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Great Western Woodlands Flux Data Release 2023_v2

Parent Dataset: Great Western Woodlands Flux Data Collection
Ver: 2023_v2
Status of Data: completed
Update Frequency: biannually
Security Classification: unclassified
Viewed: 0
Accessed: 0

Description


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.

Data Processing

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.

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).

Temporal coverage

From 1/1/2013 to 7/1/2023

Dates

Creation date

10/6/2023

Publication date

1/4/2024

Revision date

12/16/2024

Citation information

How to cite this collection:

Macfarlane, C. K., Prober, S. M. & Wiehl, G. (2024): Great Western Woodlands Flux Data Release 2023_v2. Version 2023_v2. Terrestrial Ecosystem Research Network. (Dataset). https://doi.org/10.25901/y735-bp31

Access data

These data can be accessed from following links:

Rights and Licensing

CC-BY

Creative Commons Attribution 4.0 International Licence
http://creativecommons.org/licenses/by/4.0

TERN services are provided on an “as-is” and “as available” basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure.
Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.

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}.

Keywords

Parameters
Platforms
Instruments
GCMD Science
ANZSRC - FOR
Horizontal Resolution
Temporal Resolution
Topic Categories
User Defined
  • AU-GWW
  • Eddy Covariance
  • sparse eucalypt woodland

People and Organisation

AuthorsAuthors
Co-authorsCo-authors
Point of ContactPoint of Contact
PublisherPublisher
Distributor's OrganisationDistributor's Organisation

Publications

PublicationsPublications

Data Quality

Data QualityData Quality
  • 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

Additional information

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Contacts
  • Terrestrial Ecosystem Research Network
  • Building 1019, 80 Meiers Rd
  • QLD 4068
  • Australia
Spatial coverage
Spatial description
Located in Credo Conservation Reserve, Western Australia