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Great Western Woodlands Flux Data Release 2023_v2 

Ver: 2023_v2
Status of Data: completed
Update Frequency: biannually
Security Classification: unclassified
Record Last Modified: 2025-12-02
Viewed 50 times
Accessed 4 times
Dataset Created: 2023-10-06
Dataset Published: 2024-01-04
Data can be accessed from the following links:
HTTPPoint-of-truth metadata URLOPeNDAPNetCDF files (2023_v2)HTTPro-crate-metadata.json
How to cite this collection:
Macfarlane, C., Prober, S. & Wiehl, G. (2024). Great Western Woodlands Flux Data Release 2023_v2. Version 2023_v2. Terrestrial Ecosystem Research Network. Dataset. https://dx.doi.org/10.25901/y735-bp31 
This release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer using eddy covariance techniques. Data were processed using PyFluxPro (v3.4.15) as described by Isaac et al. (2017). PyFluxPro produces a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER).

Great Western Woodlands (GWW) comprise a 16 million ha mosaic of temperate woodland, shrubland and mallee vegetation in south-west Western Australia. The region has remained relatively intact since European settlement, owing to the variable rainfall and lack of readily accessible groundwater. The woodland component is globally unique in that nowhere else do woodlands occur at as little as 220 mm mean annual rainfall. Further, other temperate woodlands around the world have typically become highly fragmented and degraded through agricultural use. Great Western Woodlands Site was established in 2012 in the Credo Conservation Reserve. The site is in semi-arid woodland and was operated as a pastoral lease from 1907 to 2007. The core 1 ha plot is characterised by Eucalyptus salmonophloia (salmon gum), with Eucalyptus salubris and Eucalyptus clelandii dominating other research plots. The flux station is located in salmon gum woodland. 
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.
Great Western Woodlands Site was established in 2012 and is managed by CSIRO Land and Water and funded by TERN and the WA Department of Environment and Conservation. The flux station is part of the Australia OzFlux Network and contributes to the international FLUXNET Network. 
Purpose
The flux station and site work towards building a process-based understanding of semi-arid woodlands to inform management and climate adaptation in Great Western Woodlands and climate-resilient restoration in the adjacent WA wheatbelt. 
Lineage
All flux raw data is subject to the quality control process OzFlux QA/QC to generate data from L1 to L6. Levels 3 to 6 are available for re-use. Datasets contain Quality Controls flags which will indicate when data quality is poor and has been filled from alternative sources. For more details, refer to Isaac et al. (2017). 
Method DocumentationIsaac P., Cleverly J., McHugh I., van Gorsel E., Ewenz C. and Beringer, J. (2017). OzFlux data: network integration from collection to curation, Biogeosciences, 14: 2903-2928PyFluxPro
Procedure StepsData not provided.
Located in Credo Conservation Reserve, Western Australia
Temporal Coverage
From 2013-01-01 to 2023-07-01 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

Data Quality Assessment Scope
Processing levels

Under each of the data release directories, the netcdf files are organised by processing levels (L3, L4, L5 and L6):
  • L3 (Level 3) processing applies a range of quality assurance/quality control measures (QA/QC) to the L1 data. The variable names are mapped to the standard variable names (CF 1.8) as part of this step. The L3 netCDF file is then the starting point for all further processing stages.
  • L4 (Level 4) processing fills gaps in the radiation, meteorological and soil quantities utilising AWS (automated weather station), ACCESS-G (Australian Community Climate and Earth-System Simulator) and ERA5 (the fifth generation ECMWF atmospheric reanalysis of the global climate).
  • L5 (Level 5) processing fills gaps in the flux data employing the artificial neural network SOLO (self-organising linear output map).
  • L6 (Level 6) processing partitions the gap-filled NEE into GPP and ER.
Each processing level has two sub-folders ‘default’ and ‘site_pi’:
  • default: contains files processed using PyFluxPro
  • site_pi: contains files processed by the principal investigators of the site.
If the data quality is poor, the data is filled from alternative sources. Filled data can be identified by the Quality Controls flags in the dataset. Quality control checks include:
  • range checks for plausible limits
  • spike detection
  • dependency on other variables
  • manual rejection of date ranges
Specific checks applied to the sonic and IRGA data include rejection of points based on the sonic and IRGA diagnostic values and on either automatic gain control (AGC) or CO2 and H2O signal strength, depending upon the configuration of the IRGA.

Great Western Woodlands Flux Tower was established in 2013, and is currently active. The processed data release is currently ongoing, biannually. 
Isaac P., Cleverly J., McHugh I., van Gorsel E., Ewenz C. and Beringer, J. (2017). OzFlux data: network integration from collection to curation, Biogeosciences, 14: 2903-2928
Data Quality Assessment Outcome
Data not provided. 
ANZSRC - FOR
Atmospheric sciences
Climate change impacts and adaptation
Ecosystem function
Environmental management
Soil sciences
GCMD Sciences
ATMOSPHERE - AIR TEMPERATURE
ATMOSPHERE - ATMOSPHERIC CARBON DIOXIDE
ATMOSPHERE - ATMOSPHERIC PRESSURE MEASUREMENTS
ATMOSPHERE - EVAPOTRANSPIRATION
ATMOSPHERE - HEAT FLUX
ATMOSPHERE - HUMIDITY
ATMOSPHERE - INCOMING SOLAR RADIATION
ATMOSPHERE - LONGWAVE RADIATION
ATMOSPHERE - PRECIPITATION AMOUNT
ATMOSPHERE - SHORTWAVE RADIATION
ATMOSPHERE - TRACE GASES/TRACE SPECIES
ATMOSPHERE - TURBULENCE
ATMOSPHERE - WIND DIRECTION
ATMOSPHERE - WIND SPEED
BIOSPHERE - PHOTOSYNTHETICALLY ACTIVE RADIATION
BIOSPHERE - TERRESTRIAL ECOSYSTEMS
LAND SURFACE - LAND PRODUCTIVITY
LAND SURFACE - SOIL MOISTURE/WATER CONTENT
LAND SURFACE - SOIL TEMPERATURE
SOLID EARTH - BIOGEOCHEMICAL PROCESSES
Horizontal Resolution
Point Resolution
Instruments
Campbell Scientific CS616
Campbell Scientific CSAT3
Campbell Scientific TCAV Averaging Soil Thermocouple Probe
HyQuest Solutions CS700
Kipp&Zonen CNR1
Kipp&Zonen NR Lite2
LI-COR LI-7500
Middleton CN3
Parameters
air temperature
downward heat flux at ground level in soil
ecosystem respiration
gross primary productivity
lateral component of wind speed
longitudinal component of wind speed
magnitude of surface downward stress
mass concentration of water vapor in air
mole fraction of carbon dioxide in air
mole fraction of water vapor in air
Monin-Obukhov length
net ecosystem exchange
net ecosystem productivity
relative humidity
soil temperature
specific humidity
specific humidity saturation deficit in air
surface air pressure
surface downwelling longwave flux in air
surface downwelling shortwave flux in air
surface friction velocity
surface net downward radiative flux
surface upward flux of available energy
surface upward latent heat flux
surface upward mole flux of carbon dioxide
surface upward sensible heat flux
surface upwelling longwave flux in air
surface upwelling shortwave flux in air
thickness of rainfall amount
vertical wind
volume fraction of condensed water in soil
water evapotranspiration flux
water vapor partial pressure in air
water vapor saturation deficit in air
wind from direction
wind speed
Platforms
Great Western Woodlands Flux Station
Temporal Resolution
1 minute - < 1 hour
Topic
climatologyMeteorologyAtmosphere
User Defined
AU-GWW
Eddy Covariance
sparse eucalypt woodland
Author
Macfarlane, Craig Kenneth
Prober, Suzanne Mary
Co-Author
Wiehl, Georg
Contact Point
Macfarlane, Craig Kenneth
Prober, Suzanne Mary
Publisher
Terrestrial Ecosystem Research Network
Beringer J., Hutley L. B., McHugh I., Arndt S. K., Campbell D., Cleugh H. A., Cleverly J., Resco de Dios V., Eamus D., Evans B., Ewenz C., Grace P., Griebel A., Haverd V., Hinko-Najera N., Huete A., Isaac P., Kanniah K., Leuning R., Liddell M. J., Macfarlane C., Meyer W., Moore C., Pendall E., Phillips A., Phillips R. L., Prober S. M., Restrepo-Coupe N., Rutledge S., Schroder I., Silberstein R., Southall P., Yee M. S., Tapper N. J., van Gorsel E., Vote C., Walker J. and Wardlaw T. (2016). An introduction to the Australian and New Zealand flux tower network - OzFlux, Biogeosciences, 13: 5895-5916
Supplemental Information
Data not provided. 
Resource Specific Usage
Data not provided. 
Environment Description
File naming convention

The NetCDF files follow the naming convention below:

SiteName_ProcessingLevel_FromDate_ToDate_Type.nc
  • SiteName: short name of the site
  • ProcessingLevel: file processing level (L3, L4, L5, L6)
  • FromDate: temporal interval (start), YYYYMMDD
  • ToDate: temporal interval (end), YYYYMMDD
  • Type (Level 6 only): Summary, Monthly, Daily, Cumulative, Annual
For the NetCDF files at Level 6 (L6), there are several additional 'aggregated' files. For example:
  • Summary: This file is a summary of the L6 data for daily, monthly, annual and cumulative data. The files Monthly to Annual below are combined together in one file.
  • Monthly: This file shows L6 monthly averages of the respective variables, e.g. AH, Fc, NEE, etc.
  • Daily: same as Monthly but with daily averages.
  • Cumulative: File showing cumulative values for ecosystem respiration, evapo-transpiration, gross primary product, net ecosystem exchange and production as well as precipitation.
  • Annual: same as Monthly but with annual averages.
 
By Parent record
Great Western Woodlands Flux Data Collection
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Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting 
Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}. 

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