Articles | Volume 14, issue 17
https://doi.org/10.5194/acp-14-9363-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-14-9363-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Sep 2014
Research article |
| 10 Sep 2014
Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case
Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric Research, Aspendale, VIC 3195, Australia
A. Nickless
Global Change and Ecosystem Dynamics, CSIR, Pretoria, 0005, South Africa
P. J. Rayner
School of Earth Sciences, University of Melbourne, Melbourne, VIC 3010, Australia
R. M. Law
Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric Research, Aspendale, VIC 3195, Australia
G. Roff
Centre for Australian Weather and Climate Research, Australian Bureau of Meteorology, Docklands, VIC 3008, Australia
P. Fraser
Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric Research, Aspendale, VIC 3195, Australia
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Cited
22 citations as recorded by crossref.
- Tower-based greenhouse gas measurement network design—The National Institute of Standards and Technology North East Corridor Testbed I. Lopez-Coto et al. https://doi.org/10.1007/s00376-017-6094-6
- Estimates of CO2 fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling A. Nickless et al. https://doi.org/10.5194/acp-18-4765-2018
- Greenhouse gas network design using backward Lagrangian particle dispersion modelling – Part 2: Sensitivity analyses and South African test case A. Nickless et al. https://doi.org/10.5194/acp-15-2051-2015
- A novel cluster-based learning scheme to design optimal networks for atmospheric greenhouse gas monitoring (CRO2A version 1.0) D. Matajira-Rueda et al. https://doi.org/10.5194/gmd-19-3757-2026
- Designing additional CO2 in-situ surface observation networks over South Korea using bayesian inversion coupled with Lagrangian modelling S. Takele Kenea et al. https://doi.org/10.1016/j.atmosenv.2024.120471
- Southern Hemisphere tree rings as proxies to reconstruct Southern Ocean upwelling C. Lewis et al. https://doi.org/10.5194/bg-22-4187-2025
- On the potential of the ICOS atmospheric CO2 measurement network for estimating the biogenic CO2 budget of Europe N. Kadygrov et al. https://doi.org/10.5194/acp-15-12765-2015
- Designing optimal greenhouse gas observing networks that consider performance and cost D. Lucas et al. https://doi.org/10.5194/gi-4-121-2015
- Designing optimal greenhouse gas monitoring networks for Australia T. Ziehn et al. https://doi.org/10.5194/gi-5-1-2016
- Designing an Atmospheric Monitoring Network to Verify National CO2 Emissions S. Sim et al. https://doi.org/10.1007/s13143-023-00343-3
- Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements M. Pallandt et al. https://doi.org/10.5194/bg-19-559-2022
- Site selection and effects of background towers on urban CO2 estimates: A case study from central downtown Zhengzhou in China G. Ren et al. https://doi.org/10.1016/j.envres.2024.120169
- Designing surface CO2 monitoring network to constrain the Indian land fluxes K. Nalini et al. https://doi.org/10.1016/j.atmosenv.2019.117003
- The potential of Orbiting Carbon Observatory-2 data to reduce the uncertainties in CO2 surface fluxes over Australia using a variational assimilation scheme Y. Villalobos et al. https://doi.org/10.5194/acp-20-8473-2020
- Towards improving top–down national CO2 estimation in Europe: potential from expanding the ICOS atmospheric network in Italy Y. Villalobos et al. https://doi.org/10.1088/1748-9326/adc41e
- Greenhouse gas observation network design for Africa A. Nickless et al. https://doi.org/10.1080/16000889.2020.1824486
- An atmospheric inversion over the city of Cape Town: sensitivity analyses A. Nickless et al. https://doi.org/10.5194/acp-19-7789-2019
- Sixty years of radiocarbon dioxide measurements at Wellington, New Zealand: 1954–2014 J. Turnbull et al. https://doi.org/10.5194/acp-17-14771-2017
- Design and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experiments J. Park & H. Kim https://doi.org/10.5194/acp-20-5175-2020
- Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design T. Kaminski & P. Rayner https://doi.org/10.5194/bg-14-4755-2017
- Comparison of the genetic algorithm and incremental optimisation routines for a Bayesian inverse modelling based network design A. Nickless et al. https://doi.org/10.1088/1361-6420/aab46c
- Exploring atmospheric CH4 monitoring network expansion in Italy using inverse modelling J. Thanwerdas et al. https://doi.org/10.5194/acp-26-10477-2026
22 citations as recorded by crossref.
- Tower-based greenhouse gas measurement network design—The National Institute of Standards and Technology North East Corridor Testbed I. Lopez-Coto et al. https://doi.org/10.1007/s00376-017-6094-6
- Estimates of CO2 fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling A. Nickless et al. https://doi.org/10.5194/acp-18-4765-2018
- Greenhouse gas network design using backward Lagrangian particle dispersion modelling – Part 2: Sensitivity analyses and South African test case A. Nickless et al. https://doi.org/10.5194/acp-15-2051-2015
- A novel cluster-based learning scheme to design optimal networks for atmospheric greenhouse gas monitoring (CRO2A version 1.0) D. Matajira-Rueda et al. https://doi.org/10.5194/gmd-19-3757-2026
- Designing additional CO2 in-situ surface observation networks over South Korea using bayesian inversion coupled with Lagrangian modelling S. Takele Kenea et al. https://doi.org/10.1016/j.atmosenv.2024.120471
- Southern Hemisphere tree rings as proxies to reconstruct Southern Ocean upwelling C. Lewis et al. https://doi.org/10.5194/bg-22-4187-2025
- On the potential of the ICOS atmospheric CO2 measurement network for estimating the biogenic CO2 budget of Europe N. Kadygrov et al. https://doi.org/10.5194/acp-15-12765-2015
- Designing optimal greenhouse gas observing networks that consider performance and cost D. Lucas et al. https://doi.org/10.5194/gi-4-121-2015
- Designing optimal greenhouse gas monitoring networks for Australia T. Ziehn et al. https://doi.org/10.5194/gi-5-1-2016
- Designing an Atmospheric Monitoring Network to Verify National CO2 Emissions S. Sim et al. https://doi.org/10.1007/s13143-023-00343-3
- Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements M. Pallandt et al. https://doi.org/10.5194/bg-19-559-2022
- Site selection and effects of background towers on urban CO2 estimates: A case study from central downtown Zhengzhou in China G. Ren et al. https://doi.org/10.1016/j.envres.2024.120169
- Designing surface CO2 monitoring network to constrain the Indian land fluxes K. Nalini et al. https://doi.org/10.1016/j.atmosenv.2019.117003
- The potential of Orbiting Carbon Observatory-2 data to reduce the uncertainties in CO2 surface fluxes over Australia using a variational assimilation scheme Y. Villalobos et al. https://doi.org/10.5194/acp-20-8473-2020
- Towards improving top–down national CO2 estimation in Europe: potential from expanding the ICOS atmospheric network in Italy Y. Villalobos et al. https://doi.org/10.1088/1748-9326/adc41e
- Greenhouse gas observation network design for Africa A. Nickless et al. https://doi.org/10.1080/16000889.2020.1824486
- An atmospheric inversion over the city of Cape Town: sensitivity analyses A. Nickless et al. https://doi.org/10.5194/acp-19-7789-2019
- Sixty years of radiocarbon dioxide measurements at Wellington, New Zealand: 1954–2014 J. Turnbull et al. https://doi.org/10.5194/acp-17-14771-2017
- Design and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experiments J. Park & H. Kim https://doi.org/10.5194/acp-20-5175-2020
- Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design T. Kaminski & P. Rayner https://doi.org/10.5194/bg-14-4755-2017
- Comparison of the genetic algorithm and incremental optimisation routines for a Bayesian inverse modelling based network design A. Nickless et al. https://doi.org/10.1088/1361-6420/aab46c
- Exploring atmospheric CH4 monitoring network expansion in Italy using inverse modelling J. Thanwerdas et al. https://doi.org/10.5194/acp-26-10477-2026
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