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 (v3.5.0) 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 Cumberland Plain flux station is located in a dry sclerophyll forest. The Cumberland Plain Woodland is now an endangered ecological community that encompasses distinct groupings of plants growing on clayey soils. The canopy is dominated by Eucalyptus moluccana and Eucalyptus fibrosa, which host an expanding population of mistletoe. Average canopy height is 23 m, the elevation of the site is 20 m and mean annual precipitation is 800 mm. Fluxes of water vapour, carbon dioxide and heat are quantified with the open-path eddy flux technique from a 30 m tall mast. Additional measurements above the canopy include temperature, humidity, wind speed and direction, rainfall, incoming and reflected shortwave and longwave radiation and net, diffuse and direct radiation and the photochemical reflectance index. In addition, profiles of humidity and CO2 are measured at eight levels within the canopy, as well as measurements of soil moisture content, soil heat fluxes, soil temperature, and 10 hr fuel moisture dynamics. In addition, regular monitoring of understory species abundance, mistletoe infection, leaf area index and litterfall are also performed.
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.
Cumberland Plain flux station is managed by the Hawkesbury Institute for the Environment at Western Sydney University and was funded by the Education Investment Fund and TERN.
The purpose of the Cumberland Plain flux station is:
- to quantify the exchanges of carbon dioxide, water vapour and energy in a dry sclerophyll forest
- to characterize the functional behaviour and sensitivity of the different components contributing to the ecosystem carbon balance from sub-daily to multi-annual temporal scales and under climatic variability
- to identify the role of hydraulic limitations on constraining ecosystem productivity
- to quantify the impact of mistletoe on plant physiological processes and whole ecosystem water vapour and carbon dioxide exchange
- to validate remote sensing estimates of different radiation components to obtain accurate regional predictions of fuel moisture
- to understand how wood traits and microbial diversity interact to determine rates of wood decay.
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>
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: 2023-03-31
Issued: 2024-05-04
Modified: 2024-05-07
Data time period: 2014-01-01
text: In the Hawkesbury Valley in central New South Wales.
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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/97b3701b-2fcb-47ed-9bee-2d84ea1c6ef4
- global : 97b3701b-2fcb-47ed-9bee-2d84ea1c6ef4
