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.

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.

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.

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. …Show full descriptionThe 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.

Daily (1981-2019), monthly (1981-2019) and monthly mean (1981-2010) surfaces of maximum temperature (approx. 1.2 m from ground) across Victoria at a spatial resolution of 9 seconds (approx. 250 m). Surfaces are developed using trivariate splines (latitude, longitude and elevation) with partial dependence upon standardised day time MODIS land surface temperature. Lineage: A) Data modelling: 1. Weather station observations collected by the Australian Bureau of Meteorology were obtained via the SILO patched point dataset (https://data.qld.gov.au/dataset/silo-patched-point-datasets-for-queensland), followed by the removal of all interpolated records. 2. Climate normals representing the 1981-2010 reference period were calculated for each weather station. A regression patching procedure (Hopkinson et al. 2012) was used to correct for biases arising due to differences in record length where possible. 3. Climate normals for each month were interpolated using trivariate splines (latitude, longitude and elevation as spline variables) with partial dependence upon standardised day time MODIS land surface temperature. All models were fit and interpolated using ANUSPLIN 4.4 (Hutchinson & Xu 2013). 4. Daily anomalies were calculated by subtracting daily observations from climate normals and interpolated with full spline dependence upon latitude and longitude 5. Interpolated anomalies were added to interpolated climate normals to obtain the final daily surfaces. 6. Monthly surfaces are calculated as an aggregation of the daily product. B) Spatial data inputs: 1. Fenner School of Environment and Society and Geoscience Australia. 2008. GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3. 2. Paget, MJ, King EA. 2008. MODIS Land data sets for the Australian region. CSIRO Marine and Atmospheric Research. Canberra, Australia. https://doi.org/10.4225/08/585c173339358 C) Model performance (3DS): Accuracy assessment was conducted with leave-one-out cross validation. Mean monthly maximum temperature RMSE = 0.48 °C Daily maximum temperature RMSE = 1.19 °C

Please refer to the linked manuscript for further details.

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.

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.

A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis, produced daily on an operational basis at the Australian Bureau of Meteorology (BoM) using optimal interpolation (OI) on a regional 1/12 degree grid over the Australian region (20N - 70S, 60E - 170W). This Regional Australian Multi-Sensor SST Analysis (RAMSSA) v1.0 system blends satellite SST observations from passive infrared and passive microwave radiometers, with in situ data from ships, Argo floats, XBTs, CTDs, drifting buoys and moorings from the Global Telecommunications System (GTS). SST observations that have experienced recent surface wind speeds less than 6 m/s during the day or less than 2 m/s during night are rejected from the analysis. The processing results in daily foundation SST estimates that are largely free of nocturnal cooling and diurnal warming effects. Sea ice concentrations are supplied by the NOAA/NCEP 12.7 km sea ice analysis. In the absence of observations, the analysis relaxes to the BoM Global Weekly 1 degree OI SST analysis, which relaxes to the Reynolds and Smith (1994) Monthly 1 degree SST climatology for 1961 - 1990.

This dataset contains the precipitation, mean maximum temperature and mean minimum temperature data used in the study Application of Machine Learning to Attribution and Prediction of Seasonal Precipitation and Temperature Trends in Canberra, Australia. This data was originally from the Australian Bureau of Meteorology Climate Data Online (http://www.bom.gov.au/climate/data/index.shtml), but has been updated to have missing values (1% of data) filled using a moving average centred on the year for which the data is missing.

Below is the abstract for the paper.

Southeast Australia is frequently impacted by drought, requiring monitoring of how the various factors influencing drought change over time. Precipitation and temperature trends were analysed for Canberra, Australia, revealing decreasing autumn precipitation. However, annual precipitation remains stable as summer precipitation increased and the other seasons show no trend. Further, mean temperature increases in all seasons. These results suggest that Canberra is increasingly vulnerable to drought. Wavelet analysis suggests that the El-Niño Southern Oscillation (ENSO) influences precipitation and temperature in Canberra, although its impact on precipitation has decreased since the 2000s. Linear regression (LR) and support vector regression (SVR) were applied to attribute climate drivers of annual precipitation and mean maximum temperature (TMax). Important attributes of precipitation include ENSO, the southern annular mode (SAM), Indian Ocean Dipole (DMI) and Tasman Sea SST anomalies. Drivers of TMax included DMI and global warming attributes. The SVR models achieved high correlations of 0.737 and 0.531 on prediction of precipitation and TMax, respectively, outperforming the LR models which obtained correlations of 0.516 and 0.415 for prediction of precipitation and TMax on the testing data. This highlights the importance of continued research utilising machine learning methods for prediction of atmospheric variables and weather pattens on multiple time scales.

This dataset provides values for TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Three datasets containing climate data, compiled in April 2011, have been purchased from the Bureau of Meteorology. These datasets include observations from stations in all Australian States and Territories. Each dataset includes a file which gives details of the stations where observations were made and a file describing the data. AWS Hourly Data contains hourly records of precipitation, air temperature, wet bulb temperature, dew point temperature, relative humidity, vapour pressure, saturated vapour pressure, wind speed, wind direction, maximum wind gust, mean sea level pressure, station level pressure. Each record for each parameter is also flagged to indicate the quality of the value.Synoptic Data contains records of air temperature, dew point temperature, wet bulb temperature, relative humidity, wind speed, wind direction, mean sea level pressure, station level pressure, QNH pressure, vapour pressure and saturated vapour pressure. Each record for each parameter is also flagged to indicate the quality of the value.Daily Rainfall Data contains records precipitation in the 24 hours before 9 am, number of days of rain within the days of accumulation and the accumulated number of days over which the precipitation was measured. Each precipitation record is flagged to indicate the quality of the value.

Global Temperature: Daily Normal: Australia: Keith data was reported at 22.000 Degrees Celsius in 08 Feb 2024. This stayed constant from the previous number of 22.000 Degrees Celsius for 07 Feb 2024. Global Temperature: Daily Normal: Australia: Keith data is updated daily, averaging 22.000 Degrees Celsius from Feb 2024 (Median) to 08 Feb 2024, with 2 observations. The data reached an all-time high of 22.000 Degrees Celsius in 08 Feb 2024 and a record low of 22.000 Degrees Celsius in 08 Feb 2024. Global Temperature: Daily Normal: Australia: Keith data remains active status in CEIC and is reported by Climate Prediction Center. The data is categorized under Global Database’s Australia – Table AU.CPC.GT: Environmental: Global Temperature: Daily Normal.

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.

This dataset is part of the Monash, UEA & UCR time series regression repository. http://tseregression.org/

The goal of this dataset is to predict the total daily rainfall using 24 hours of temperature measurements. This is useful as temperature sensors are much cheaper and easy to maintain as compared to rain gauges. This dataset contains 160,267 time series obtained from a dataset released by the Australian Bureau of Meteorology (BOM).The time series has 3 dimensions, measuring the average hourly temperature, minimum hourly temperature and maximum hourly temperature from 518 weather stations throughout all of Australia.

Please refer to https://data.gov.au/data/dataset/weather-forecasting-verification-data-2015-05-to-2016-04 for more details

This dataset contains time series for monthly precipitation over six sites (Blackheath, Braidwood, Darkes Forest, Goulburn, Lithgow and Moss Vale) in the Sydney Catchment Area (SCA) and monthly mean maximum and mean minimum temperature for three sites (Goulburn, Lithgow, and Moss Vale) in the SCA. This data was used in the study Attribution and Prediction of Precipitation and Temperature Trends within the Sydney Catchment Using Machine Learning. The data was originally from the Australian Bureau of Meteorology Climate Data Online (http://www.bom.gov.au/climate/data/index.shtml), but has been updated to have missing values (8% of data) filled using a moving average centred on the year for which the data is missing.

Below is the abstract for the paper:

Droughts in southeastern Australia can profoundly affect the water supply to Sydney, Australia's largest city. Increasing population, a warming climate, land surface changes, and expanded agricultural use increase water demand and reduce catchment runoff. Studying Sydney's water supply is necessary to manage water resources and lower the risk of severe water shortages. This study aims at understanding Sydney water supply by analysing precipitation and temperature trends across the catchment. A decreasing trend in annual precipitation was found across the Sydney catchment area. Annual precipitation also is significantly less variable, due to fewer years above the 80th percentile. These trends result from significant reductions in precipitation during spring and autumn, especially over the last 20 years. Wavelet analysis is applied to assess how the influence of climate drivers has changed over time. Attribute selection was carried out using linear regression and machine learning techniques including random forests and support vector regression. Drivers of annual precipitation included Niño3.4, SAM, DMI and measures of global warming such as the Tasman Sea Sea Surface temperature anomalies. The support vector regression model with a polynomial kernel achieved correlations of 0.921 and a skill score compared to climatology of 0.721. The linear regression model also performed well with a correlation of 0.815 and skill score of 0.567, highlighting the importance of considering both linear and non-linear methods when developing statistical models. Models were also developed on autumn and winter precipitation but performed worse than annual precipitation on prediction. For example, the best performing model on autumn precipitation, which accounts for approximately one quarter of annual precipitation, achieved an RMSE of 418.036 mm² on the testing data while annual precipitation achieved an RMSE of 613.704 mm². However, the seasonal models provided valuable insight into whether the season would be wet or dry compared to the climatology.

Global Temperature: Mean of Daily Temperature Departures: Australia: Keith data was reported at 0.000 Degrees Celsius in 08 Feb 2024. This stayed constant from the previous number of 0.000 Degrees Celsius for 07 Feb 2024. Global Temperature: Mean of Daily Temperature Departures: Australia: Keith data is updated daily, averaging 0.000 Degrees Celsius from Feb 2024 (Median) to 08 Feb 2024, with 2 observations. The data reached an all-time high of 0.000 Degrees Celsius in 08 Feb 2024 and a record low of 0.000 Degrees Celsius in 08 Feb 2024. Global Temperature: Mean of Daily Temperature Departures: Australia: Keith data remains active status in CEIC and is reported by Climate Prediction Center. The data is categorized under Global Database’s Australia – Table AU.CPC.GT: Environmental: Global Temperature: Mean of Daily Temperature Departures.

In recent years the term 'enhanced greenhouse effect' has become well known in modern society and yet aspects of this possible 'future climate' are poorly understood. The characteristics of the geological record provide a basis to understand this possible future climate through the examination of alternating glacial (cold) and interglacial (warm) stages. Understanding the variability of sea-surface temperature and biological processes in the water column provides insight into general circulation of present and paleo-ocean currents. From core MD032607 the annual mean SST (Tmean) indicates a temperature range of 9oC±0.84oC between Marine Isotope Stage (MIS) 6 to MIS 5, representing the largest sea surface temperature (SST) transition from a glacial to interglacial. The results also suggest that there is more stratification in the water column during interglacial periods as opposed to glacials. Conversely, temperatures gradients are reduced during the Last Glacial Maximum (LGM) and MIS 6 suggesting a well mixed homogenised mixed layer.

Australia Heat Index data was reported at 8.220 Day in 2020. This records a decrease from the previous number of 12.320 Day for 2019. Australia Heat Index data is updated yearly, averaging 4.760 Day from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 12.320 Day in 2019 and a record low of 0.490 Day in 1974. Australia Heat Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Environmental: Climate Risk. Total count of days per year where the daily mean Heat Index rose above 35°C. A Heat Index is a measure of how hot it feels once humidity is factored in with air temperature.;World Bank, Climate Change Knowledge Portal. https://climateknowledgeportal.worldbank.org;;

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).