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Gridded Near-Surface Wind Data for Australia 

Ver: 1
Status of Data: completed
Update Frequency: asNeeded
Security Classification: unclassified
Record Last Modified: 2025-12-02
Viewed 558 times
Accessed 157 times
Dataset Created: 2019-08-01
Dataset Published: 2023-11-03
Data can be accessed from the following links:
HTTPPoint-of-truth metadata URLHTTPmean_wind_10m - Blended daily wind speed data (at 10m) for AustraliaHTTPmean_wind_2m - Blended daily wind speed data (at 2m) for AustraliaHTTPro-crate-metadata.json
How to cite this collection:
Zhang, H. & Department of Environment and Science (2017-2023), Q. (2023). Gridded Near-Surface Wind Data for Australia. Version 1. Terrestrial Ecosystem Research Network. Dataset. https://dx.doi.org/10.25901/t7s2-er29 
Gridded near-surface (2 and 10 m) daily average wind datasets for Australia from 1975 to 2018 have been constructed by interpolating observational data collected by the Australian Bureau of Meteorology (BoM). The new datasets span Australia at 0.05 × 0.05° resolution with a daily time step. The datasets were constructed by blending observational data collected at various heights using local surface roughness information. 
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging. 
Purpose
We expect the improved accuracy and availability will assist modellers and other users requiring wind estimates in Australia. 
Lineage
Gridded near-surface (2 and 10 m) daily average wind datasets for Australia have been constructed by interpolating observational data collected by the Australian Bureau of Meteorology (BoM). The new datasets span Australia at 0.05 × 0.05° resolution with a daily time step. They are available as daily values for the period 1 January 1975 to 31 December 2018. The datasets were constructed by blending observational data collected at various heights using local surface roughness information. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Australia.
Temporal Coverage
From 1975-01-01 to 2018-12-31 
Spatial Resolution

Distance of 5000 Meters

Vertical Extent

Between 2 and 10 Meters

Data Quality Assessment Scope
Error detection techniques were used to identify and remove suspect data. Statistical performances of the spatial interpolations were evaluated using a cross-validation procedure, by sequentially applying interpolations after removing the observed weather station data. The accuracy of the new blended 10 m wind datasets were estimated through comparison with the Reanalysis ERA5-Land 10 m wind datasets. 
Zhang H., Jeffrey S. and Carter J. (2022). Improved quality gridded surface wind speed datasets for Australia. Meteorology and Atmospheric Physics, 134 (85)
Data Quality Assessment Outcome
Overall, the blended 10 m wind speed patterns are similar to the ERA5-Land 10 m wind. The new blended 10 m wind datasets outperformed ERA5-Land 10 m wind in terms of spatial correlations and mean absolute errors through validations with BoM 10 m wind weather station data for the period from 1981 to 2020. Average correlation (R2) for blended 10 m wind is 0.68, which is 0.45 for ERA5-Land 10 m wind. The average of the mean absolute error is 1.15 m/s for blended 10 m wind, which is lower than that for ERA5-Land 10 m wind (1.61 m/s). The blending technique substantially improves the spatial correlations for blended 2 m wind speed. 
ANZSRC - FOR
Meteorology
GCMD Sciences
ATMOSPHERE - WIND SPEED
Horizontal Resolution
1 km - < 10 km or approximately .01 degree - < .09 degree
Parameters
wind speed
Temporal Resolution
Daily Climatology
Topic
climatologyMeteorologyAtmosphere
Author
Zhang, Hong
Department of Environment and Science (2017-2023), Queensland Government
Contact Point
Department of Environment and Science (2017-2023), Queensland Government
Zhang, Hong
Publisher
Terrestrial Ecosystem Research Network
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Creative Commons Attribution 4.0 International Licence
https://creativecommons.org/licenses/by/4.0/
Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}. 
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