasshouses. Some species were purchased from nurseries. A fully factorial experimental design was used with three biomes, eight species per biome, five replicates, and four temperature treatments (control, hot days, cold nights, and a combination of hot days and cold nights). Experiments were conducted in growth chambers, and plants were exposed to the temperature regimes for five days. Leaf temperatures were monitored using thermocouples. Thermal tolerance assays were performed on days three and five of the experiment using Maxi Pulse Amplitude Modulating (PAM) systems. Leaf discs were placed on Peltier plates and subjected to cooling (-25°C) and heating (65°C) ramps. The critical temperatures during heating (Tcrit-hot) and cooling (Tcrit-cold) were defined as the breakpoint between the slow and fast-rise phases of basal fluorescence.

The maximum temperature of any monthly minimum temperature

Abstract

This data and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Köppen's scheme to classify world climates was devised in 1918 by Dr Wladimir Köppen of the University of Graz in Austria. Over the decades it has achieved wide acceptance amongst climatologists. However, the scheme has also had its share of critics, who have challenged the scheme's validity on a number of grounds. For example, Köppen's rigid boundary criteria often lead to large discrepancies between climatic subdivisions and features of the natural landscape. Furthermore, whilst some of his boundaries have been chosen largely with natural landscape features in mind, other boundaries have been chosen largely with human experience of climatic features in mind. The present paper presents a modification of Köppen's classification that addresses some of the concerns and illustrates this modification with its application to Australia.

A modification of the Köppen classification of world climates has been presented. The extension has been illustrated by its application to Australian climates. Even with the additional complexity, the final classification contains some surprising homogeneity. For example, there is a common classification between the coastal areas of both southern Victoria and southern New South Wales. There is also the identical classification of western and eastern Tasmania. This arises due to the classification not identifying every climate variation because a compromise has to be reached between sacrificing either detail or simplicity. For example, regions with only a slight annual cycle in rainfall distribution do not have that variation so specified in the classification. Similarly, regions with only slightly different mean annual temperatures are sometimes classified as being of the same climate.

The classification descriptions need to be concise, for ease of reference. As a result, the descriptions are not always complete. For example, the word "hot" is used in reference to those deserts with the highest annual average temperatures, even though winter nights, even in hot desert climates, can't realistically be described as "hot".

In conclusion, the authors see the classification assisting in the selection of new station networks. There is also the potential for undertaking subsequent studies that examine climate change in the terms of shifts in climate classification boundaries by using data from different historical periods, and by using different characteristics to define climate type such as "inter-annual variability of precipitation". In the future, it is planned to prepare climate classification maps on a global scale, as well as on a regional-Australian scale.

TABLE 1

Köppen's original scheme New scheme

Tropical group Divided into equatorial & tropical groups

Monsoon subdivision Becomes rainforest (monsoonal) subdivision

Dry group Divided into desert & grassland groups

Summer/winter drought subdivisions Now requires 30+mm in wettest month

Temperate group Divided into subtropical & temperate groups

Cold-snowy-forest group Cold group

Dry summer/winter subdivisions Moderately dry winter subdivision added

Polar group Maritime subdivision added

Frequent fog subdivision Applies now only to the desert group

Frequent fog subdivision Becomes high humidity subdivision

High-sun dry season subdivision Absorbed into other subdivisions

Autumn rainfall max subdivision Absorbed into other subdivisions

Other minor subdivisions Absorbed into other subdivisions

This dataset has been provided to the BA Programme for use within the programme only. For copyright information go to http://www.bom.gov.au/other/copyright.shtml. Information on how to request a copy of data can be found at www.bom.gov.au/climate/data.

Dataset History

Trewartha (1943) notes that Köppen's classification has been criticised from "various points of view" (Thornthwaite 1931, Jones 1932, Ackerman, 1941). Rigid boundary criteria often lead to large discrepancies between climatic subdivisions and features of the natural landscape. Some boundaries have been chosen largely with natural landscape features in mind (for example, "rainforest"), whilst other boundaries have been chosen largely with human experience of climatic features in mind (for example, "monsoon"). Trewartha (1943) acknowledges the validity of these criticisms when he writes that "climatic boundaries, as seen on a map, even when precisely defined, are neither better nor worse than the human judgements that selected them, and the wisdom of those selections is always open to debate". He emphasises, however, that such boundaries are always subject to change "with revision of boundary conditions ... (and that) ... such revisions have been made by Köppen himself and by other climatologists as well".

Nevertheless, the telling evidence that the Köppen classification's merits outweigh its deficiencies lies in its wide acceptance. Trewartha (1943) observes that "its individual climatic formulas are almost a common language among climatologists and geographers throughout the world ... (and that) ... its basic principles have been ... widely copied (even) by those who have insisted upon making their own empirical classifications". Trewartha's (1943) comments are as relevant today as they were half a century ago (see, for example, Müller (1982); Löhmann et al. (1993)).

For the above reasons, in modifying the Köppen classification (Figures 1 and 2), the authors have chosen to depart only slightly from the original. Nevertheless, the additional division of some of the Köppen climates and some recombining of other Köppen climates may better reflect human experience of significant features. In recognition of this, the following changes, which are also summarised in Table 1, have been adopted in this work:

The former tropical group is now divided into two new groups, an equatorial group and a new tropical group. The equatorial group corresponds to the former tropical group's isothermal subdivision. The new tropical group corresponds to that remaining of the former tropical group. This is done to distinguish strongly between those climates with a significant annual temperature cycle from those climates without one (although this feature is not as marked in the Australian context, as elsewhere in the world). Under this definition some climates, distant from the equator, are classified as equatorial. This is considered acceptable as that characteristic is typical of climates close to the equator. Figure 1 shows that, in Australia, equatorial climates are confined to the Queensland's Cape York Peninsula and the far north of the Northern Territory.

The equatorial and tropical group monsoon subdivisions are re-named as rainforest (monsoonal) subdivisions. This is done because, in these subdivisions, the dry season is so short, and the total rainfall is so great, that the ground remains sufficiently wet throughout the year to support rainforest. Figure 2 shows that, in Australia, rainforest subdivisions are found along parts of the northern part of Queensland's east coast.

The former dry group is now divided into two new groups, a desert group and a grassland group. The new groups correspond to the former subdivisions of the dry group with the same name. This is believed necessary because of the significant differences between the types of vegetation found in deserts and grasslands. That there is a part of central Australia covered by the grassland group of climates (Figure 1) is a consequence of the higher rainfall due to the ranges in that region.

The new desert and grassland winter drought (summer drought) subdivisions now require the additional criterion that there is more than 30 mm in the wettest summer month (winter month) to be so classified. This change is carried out because drought conditions may be said to prevail throughout the year in climates without at least a few relatively wet months. It should be noted that the original set of Köppen climates employed the phrases "winter drought" and "summer drought" to respectively describe climates that are seasonally dry. Figure 2 shows that the summer drought subdivisions are found in the southern half of the country, whilst the winter drought subdivisions are found in the northern half of the country.

The former temperate group is divided into two new groups, a temperate group and a subtropical group. The new subtropical group corresponds to that part of the former temperate group with a mean annual temperature of at least 18°C. The new temperate group corresponds to that part of the former temperate group remaining. This is done because of the significant differences in the vegetation found in areas characterised by the two new groups, and in order that there is continuity in the boundary between the hot and warm desert and grassland climates where they adjoin rainy climates. Figure 1 shows that a large region, covering much of southeast Queensland and some elevated areas further north, is now characterised as subtropical.

For simplicity, the former Köppen cold snowy forest group of climates is re-named as the cold group. Figure 1 shows that this climate is not found on the Australian mainland or in Tasmania.

For the temperate, subtropical, and the cold groups, the distinctly dry winter subdivision requires the additional criterion of no more than 30 mm in the driest winter month to be so classified. In order that there be consistency between the criteria for the distinctly dry winter and the distinctly dry summer subdivisions, this is thought to be a worthwhile change. Figure 2 shows that, whereas that part of Western Australia characterised as subtropical has a distinctly dry summer, much of subtropical southeast