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 (v3.4.15) 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).
The flux station is located within an area of dryland agriculture. The surrounding area is dominated by broadacre farming practices. The vegetation cover is predominantly pasture. Elevation of the site is close to 330 m. 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. Maximumum and minuimum 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).
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 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).
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.
The site is managed by the University of Western Australia. The flux station is part of the Australian OzFlux Network and contributes to the international FLUXNET Network.
The purpose of the Ridgefield 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
- provide 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 wheatbelt of Western Australia.
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>
<br>Ridgefield Flux Tower was established in 2016, and is currently active. The processed data release is currently ongoing, biannually.</br>
<br></br>
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
Created: 2023-10-06
Issued: 2022-03-28
Modified: 2024-05-04
Data time period: 2016-01-01 to 2023-08-07
text: Approximately 12km west of Pingelly, near Perth, Western Australia
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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/02c7c97a-bc72-4cd2-9b03-db8c438f45f5
- global : 02c7c97a-bc72-4cd2-9b03-db8c438f45f5
