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).
Yarramundi Control Paddock site is located near Richmond, NSW (GPS coordinates -33.613469, 150.734864). The site is about 1 km east of the Cumberland Plain Woodland flux tower. The climate is warm-temperate, with annual rainfall averaging 728 mm, mean maximum temperature in January of 30.4°C and mean minimum temperature in July of 3.6°C (BOM station 067105). The elevation of the site is about 20 m asl and the topography is flat. The soil is sandy loam in texture, organic carbon content is <1% nutrient availability is very low in the top 10 cm; iron concretions below 50 cm indicate poor drainage at times. The vegetation canopy is less than 1 m tall, and the plant community is dominated by exotic herbaceous perennials, including Conyza sumatrensis, Setaria parviflora, Cynodon dactylon, Commelina cyanea, Senecio madagascariensis, and Eragrostis curvula.
Fluxes of water vapour, carbon dioxide and heat are quantified with the open-path eddy flux technique from a 2.5 m tall mast. Additional measurements above the canopy include temperature, humidity, rainfall and net radiation, and photographs are taken several times per day to track canopy greenness.
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.
Yarramundi Control Flux Tower station is managed by Western Sydney University. Infrastructure at the site was funded by the Terrestrial Ecosystem Research Network (TERN), a project of the Commonwealth’s National Collaborative Research Infrastructure Strategy (NCRIS). This site is part of OzFlux Australia.
Purpose
The purpose of Yarramundi Control Paddock flux station is to:
- measure the exchange of carbon dioxide, water vapour and energy between an unmanaged pasture ecosystem and the atmosphere using micrometeorological techniques
- support an understanding of forage dynamics on an active cattle station
- support an understanding of environmental variability on ecosystem processes (such as photosynthesis, respiration or changes in plant structure and function)
- utilise the measurements for parameterising forage and grazing models
- utilise the measurements for parameterising and validating remote sensing measurements over semi-arid savanna ecosystems
- utilise the measurements for parameterising and validating the Earth System models to better understand the effects of climate change.
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
- 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).