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.

SILO is a Queensland Government database containing continuous daily climate data for Australia from 1889 to present, in a number of ready-to-use formats, suitable for modelling and research applications. The SILO database contains two major classes of data: point (station) time series and spatial grids, both based on observed data from the Bureau of Meteorology ADAM (Australian Data Archive for Meteorology) database. For point data, interpolated or derived values are used where observations are missing. Gridded data are spatially interpolated from observations.

SILO is a database of Australian climate data from 1889 to the present. It provides continuous, daily time-step data products in ready-to-use formats for research and operational applications. SILO's gridded datasets (in NetCDF and GeoTiff formats) are hosted on AWS Public Data. Point data (at both station and grid cell locations) are available from the SILO website. Incremental update files for mirroring point datasets at station locations are also available on AWS Public Data.

Daily (1981-2019), monthly (1981-2019) and monthly mean (1981-2010) surfaces of precipitation across Victoria at a spatial resolution of 9 seconds (approx. 250 m). 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) using a DEM smoothed (Gaussian filter with a standard deviation of 10 and a search radius of 0.0825°, optimised using cross validation) to account for the lack of strong correlation between elevation and precipitation at short distances (Hutchinson 1998; Sharples et al. 2005). All data was interpolated using ANUSPLIN 4.4 (Hutchinson & Xu 2013). 4. Monthly surfaces were interpolated directly from monthly station records using the methods described in step 3. 5. Daily anomalies were calculated as a proportion of monthly precipitation, and interpolated with full spline dependence on latitude and longitude. 6. Interpolated anomalies (constrained to values between 0 and 1) were multiplied by monthly precipitation to obtain the final daily surfaces. 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. C) Model performance: Accuracy assessment was conducted with leave-one-out cross validation. Mean monthly precipitation: RMSE = 7.65 mm (14.0% relative to mean) Monthly precipitation: RMSE = 13.12 mm (24.7% relative to mean) Daily precipitation: RMSE = 2.21 mm (26.3% relative to mean)

SILO (Scientific Information for Land Owners) is a database of Australian climate data from 1889 (current to yesterday). It provides daily datasets for a range of climate variables in ready-to-use formats suitable for research and climate applications. SILO products provide national coverage with interpolated infills for missing data, which allows you to focus on your research or model development without the burden of data preparation.
The SILO climate API (Application Programming Interface) allows you to query point datasets, as well as a range of metadata, in real time.
Note: An API key is required to use this API. Please visit the SILO website to obtain your API key.

Abstract

The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.

This dataset includes the following parameters clipped to BA_SYD extent.

1) Mean annual BAWAP (Bureau of Meteorology Australian Water Availability Project) rainfall of year 1981 - 2013

2) Mean annual penman PET (potential evapotranspiration) of year 1981 - 2013

3) Mean annual runoff using the 'Budyko-framework' implementation of Choudhury

Dataset History

Lineage is as per the BA All mean climate data for Australia except the national data has been clipped to BA SYD extent.

The mean annual rainfall data is created from monthly BAWAP grids which is created from daily BILO rainfall.

Jones, D. A., W. Wang and R. Fawcett (2009). "High-quality spatial climate data-sets for Australia." Australian Meteorological and Oceanographic Journal 58(4): 233-248.

The Mean annual penman PET is created as per the Donohue et al (2010) paper using the fully physically based Penman formulation of potential evapotranspiration, exept that daily wind speed grids used here were generated with a spline (i.e., ANUSPLIN) as per McVicar et al (2008), not the TIN as per Donohue et al (2010). For comprehensive details regarding the generation of some of these datasets (i.e., net radiation, Rn) see the details provided in Donohue et al (2009).

Donohue, R.J., McVicar, T.R. and Roderick, M.L. (2010) Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. Journal of Hydrology. 386(1-4), 186-197. doi:10.1016/j.jhydrol.2010.03.020

Donohue, R.J., McVicar, T.R. and Roderick, M.L., (2009) Generating Australian potential evaporation data suitable for assessing the dynamics in evaporative demand within a changing climate. CSIRO: Water for a Healthy Country Flagship, pp 43. http://www.clw.csiro.au/publications/waterforahealthycountry/2009/wfhc-evaporative-demand-dynamics.pdf

McVicar, T.R., Van Niel, T.G., Li, L.T., Roderick, M.L., Rayner, D.P., Ricciardulli, L. and Donohue, R.J. (2008) Wind speed climatology and trends for Australia, 1975-2006: Capturing the stilling phenomenon and comparison with near-surface reanalysis output. Geophysical Research Letters. 35, L20403, doi:10.1029/2008GL035627

The Mean annual runoff was created as per the Donohue et al (2010) paper. The data represent the runoff expected from the steady-state 'Budyko curve' longterm mean annual water-energy limit approach using BAWAP precipitation and the Penman potential ET described above.

Choudhury BJ (1999) Evaluation of an empirical equation for annual evaporation using field observations and results from a biophysical model. Journal of Hydrology 216, 99-110.

Donohue, R.J., McVicar, T.R. and Roderick, M.L. (2010) Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. Journal of Hydrology. 386(1-4), 186-197. doi:10.1016/j.jhydrol.2010.03.020

Donohue, R.J., McVicar, T.R. and Roderick, M.L., (2009) Generating Australian potential evaporation data suitable for assessing the dynamics in evaporative demand within a changing climate. CSIRO: Water for a Healthy Country Flagship, pp 43. http://www.clw.csiro.au/publications/waterforahealthycountry/2009/wfhc-evaporative-demand-dynamics.pdf

McVicar, T.R., Van Niel, T.G., Li, L.T., Roderick, M.L., Rayner, D.P., Ricciardulli, L. and Donohue, R.J. (2008) Wind speed climatology and trends for Australia, 1975-2006: Capturing the stilling phenomenon and comparison with near-surface reanalysis output. Geophysical Research Letters. 35, L20403, doi:10.1029/2008GL035627

Dataset Citation

Bioregional Assessment Programme (2014) Mean annual climate data clipped to BA_SYD extent. Bioregional Assessment Derived Dataset. Viewed 18 June 2018, http://data.bioregionalassessments.gov.au/dataset/a8393a45-5e86-431b-b504-c0b2953296f4.

Dataset Ancestors

• Derived From BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012

• Derived From Mean Annual Climate Data of Australia 1981 to 2012

Abstract

The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets provided by the Bureau of Meteorology. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.

This dataset includes the following parameters for the whole of Australia:

1) Mean annual BAWAP (Bureau of Meteorology Australian Water Availability Project) rainfall of year 1981 - 2013

2) Mean annual penman PET (potential evapotranspiration) of year 1981 - 2013

3) Mean annual runoff using the 'Budyko-framework' implementation of Choudhury

Purpose

Provide long term (last 30 years) average annual grids of rainfall, penman PET and runoff for whole Australia.

Dataset History

The mean annual rainfall data is created from monthly BAWAP grids (Dataset ID: 7aaf0621-a0e5-4b01-9333-53ebcb1f1c14) which is created from daily BILO rainfall.

Jones, D. A., W. Wang and R. Fawcett (2009). "High-quality spatial climate data-sets for Australia." Australian Meteorological and Oceanographic Journal 58(4): 233-248.

The Mean annual penman PET is created by Randall Donohue, as per the Donohue et al (2010) paper using the fully physically based Penman formulation of potential evapotranspiration, except that daily wind speed grids used here were generated with a spline (i.e., ANUSPLIN) as per McVicar et al (2008), not the TIN as per Donohue et al (2010). For comprehensive details regarding the generation of some of these datasets (i.e., net radiation, Rn) see the details provided in Donohue et al (2009).

Donohue, R.J., McVicar, T.R. and Roderick, M.L. (2010) Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. Journal of Hydrology. 386(1-4), 186-197. doi:10.1016/j.jhydrol.2010.03.020

Donohue, R.J., McVicar, T.R. and Roderick, M.L., (2009) Generating Australian potential evaporation data suitable for assessing the dynamics in evaporative demand within a changing climate. CSIRO: Water for a Healthy Country Flagship, pp 43. http://www.clw.csiro.au/publications/waterforahealthycountry/2009/wfhc-evaporative-demand-dynamics.pdf

McVicar, T.R., Van Niel, T.G., Li, L.T., Roderick, M.L., Rayner, D.P., Ricciardulli, L. and Donohue, R.J. (2008) Wind speed climatology and trends for Australia, 1975-2006: Capturing the stilling phenomenon and comparison with near-surface reanalysis output. Geophysical Research Letters. 35, L20403, doi:10.1029/2008GL035627

The Mean annual runoff was created by Randall Donohue, as per the Donohue et al (2010) paper. The data represent the runoff expected from the steady-state 'Budyko curve' longterm mean annual water-energy limit approach using BAWAP precipitation and the Penman potential ET described above.

Choudhury BJ (1999) Evaluation of an empirical equation for annual evaporation using field observations and results from a biophysical model. Journal of Hydrology 216, 99-110.

Donohue, R.J., McVicar, T.R. and Roderick, M.L. (2010) Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. Journal of Hydrology. 386(1-4), 186-197. doi:10.1016/j.jhydrol.2010.03.020

Donohue, R.J., McVicar, T.R. and Roderick, M.L., (2009) Generating Australian potential evaporation data suitable for assessing the dynamics in evaporative demand within a changing climate. CSIRO: Water for a Healthy Country Flagship, pp 43. http://www.clw.csiro.au/publications/waterforahealthycountry/2009/wfhc-evaporative-demand-dynamics.pdf

McVicar, T.R., Van Niel, T.G., Li, L.T., Roderick, M.L., Rayner, D.P., Ricciardulli, L. and Donohue, R.J. (2008) Wind speed climatology and trends for Australia, 1975-2006: Capturing the stilling phenomenon and comparison with near-surface reanalysis output. Geophysical Research Letters. 35, L20403, doi:10.1029/2008GL035627

Dataset Citation

Bioregional Assessment Programme (2014) Mean Annual Climate Data of Australia 1981 to 2012. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/02418c67-f8bb-48a8-88a3-2a5c6b485f78.

Dataset Ancestors

• Derived From BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012

(From http://www.worldclim.org/methods) - For a complete description, see:

Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.

The data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.

The WorldClim interpolated climate layers were made using: * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others. * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km) * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.

Abstract

This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. The metadata was not provided by the data supplier and has been compiled by the programme based on known details.

This dataset contains long-term monthly rainfall records for the Bureau of Meteorology Harrisville rainfall station in southeast Queensland. See file 'IDCJAC0001_040094_Note.txt' stored with the dataset for details of data.

Dataset History

This dataset contains long-term monthly rainfall records for the Bureau of Meteorology Harrisville rainfall station in southeast Queensland. The dataset was downloaded from the Bureau of Meteorology climate data online webpage. http://www.bom.gov.au/climate/data/

Dataset Citation

Bureau of Meteorology (2016) Monthly rainfall climate data - Harrisville Mary Street. Bioregional Assessment Source Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/d77e55e6-57b7-48e0-84fb-e7b6d3ae2674.

Abstract

This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. Metadata was not provided and has been compiled by the Bioregional Assessment Programme based on the known details at the time of acquisition.

The BILO gridded data set contains daily fields of selected meteorological variables at 0.05 degrees resolution for the whole Australian continent, including Tasmania. It was obtained by CSIRO for use in the Australian Water Availability Project. In addition to daily data fields, some aggregates at monthly and annual intervals have been created.

The variable is daily rainfall. Current data is updated daily by automatic download from the BoM website. Periodic updates (approximately every 6 months) of the dataset include new data and reprocessed data in immediately preceding years. These different revisions are distinguished by an element in the file names "bYYMM" which gives the last two digits of the year and the two digit month corresponding to the revision delivery date. These data represent the snapshot of current data as at 14/10/2013.

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

The data are a snapshot of the climate dataset known as BILO which represents the data as at 14/10/2013. CSIRO maintain a copy of the data as licenced though the Australian Water Availability Project. The BoM version is constantly updated and revised when new data are obtained, when errors in data are identified and when interpolation routines are revised. Therefore there may be difference in the values of some grid cells in the current BoM data compared to this snapshot held by CSIRO. The current BoM archive for these data are listed in the URLs below.

Data provided by BoM on disk or directly downloaded from BoM website.

http://www.bom.gov.au/cgi-bin/silo/reg/brs/rarchives_awa

.cgi?state=nat&period=daily&data_type=totals&format_type=grid

http://www.bom.gov.au/cgi-bin/silo/reg/brs/tarchives_awa

.cgi?state=nat&period=daily&data_type=maxave&format_type=grid

http://www.bom.gov.au/cgi-bin/silo/reg/brs/tarchives_awa

.cgi?state=nat&period=daily&data_type=minave&format_type=grid

http://www.bom.gov.au/cgi-bin/silo/reg/brs/sarchives_awa.

cgi?state=nat&period=daily&data_type=solarave&format_type=grid

Processing Steps

Data provided by BoM in Arc/Info ASCII raster format. Reformatted to binary flt and NetCDF.

Dataset Citation

Bureau of Meteorology (2013) BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/7aaf0621-a0e5-4b01-9333-53ebcb1f1c14.

NOTE - to access these data, please contact the AADC. The data can only be made available on request.

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).

Climate Data Online offers temperature, rainfall and solar exposure values, per day, and per month for each station, for all years that a Station has been operating and measuring that variable. …Show full descriptionClimate Data Online offers temperature, rainfall and solar exposure values, per day, and per month for each station, for all years that a Station has been operating and measuring that variable. Data is from both closed and open stations. Data timespans vary across stations. The earliest data is for Parramatta, commencing 1832. Data values are typically incorporated into CDO within 24 hours of the value being recorded, but QC of the data can take some time. The data's QC-status is indicated by the font (colour and italics). Rainfall: Daily rainfall Observations are nominally made at 9 am local clock time, and record the total for the previous 24 hours. Rainfall includes all forms of precipitation that reach the ground, such as rain, drizzle, hail and snow. For more information, see: [ About daily rainfall data: http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0009.shtml ] and ["About rain data: http://www.bom.gov.au/climate/cdo/about/about-rain-data.shtml ] and [ About measuring rain: http://www.bom.gov.au/climate/cdo/about/rain-measure.shtml ]. The Monthly rainfall data is the total of all available Daily rainfall for the month. Rainfall includes all forms of precipitation that reach the ground, such as rain, drizzle, hail and snow. [ More information about monthly rainfall data: http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0001.shtml ]. More information about Temperature measurements : [http://www.bom.gov.au/climate/cdo/about/about-airtemp-data.shtml ]. Temperature (Daily maximum or minimum): The Daily minimum or maximum air temperature is nominally recorded at 9 am local clock time. The daily maximum air temperature is the highest temperature for the 24 hours leading up to the observation, and is recorded as the maximum temperature for the previous day. The daily minimum air temperature is the lowest temperature for the 24 hours leading up to the observation, and is recorded as the minimum temperature for the day on which the observation was made. Temperature data prior to 1910 should be used with extreme caution as many stations prior to that date used non-standard shelters. [See: http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0011.shtml (minT) and http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0010.shtml (maxT) ] Temperature (Mean minimum or maximum, per month) : The Monthly mean minimum (or maximum) temperature is the average of all available daily minima (or maxima) for the month. For detail of daily Temperature, see above. [ For more detail on Mean minimum or maximum, per month, see : http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0002.shtml ] Temperature (Lowest or Highest per month, for each month) : The Monthly highest (or Lowest) temperature is the highest (or lowest) of all available daily maxima (or minima) for the month. For detail of daily Temperature, see above. [ For more details, see: http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0006.shtml ] Temperature (Lowest Maximum or Highest Minimum temperature per month, for each month) : The Monthly lowest maximum (or highest minimum) temperature is the lowest (or highest) of all available daily maxima (or minima) for the month. For detail of daily Temperature, see above. Solar Exposure (Daily): The Daily global solar exposure (per station) is the total solar energy for a day falling on a horizontal surface. It is measured from midnight to midnight. The values are usually highest in clear sun conditions during the summer and lowest during winter or very cloudy days. Units of Measurements are MJ/m2. The Monthly mean daily global solar exposure is the average of all available daily Solar Exposure for the month. For more details about the Daily Solar Exposure product, see: [ http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0016.shtml ]. Info about solar exposure: [ http://www.bom.gov.au/climate/austmaps/solar-radiation-glossary.shtml#globalexposure ; For more details about the Monthly Sol.Exp product, see: [ http://www.bom.gov.au/climate/cdo/about/about-IDCJAC0003.shtml ].

For each station, an extended list of climate statistics is provided. Data includes various statitics related to air temperature , dew-point temperature , wet-bulb temperature , ground temperature …Show full descriptionFor each station, an extended list of climate statistics is provided. Data includes various statitics related to air temperature , dew-point temperature , wet-bulb temperature , ground temperature , rainfall , wind , sunshine hours , solar exposure , cloud cover , evaporation and relative humidity. Data timespans vary depending on each site's commencement, and when that data parameter was first collected at the site. Data covers all years that a site has been measuring that data parameter. The earliest commencement date of any sites is 1834 Parramatta, NSW). The dataset includes over 1000 sites. Monthly statistics are only included if there are more than 10 years of suitable data. Sites have been included only if a minimum of 10 years of temperature data are available for the site. Thus, statistics for more than 15,000 'rainfall-only' stations are not currently available on this web site, but may be obtained by contacting the Bureau. The sites cover Australasia (including outer islands and 4 in Antarctica). Site locations can be viewed on a map, at [ http://www.bom.gov.au/climate/data/index.shtml?bookmark=200 ]. Locations are also listed [ http://www.bom.gov.au/climate/averages/tables/ca_site_file_names.shtml ] by State/Territory, and then place name. Both the map and list provide access to a webpage offering the climate statistics for that location (for the 'main' statistics, or for 'all' statistics; and relative to a user-selected period (3 decades, or all years).] Statistics include highest/lowest or mean of monthly values, applied against all years of data, or against a user-selected 30-year subset of the data. Other statistics for a number of elements include: maximum, minimum and ground surface temperatures; rainfall, including extremes and days of rain above 1mm, 10mm, and 25mm; other daily elements including sunshine and evaporation where available; and temperatures, humidity, wind and cloud (nominally) at 9am and 3pm. Explanations of each variable can be found by clicking on the first column of each row in the statistics tables. Note: Many statistics are updated quarterly and recent weather events may not be represented in the statistics below. For more current information on recent extreme values, please refer to the corresponding 'Daily rainfall', 'Maximum temperature' and 'Minimum temperature' data tables for the site, in CDO. (Links to these are provided at the top of the each Site's Climate Statistics webpage; or see See 'SupplementalInformation' section of this record, for details). The top of each Climate Stats webpage also provides a link to the data (for the timespan that the user has selected); as well as to details of the site (via "Map")

The fundamental input data of work undertaken by Water Modelling Team is climate data in the form of daily rainfall and potential evapotranspiration. This data is input to water models of varying types, purposes, and complexity. The water models transform this input data to produce a range of water related modelled data.

The stochastic climate data and palaeo stochastic climate data include 10,000 replicates of 130-yr daily data sets of rainfall and potential evapotranspiration generated using observed data sets without and with combined palaeo climate data. This work has been undertaken by researchers at the University of Newcastle and used in modelling for Greater Sydney Water Strategy.

Stochastic Climate data and palaeo stochastic climate data are available to download for Greater Sydney region from the Related Datasets section below.

Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

Using the Climpact software , we have calculated the full set of climate indices for the Australian Gridded Climate Data (AGCD) v1.0.0 at four spatial resolutions: 1x1 deg, 0.5x0.5 deg, 0.25x0.25 deg, and the original 0.05x0.05 deg grid. Threshold indices are based on the reference period 1971-2000.

Filenames are organized as: {climate index}_{temporal resolution}_agcd_historical_{spatial resolution}_{time period available}

Possible temporal resolution values are:

• MON for monthly data
• ANN for annual data

Possible spatial resolution values are:

• r005 for 0.05x0.05 degree resolution
• r025 for 0.25x0.25 degree resolution
• r050 for 0.5x0.5 degree resolution
• r1 for 1x1 degree resolution

We used bilinear interpolation to interpolate the daily AGCD tmin and tmax files to the coarser resolutions, and first-order conservative remapping to interpolate the daily precipitation files to a coarser resolution. Interpolation was completed using CDO prior to running Climpact.

More information about the AGCD dataset can be found at: https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f1801_8183_3094_1341

More information about Climpact and the climate indices can be found at: https://climpact-sci.org/

This dataset provides precipitation and temperature data for the 207 subcatchments in the 5 major river basins of Afghanistan. It includes daily time series of precipitation, maximum temperature and minimum temperature for the period of 2001 to 2020. Lineage: These data were generated from gauge observations. Data from 169 weather stations across Afghanistan were obtained from the Surface Water Resources Department of Afghanistan National Water Affairs Regulation Authority. Gauge data were interpolated to 207 subcatchment using Thiessen Polygons method.

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 selection of 9sec gridded National climate change variables for biodiversity modelling. This collection represents 30-year averages centred on each of 1990, 2050, 2070, 2090. Projected future climates were generated by applying within-model changes for two circulation model outputs: GFDL and ACCESS1.0; and for two representative concentration pathways (RCP 4.5, 8.5), calculated at the native general circulation model grid resolution to these current surfaces, using ANUCLIM 6.1 prior to radiative adjustment. That the maximum temperature variables have been adjusted for topographic slope/aspect and shading effects. A short methods summary is provided in the file 9sClimateMethodsSummary.pdf for further information, including a nomenclature for files. The selected climate variables provided in this collection are: TNM - mean annual minimum temperature TXM - mean annual maximum temperature TXX - mean maximum monthly maximum temperature TXI - mean minimum monthly maximum temperature TNI - mean minimum monthly minimum temperature TNX - mean maximum monthly minimum temperature PTA - Average total annual rainfall PTX - mean maximum monthly rainfall PTI - mean minimum monthly rainfall Other variables (evaporation and water balance, temperature range, and seasonality, etc) are available upon application. The data are provided in ESRI binary float grid format (*.hdr, *.flt), Projection is geographic GDA94. Lineage: Climate surfaces for the present were based on the ANUCLIM 6.1 (Xu and Hutchinson, 2011) 30 year average climate surfaces for Australia (1976-2005), with elevational lapse rate correction applied over the 9s GEODATA digital elevation model (Hutchinson et al , 2008). Radiative correction derived from the same DEM was applied to radiation and maximum temperature before calculation of evaporation, using the CSIRO TerraFormer software. Summary statistics for each variable were then calculated including variables described in Williams et al (2012: Which environmental variables should I use in my biodiversity model? International Journal of Geographic Information Sciences 26(11), 2009-2047. DOI: 10.1080/13658816.2012.698015.). Details are given in the short summary report by Tom Harwood, Noboru Ota, Justin Perry, Kristen Williams, Ian Harman, Simon Ferrier (2014) gridded continental climate variables for Australia: November 2014. CSIRO Land and Water, Canberra. Attached with the collection. Key published references: Reside AE, VanDerWal J, Phillips B, Shoo L, Rosauer D, Anderson BA, Welbergen J, Moritz C, Ferrier S, Harwood TD, Williams KJ, Mackey B, Hugh S and Williams SE (2013) Climate change refugia for terrestrial biodiversity: Defining areas that promote species persistence and ecosystem resilience in the face of global climate change. National Climate Change Adaptation Research Facility, Griffith University, Gold Coast, Qld. Xu T and Hutchinson MF (2013) New developments and applications in the ANUCLIM spatial climatic and bioclimatic modelling package. Environmental Modelling & Software 40(0), 267-279. DOI: http://dx.doi.org/10.1016/j.envsoft.2012.10.003. ACCESS: Bi D, Dix M, Marsland SJ, O’Farrell S, Rashid HA, Uotila P, Hirst AC, Kowalczyk E, Golebiewski M, Sullivan A, Yan H, Hannah N, Franklin C, Sun Z, Vohralik P, Watterson I, Zhou X, Fiedler R, Collier M, Ma Y, Noonan J, Stevens L, Uhe P, Zhu H, Griffies SM, Hill R, Harris C and Puri K (2013) The ACCESS coupled model: description, control climate and evaluation. Australian Meteorological and Oceanographic Journal 63(1), 41-64. GFDL: Dunne JP, John JG, Shevliakova E, Stouffer RJ, Krasting JP, Malyshev SL, Milly PCD, Sentman LT, Adcroft AJ, Cooke W, Dunne KA, Griffies SM, Hallberg RW, Harrison MJ, Levy H, Wittenberg AT, Phillips PJ and Zadeh N (2013) GFDL’s ESM2 global coupled climate–carbon earth system models. Part II: Carbon system formulation and baseline simulation characteristics. Journal of Climate 26(7), 2247-2267. DOI: 10.1175/JCLI-D-12-00150.1.

Context

Predict next-day rain by training classification models on the target variable RainTomorrow.

Content

This dataset contains about 10 years of daily weather observations from many locations across Australia.

RainTomorrow is the target variable to predict. It means -- did it rain the next day, Yes or No? This column is Yes if the rain for that day was 1mm or more.

Source & Acknowledgements

Observations were drawn from numerous weather stations. The daily observations are available from http://www.bom.gov.au/climate/data. An example of latest weather observations in Canberra: http://www.bom.gov.au/climate/dwo/IDCJDW2801.latest.shtml

Definitions adapted from http://www.bom.gov.au/climate/dwo/IDCJDW0000.shtml Data source: http://www.bom.gov.au/climate/dwo/ and http://www.bom.gov.au/climate/data.

Copyright Commonwealth of Australia 2010, Bureau of Meteorology.

Consistent Climate Scenarios (CCS) data are daily climate projections data for Australian locations for years centred on 2030 and 2050. The data have been developed by adjusting SILO historical climate data according to AR4 based climate projections for 2030 and 2050. Since mid-2012, CCS data have been freely provided to registered users through a portal on the Queensland Government's Long Paddock website. CCS data are unique, in that they: - maintain 'weather-like' properties for a range of climate variables (rainfall, evaporation, minimum and maximum temperature, solar radiation and vapour pressure deficit), - are available for more than 4500 climate stations across Australia, or for individual grid points on a 0.05 degree (approximately 5 km) grid across Australia and - are provided in 'ready to use' formats, suitable for input to biophysical models (such as GRASP and APSIM). The development of the CCS Data was funded by the Commonwealth Department of Agriculture, Fisheries and Forestry (DAFF) through its Australia's Farming Future Climate Change Research Program. While the CCS web portal currently provides AR4 based projections data, AR5 based projections data may be included at a future date.