Articles | Volume 15, issue 14
https://doi.org/10.5194/bg-15-4495-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-15-4495-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Does predictability of fluxes vary between FLUXNET sites?
Climate Change Research Centre, UNSW, Sydney, Australia
Gab Abramowitz
Climate Change Research Centre, UNSW, Sydney, Australia
Martin G. De Kauwe
Climate Change Research Centre, UNSW, Sydney, Australia
Andy J. Pitman
Climate Change Research Centre, UNSW, Sydney, Australia
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Cited
22 citations as recorded by crossref.
- Remote sensing of dryland ecosystem structure and function: Progress, challenges, and opportunities W. Smith et al. 10.1016/j.rse.2019.111401
- A spectral mixture analysis based framework for estimating and charactering water use efficiency in heterogeneous drylands Q. Pan et al. 10.1016/j.jhydrol.2024.131376
- Heat Storage Effect on Evaporation Estimates of China's Largest Freshwater Lake G. Gan & Y. Liu 10.1029/2019JD032334
- Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems J. Cranko Page et al. 10.5194/bg-19-1913-2022
- Evaluation of modeled actual evapotranspiration estimates from a land surface, empirical and satellite-based models using in situ observations from a South African semi-arid savanna ecosystem F. Khosa et al. 10.1016/j.agrformet.2019.107706
- Global trends in land-atmosphere CO<SUB>2</SUB> exchange fluxes: an analysis of a flux measurement dataset and comparison with terrestrial model simulations A. ITO 10.2480/agrmet.D-21-00015
- Upscaling dryland carbon and water fluxes with artificial neural networks of optical, thermal, and microwave satellite remote sensing M. Dannenberg et al. 10.5194/bg-20-383-2023
- A Review of Terrestrial Carbon Assessment Methods Using Geo-Spatial Technologies with Emphasis on Arid Lands S. Issa et al. 10.3390/rs12122008
- Investigation of a non-linear complementary relationship model for monthly evapotranspiration estimation at global flux sites G. Gan et al. 10.1175/JHM-D-20-0224.1
- Satellite Remote Sensing of Savannas: Current Status and Emerging Opportunities A. Abdi et al. 10.34133/2022/9835284
- Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules S. Westermann et al. 10.5194/bg-21-5277-2024
- TERN, Australia’s land observatory: addressing the global challenge of forecasting ecosystem responses to climate variability and change J. Cleverly et al. 10.1088/1748-9326/ab33cb
- Spatio-Temporal Changes in Water Use Efficiency and Its Driving Factors in Central Asia (2001–2021) S. Qin et al. 10.3390/rs15030767
- Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels P. Alton 10.1016/j.agrformet.2020.108017
- Complexity and Predictability of Daily Actual Evapotranspiration Across Climate Regimes C. Di et al. 10.1029/2022WR032811
- Intercomparison and evaluation of ten global ET products at site and basin scales H. Liu et al. 10.1016/j.jhydrol.2022.128887
- Understanding interactions among climate, water, and vegetation with the Budyko framework G. Gan et al. 10.1016/j.earscirev.2020.103451
- A flux tower dataset tailored for land model evaluation A. Ukkola et al. 10.5194/essd-14-449-2022
- Using automated machine learning for the upscaling of gross primary productivity M. Gaber et al. 10.5194/bg-21-2447-2024
- Non‐Stationary Lags and Legacies in Ecosystem Flux Response to Antecedent Rainfall J. Cranko Page et al. 10.1029/2022JG007144
- Carbon, water and energy fluxes in agricultural systems of Australia and New Zealand J. Cleverly et al. 10.1016/j.agrformet.2020.107934
- Embolism resistance explains mortality and recovery of five subtropical evergreen broadleaf trees to persistent drought J. Shao et al. 10.1002/ecy.3877
22 citations as recorded by crossref.
- Remote sensing of dryland ecosystem structure and function: Progress, challenges, and opportunities W. Smith et al. 10.1016/j.rse.2019.111401
- A spectral mixture analysis based framework for estimating and charactering water use efficiency in heterogeneous drylands Q. Pan et al. 10.1016/j.jhydrol.2024.131376
- Heat Storage Effect on Evaporation Estimates of China's Largest Freshwater Lake G. Gan & Y. Liu 10.1029/2019JD032334
- Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems J. Cranko Page et al. 10.5194/bg-19-1913-2022
- Evaluation of modeled actual evapotranspiration estimates from a land surface, empirical and satellite-based models using in situ observations from a South African semi-arid savanna ecosystem F. Khosa et al. 10.1016/j.agrformet.2019.107706
- Global trends in land-atmosphere CO<SUB>2</SUB> exchange fluxes: an analysis of a flux measurement dataset and comparison with terrestrial model simulations A. ITO 10.2480/agrmet.D-21-00015
- Upscaling dryland carbon and water fluxes with artificial neural networks of optical, thermal, and microwave satellite remote sensing M. Dannenberg et al. 10.5194/bg-20-383-2023
- A Review of Terrestrial Carbon Assessment Methods Using Geo-Spatial Technologies with Emphasis on Arid Lands S. Issa et al. 10.3390/rs12122008
- Investigation of a non-linear complementary relationship model for monthly evapotranspiration estimation at global flux sites G. Gan et al. 10.1175/JHM-D-20-0224.1
- Satellite Remote Sensing of Savannas: Current Status and Emerging Opportunities A. Abdi et al. 10.34133/2022/9835284
- Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules S. Westermann et al. 10.5194/bg-21-5277-2024
- TERN, Australia’s land observatory: addressing the global challenge of forecasting ecosystem responses to climate variability and change J. Cleverly et al. 10.1088/1748-9326/ab33cb
- Spatio-Temporal Changes in Water Use Efficiency and Its Driving Factors in Central Asia (2001–2021) S. Qin et al. 10.3390/rs15030767
- Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels P. Alton 10.1016/j.agrformet.2020.108017
- Complexity and Predictability of Daily Actual Evapotranspiration Across Climate Regimes C. Di et al. 10.1029/2022WR032811
- Intercomparison and evaluation of ten global ET products at site and basin scales H. Liu et al. 10.1016/j.jhydrol.2022.128887
- Understanding interactions among climate, water, and vegetation with the Budyko framework G. Gan et al. 10.1016/j.earscirev.2020.103451
- A flux tower dataset tailored for land model evaluation A. Ukkola et al. 10.5194/essd-14-449-2022
- Using automated machine learning for the upscaling of gross primary productivity M. Gaber et al. 10.5194/bg-21-2447-2024
- Non‐Stationary Lags and Legacies in Ecosystem Flux Response to Antecedent Rainfall J. Cranko Page et al. 10.1029/2022JG007144
- Carbon, water and energy fluxes in agricultural systems of Australia and New Zealand J. Cleverly et al. 10.1016/j.agrformet.2020.107934
- Embolism resistance explains mortality and recovery of five subtropical evergreen broadleaf trees to persistent drought J. Shao et al. 10.1002/ecy.3877
Discussed (final revised paper)
Discussed (preprint)
Latest update: 14 Dec 2024
Short summary
This project explores predictability in energy, water, and carbon fluxes in the free-use Tier 1 of the FLUXNET 2015 dataset using a uniqueness metric based on comparison of locally and globally trained models. While there is broad spread in predictability between sites, we found strikingly few strong patterns. Nevertheless, these results can contribute to the standardisation of site selection for land surface model evaluation and help pinpoint regions that are ripe for further FLUXNET research.
This project explores predictability in energy, water, and carbon fluxes in the free-use Tier 1...
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