R. Leuning’s research while affiliated with CSIRO Marine and Atmospheric Research and other places

p>The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions.</p

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Characterisation of Regional Fluxes of Methane in the Surat Basin, Queensland.

OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national research facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. This paper describes the evolution, design, and current status of OzFlux as well as provides an overview of data processing.We analyse measurements from all sites within the Australian portion of the OzFlux network and two sites from New Zealand. The response of the Australian biomes to climate was largely consistent with global studies except that Australian systems had a lower ecosystem water-use efficiency. Australian semi-arid/arid ecosystems are important because of their huge extent (70 %) and they have evolved with common moisture limitations. We also found that Australian ecosystems had a similar radiationuse efficiency per unit leaf area compared to global values that indicates a convergence toward a similar biochemical efficiency. The two New Zealand sites represented extremes in productivity for a moist temperate climate zone, with the grazed dairy farm site having the highest GPP of any OzFlux site (2620 gCm􀀀2 yr􀀀1/ and the natural raised peat bog site having a very low GPP (820 gCm􀀀2 yr􀀀1/. The paper discusses the utility of the flux data and the synergies between flux, remote sensing, and modelling. Lastly, the paper looks ahead at the future direction of the network and concludes that there has been a substantial contribution by OzFlux, and considerable opportunities remain to further advance our understanding of ecosystem response to disturbances, including drought, fire, land-use and land-cover change, land management, and climate change, which are relevant both nationally and internationally. It is suggested that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing the delicately balanced ecosystems in Australasia.

OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national research facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. This paper describes the evolution, design and current status of OzFlux as well as an overview of data processing. We analyse measurements from the Australian portion of the OzFlux network and found that the response of Australian biomes to climate was largely consistent with global studies but that Australian systems had a lower ecosystem water-use efficiency. Australian semi-arid/arid ecosystems are important because of their huge extent (70 %) and they have evolved with common moisture limitations. We also found that Australian ecosystems had similar radiation use efficiency per unit leaf area compared to global values that indicates a convergence toward a similar biochemical efficiency. The paper discusses the utility of the flux data and the synergies between flux, remote sensing and modelling. Lastly, the paper looks ahead at the future direction of the network and concludes that there has been a substantial contribution by OzFlux and considerable opportunities remain to further advance our understanding of ecosystem response to disturbances including drought, fire, land use and land cover change, land management and climate change that are relevant both nationally and internationally. It is suggested that a synergistic approach is required to address all of the spatial, ecological, human and cultural challenges of managing the delicately balanced ecosystems in Australia.

Climate and physiological controls of vegetation gross primary production (GPP) vary in space and time. In many ecosystems, GPP is primary limited by absorbed photosynthetically-active radiation; in others by canopy conductance. These controls further vary in importance over daily to seasonal time scales. We propose a simple but effective conceptual model that estimates GPP as the lesser of a conductance-limited (Fc) and radiation-limited (Fr) assimilation rate. Fc is estimated from canopy conductance while Fr is estimated using a light use efficiency model. Both can be related to vegetation properties observed by optical remote sensing. The model has only two fitting parameters: maximum light use efficiency, and the minimum achieved ratio of internal to external CO2 concentration. The two parameters were estimated using data from 16 eddy covariance flux towers for six major biomes including both energy- and water-limited ecosystems. Evaluation of model estimates with flux tower-derived GPP compared favourably to that of more complex models, for fluxes averaged; per day (r2 = 0.72, root mean square error, RMSE = 2.48 μmol C m2 s− 1, relative percentage error, RPE = − 11%), over 8-day periods (r2 = 0.78 RMSE = 2.09 μmol C m2 s− 1,RPE = − 10%), over months (r2 = 0.79, RMSE = 1.93 μmol C m2 s− 1, RPE = − 9%) and over years (r2 = 0.54, RMSE = 1.62 μmol C m2 s− 1, RPE = − 9%). Using the model we estimated global GPP of 107 Pg C y− 1 for 2000-2011. This value is within the range reported by other GPP models and the spatial and inter-annual patterns compared favourably. The main advantages of the proposed model are its simplicity, avoiding the use of uncertain biome- or land-cover class mapping, and inclusion of explicit coupling between GPP and plant transpiration.

We assess the performance of an inverse Lagrangian dispersion technique for its suitability to quantify leakages from geological storage of CO2. We find the technique is accurate ((QbLS/Q)=0.99, sigma=0.29) when strict meteorological filtering is applied to ensure that Monin-Obukhov Similarity Theory is valid for the periods analysed and when downwind enrichments in tracer gas concentration are 1% or more above background concentration. Because of their respective baseline atmospheric concentrations, this enrichment criterion is less onerous for CH4 than for CO2. Therefore for geologically sequestered gas reservoirs with a significant CH4 component, monitoring CH4 as a surrogate for CO2 leakage could be as much as 10 times more sensitive than monitoring CO2 alone. Additional recommendations for designing a robust atmospheric monitoring strategy for geosequestration include: continuous concentration data; exact inter-calibration of up- and downwind concentration measurements; use of an array of point concentration sensors to maximise the use of spatial information about the leakage plume; and precise isotope ratio measurement to confirm the source of any concentration elevations detected.

The CO2CRC Otway Project is Australia's first demonstration of the geological storage of carbon dioxide (CO2), where about 65,000 metric tons of fluid consisting of 92% CO2 and 8% methane (CH4) by mass have been injected underground. As part of the project objective of developing methodologies to detect, locate and quantify potential leakage of the stored fluid into the atmosphere, we formulate an inverse atmospheric model based on a Bayesian probabilistic framework coupled to a state-of-the-art backward Lagrangian particle dispersion model. A Markov chain Monte Carlo method is used for efficiently sampling the posterior probability distribution of the source parameters. Controlled experiments used to test the model involved releases of the injected fluid from one of the nearby wells and were staggered over one month. Atmospheric measurements of CO2 and CH4 concentrations were taken at two stations installed in an upwind-downwind configuration. Modeling both the emission rate and the source location using the concentration measurements from only two stations is difficult, but the fact that the emission rate was constant, which is not an unrealistic scenario for potential geological leakage, allows us to compute both parameters. The modeled source parameters compare reasonably well with the actual values, with the CH4 tracer constraining the source better than CO2, largely as a result of its six times higher signal-to-noise ratio. The results lend confidence in the ability of atmospheric techniques to quantify potential leakage from CO2 storage as well as other source types.