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 (v3.4.21) as described by Isaac et al. (2017) for the quality control and post-processing steps. The final, gap-filled product containing Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER) has been produced using the ONEFlux software as described in Pastorello et al (2020). This data set has been produced as part of the FLUXNET Shuttle project.The Litchfield flux station is located within Litchfield National Park in the Northern Territory.
It was established in 2015 and is managed by Charles Darwin University and The University of Western Australia.
The station is a research and monitoring site representative of high rainfall, frequently burnt tropical savanna. The site is a 5 km x 5 km block of relatively uniform open-forest savanna inside the park about 80 km south of Darwin.
Measurements of carbon sequestration and remote sensing properties of vegetation through time are being achieved via a 40 m guyed tower equipped with instrumentation capable of directly measuring CO2, water use and surface energy properties (energy balance, reflectance). The Litchfield flux station is located within Litchfield National Park in the Northern Territory.
Lineage
Data collected using standard eddy covariance and meteorological instrumentation on a 40m tower at the Litchfield site. The data were quality controlled using the PyFluxPro software package, see Isaac et al (2017), which is available at https://github.com/OzFlux/PyFluxPro. Gap filling and partitioning has been done using the ONEFlux software package, see Pastorello et al 2020, which is available at https://github.com/fluxnet/ONEFlux.Data Creation
Data is measured using standard micro-meteorological instrumentation on a flux tower.
Data is recorded on a data logger and is collected by the site PI.
Data quality control including removal of data outside plausible ranges, removal of spikes, exclusion of particular date ranges and removal of data based on the dependence of one variable on another is done using PyFluxPro.
Filtering for low-ustar conditions, gap filling and partitioning of NEE into GPP and ER are done using ONEFlux.
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 purpose of the Litchfield flux station is to:
- The Litchfield flux station will provide nationally consistent observations of vegetation dynamics, faunal biodiversity, micrometeorology (climate, radiation, fluxes of carbon and water), hydrology and biogeochemistry to examine the impacts of fire regime, climate on carbon stocks and GHG emissions, and impacts on habitat quality via ongoing monitoring of vegetation structure and fauna. A wide range of ground based observations of vegetation structure and floristics is planned and all will link to remote sensing of fire and vegetation change over time. Co-location of Flux observations and remote sensing systems will be co-located to provide TERN with a ground-/air-/space based remote sensing observation stream. This will enable the development of tools describing fire occurrence, severity and associated greenhouse gas emissions, evapotranspiration and carbon sequestration.
- On-going fauna and flora monitoring will be undertaken at 5 sites within the SSS footprint that are component sites of the '3 Parks' data base, a long-term (15 years+) monitoring program across the 3 major national parks of the NT (Kakadu, Nitmiluk and Litchfield National Parks) that is examining the effects of fire frequency on vegetation structure and woody growth rates. Fire management, both protective and experimental burning regimes will be implemented across the SSS to assess impacts of fire on flora, fauna and biogeochemical cycles in savanna. The tower will provide long-term measurements as part of the Ozflux network.
- Key research questions
- - What are the impacts of prevailing fire regimes (primarily frequency, but also intensity, extent, heterogeneity) on vegetation structure and composition, habitat quality, fragmentation and vertebrate faunal biodiversity?
Data Quality Assessment Scope
local :
dataset
The data have been quality controlled using the PyFluxPro software. Quality control checks applied to the data include:<ul style="list-style-type: disc;">
<li>range checks for plausible limits</li>
<li>spike detection and removal</li>
<li>dependency on other variables</li>
<li>manual rejection of date ranges</li></ul>
<br>
Specific checks applied to the sonic and IRGA data including rejection of points based on the sonic and IRGA diagnostic values and on either automatic gain control (AGC) or CO2 and H2O signal strength, depending upon the configuration of the IRGA.</br>
<br>If the data quality is poor, the meteorological data is filled from ERA5 reanalysis data and fluxes are filled using the Marginal Distribution Sampling method. Filled data can be identified by the Quality Controls flags in the dataset. </br>
<br>The ONEFlux software used to gap fill and partition this data set also applies a Median Absolute Deviation (MAD) filter to the carbon dioxide, latent heat and sensible heat before the gap filling step.</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
Data Quality Assessment Result
local :
Quality Result
No anomalous data detected after quality control.
Created: 2026-03-11
Issued: 2026-04-01
Modified: 2026-04-02
Data time period: 2015-06-23 to 2026-01-01
text: The Litchfield flux tower is located within Litchfield National Park in the Northern Territory.
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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 :
https://github.com/OzFlux/PyFluxPro
ONEFlux
uri :
https://github.com/fluxnet/ONEFlux
Pastorello, G., Trotta, C., Canfora, E. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 7, 225 (2020).
- URI : geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/faab998e-7079-4702-85ef-c1a261cb3752
- global : faab998e-7079-4702-85ef-c1a261cb3752
