Smale, D. (2026). Lauder FLUXNET Release 2026_r1. Version 2026_r1. Terrestrial Ecosystem Research Network. Dataset. https://dx.doi.org/10.25901/6zb3-2m14
Lauder FLUXNET Release 2026_r1
Ver: 2026_r1
Status of Data: completed
Update Frequency: annually
Security Classification: unclassified
Record Last Modified: 2026-04-02
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Dataset Created: 2026-03-20
Dataset Published: 2026-04-02
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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 standard micrometeorological methods 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 Lauder Eddy Covariance system (ECS) is in a paddock (6.28 h) of a local farm, adjacent to the NIWA Lauder atmospheric research station, 169°40'49.143" E 45°2'16.004" S, 390 m above mean sea level. Lauder is in the Manuherika Valley, Central Otago, New Zealand, approximately 37 km north of Alexandra.
The Eddy Covariance CO2 flux measurements made at Lauder were specifically instigated for the Endeavour funded Carbonwatch NZ project. Grasslands are likely to be associated with potentially significant carbon sources and sinks, which may be manageable. Currently, New Zealand’s National Inventory Report (NIR) assumes established grasslands have zero net flux. Measurements are vital to estimate realistic fluxes.
The Eddy Covariance CO2 flux measurements made at Lauder were specifically instigated for the Endeavour funded Carbonwatch NZ project. Grasslands are likely to be associated with potentially significant carbon sources and sinks, which may be manageable. Currently, New Zealand’s National Inventory Report (NIR) assumes established grasslands have zero net flux. Measurements are vital to estimate realistic fluxes.
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.
Purpose
- Flux estimates can be added directly to the ‘bottom up’ NIR once they are validated. - Provide apriori constraints and validation of ‘top down’ regional and national CO2 flux inversions. - Provide apriori constraints and validation to ‘bottom up’ biochemistry modelling of terrestrial carbon flux.
Lineage
Data collected using standard eddy covariance and meteorological instrumentation on a 2m tower at the Lauder site. The data were quality controlled by the site Principle Investigator. 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.
Method DocumentationPastorello, G., Trotta, C., Canfora, E. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 7, 225 (2020).ONEFlux
Procedure Steps
1.
Data is measured using standard micro-meteorological instrumentation on a flux tower.
2.
Data is recorded on a data logger and is collected by the site PI.
3.
Data quality control and post-processing has been done by the site PI.
4.
Filtering for low-ustar conditions, gap filling and partitioning of NEE into GPP and ER are done using ONEFlux.
Spatial Description
The Lauder flux tower is located at the NIWA Atmospheric Research Station in Central Otago, South Island New Zealand.
Temporal Coverage
From 2019-01-01 to 2026-01-01
Spatial Resolution
Data not provided.
Vertical Extent
Data not provided.
Data Quality Assessment Scope
The data have been quality controlled by the site PI using standard micro-meteorological methods.
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.
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.
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.
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.
Data Quality Report
Data not provided.
Data Quality Assessment Outcome
No anomalous data detected after quality control.
ANZSRC - FOR
GCMD Sciences
Horizontal Resolution
Parameters
Temporal Resolution
User Defined
FLUXNET ID
NZ-Lau
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