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).
Wombat State Forest site is a secondary re-growth forest that was last harvested in 1980. Dominant tree species are Eucalyptus obliqua (messmate stringybark), Eucalyptus radiata (narrow leaf peppermint) and Eucalyptus rubida (candlebark) with an average canopy height of 25 m. The understorey consists mainly of patchy grasses and the soil is a silty-clay overlying clay. The forest is managed by the Department of Sustainability and Environment and management includes selective harvesting and prescribed burning regimes. The climate of the study area is classified as cool-temperate to Mediterranean with cold and wet winters (May-August) and warm and dry summers (December-February) with temperatures between 1 and 30 °C and mean annual air temperature of 12.1 °C. Annual rainfall is approximately 871 mm (142 year long-term average). Coherent automated measurements of soil greenhouse gas fluxes (CO2, CH4 and N2O) were collected using a trailer-mounted mobile laboratory - Fourier transform infra-red (FTIR) spectrometer from 2010 to 2016. Measurement height was originally 30 m but increased to 33 m in January 2017.
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.
The site is managed by The University of Melbourne in collaboration with Monash University and the Department of Sustainability and Environment of Victoria. Data collection is funded by TERN.
Wombat Forest research site facilitates the investigation of complex ecosystem processes of carbon, water and nutrient cycles in a dry-sclerophyll forest that are commonly found in Australia. This research will help to assess the impact of future environmental change on forest ecosystems in Australia. The Wombat Forest research site will:
- quantify the carbon sink/source strength of a dry sclerophyll forest and identify the contribution of such forests to the Australia's National Carbon Inventory
- quantify the emission and/or uptake of non-CO2 greenhouse gases, such as nitrous oxide and methane of the forest
- assess the role of climate variability and drought on ecosystem processes
- assess the impact of disturbances (such as fire) on ecosystem processes
- provide a database of microclimate and ecological parameters for use in carbon and water modelling projects.
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: 2010-01-20
text: Within the Wombat State Forest, between Ballarat and Daylesford in Central Victoria, 100km west of Melbourne.
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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/8de7aeab-0cf1-4c03-96dc-3a646063ad6f
- global : 8de7aeab-0cf1-4c03-96dc-3a646063ad6f
