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Boyagin Flux Data Release 2022_v2

Parent Dataset: Boyagin Flux Data Collection
Ver: 2022_v2
Status of Data: on going
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 (v3.4.7) 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).

The flux station was established in 2017 in Wandoo Woodland, which is surrounded by broadacre farming. About 80% of the overstorey cover is Eucalyptus accedens. Climate information comes from the nearby Pingelly BOM AWS station 010626 (1991 to 2016) and shows mean annual precipitation is approximately 445 mm with highest rainfall in June and July of 81 mm each month. Maximum and minimum annual rainfall is 775 and 217 mm, respectively. Maximum temperatures range from 31.9 °C (in Jan) to 15.4 °C (in July), while minimum temperatures range from 5.5 °C (in July) to 16.0 °C (in Feb). The Noongar people are the traditional owners at Boyagin.

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.

The Boyagin Wandoo Woodland Site is managed by the University of Western Australia, is co-located with the Land Ecosystem Atmosphere Program (LEAP) and is funded by TERN. The flux station is part of the Australian OzFlux Network and the international FLUXNET Network.

Purpose
The purpose of the Boyagin Wandoo Woodland Flux Station is to:
  • monitor and determine the balance of environmental demands for water yields, agricultural productivity, GHG budgets and biodiversity within a catchment landscape
  • mrovide information to establish a modelling tool for GHG and water fluxes across various land use types, in order to benefit land management practices in the wheat belt of Western Australia.

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 productivity, 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 10/20/2017

Dates

Creation date

10/20/2017

Publication date

5/4/2024

Revision date

5/4/2024

Citation information

How to cite this collection:

Beringer, J., Lardner, T. & Moore, C. (2024): Boyagin Flux Data Release 2022_v2. Version 2022_v2. Terrestrial Ecosystem Research Network. (Dataset). https://doi.org/10.25901/a8py-2b94

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-Boy
  • dry sclerophyll woodland
  • eddy covariance

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.

Additional information

Method DocumentationMethod Documentation
CollectionsCollections

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Contacts
  • Terrestrial Ecosystem Research Network
  • Building 1019, 80 Meiers Rd
  • QLD 4068
  • Australia
Spatial coverage
Spatial description
The Boyagin flux station is located approximately 12 km west of Pingelly, near Perth, Western Australia.