Brief 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 site is classified as box woodland, dominated by two main eucalypt species: Eucalyptus microcarpa (grey box) and Eucalyptus leucoxylon (yellow gum). The site has an elevation of 165 m. Mean annual precipitation measured by the nearby Bureau of Meteorology site is 558 mm. Maximum temperatures range from 12.6 °C (in July) to 29.8 °C (in January), while minimum temperatures range from 3.2 °C (in July) to 14.2 °C (in February). Maximum temperatures vary on a seasonal basis by approximately 17.2 °C and minimum temperatures by 11.0 °C.
The instrument mast is 36 m tall. Heat, water vapour and carbon dioxide measurements are taken using the open-path eddy flux technique. Temperature, humidity, wind speed, wind direction, rainfall, incoming and reflected shortwave radiation and net radiation are measured above the canopy. Soil heat fluxes are measured and soil moisture content is gathered using time domain reflectometry.
Notes
Data ProcessingFile 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
- 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).
Notes
CreditWe 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.
Whroo flux station was originally established by the University of Western Australia in October 2011 as part of an ARC Linkage project "More bang for your carbon buck: carbon, biodiversity and water balance consequences of whole-catchment carbon farming" (LP0990038) Dr Ross Michael Thompson, A/Prof Jason Beringer, Dr Timothy Richard Cavagnaro, Prof Ralph Charles MacNally, Dr Patrick John Baker, Mr Mark Eigenraam, Mr Leon Metzeling. The site is affiliated to TERN and is now managed by the University of Melbourne.
The purpose of the Whroo site is to:
- assess how revegetation affects the interaction among carbon dynamics, water regimes (quality, quantity and frequency) and biodiversity across the landscape (above- and below-ground terrestrial, and aquatic ecosystems)
- develop a robust observational and modelling platform for soil-plant-atmosphere carbon and water fluxes for a range of land-use practices, including carbon farming, in these landscapes
- assess how carbon farming can be modified to increase biodiversity conservation.
Data Quality Assessment Scope
local :
dataset
<br>Processing levels</br>
<br>Under each of the data release directories, the netcdf files are organised by processing levels (L3, L4, L5 and L6):<ul style="list-style-type: disc;">
<li>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.</li>
<li>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).</li>
<li>L5 (Level 5) processing fills gaps in the flux data employing the artificial neural network SOLO (self-organising linear output map).</li>
<li>L6 (Level 6) processing partitions the gap-filled NEE into GPP and ER.</li></ul>
Each processing level has two sub-folders ‘default’ and ‘site_pi’:<ul style="list-style-type: disc;">
<li>default: contains files processed using PyFluxPro</li>
<li>site_pi: contains files processed by the principal investigators of the site.</li></ul>
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: <ul style="list-style-type: disc;">
<li>range checks for plausible limits</li>
<li>spike detection</li>
<li>dependency on other variables</li>
<li>manual rejection of date ranges</li></ul>
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 CO<sub>2</sub> and H<sub>2</sub>O signal strength, depending upon the configuration of the IRGA.</br>
Created: 2011-12-01
Issued: 2024-05-04
Modified: 2024-05-07
Data time period: 2011-12-01
text: Approximately 45km south west of Shepparton, Victoria.
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Point-of-truth metadata URL
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
doi :
https://doi.org/10.5194/bg-14-2903-2017
PyFluxPro
- URI : geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/5caef01d-03a6-417e-b178-fda2c1ae4f3f
- global : 5caef01d-03a6-417e-b178-fda2c1ae4f3f