13 citations as recorded by crossref.

1. Optimal redistribution of the background ozone monitoring stations over France L. Wu & M. Bocquet https://doi.org/10.1016/j.atmosenv.2010.08.038
2. Data assimilation using an ensemble of models: a hierarchical approach P. Rayner https://doi.org/10.5194/acp-20-3725-2020
3. 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
4. Greenhouse gas observation network design for Africa A. Nickless et al. https://doi.org/10.1080/16000889.2020.1824486
5. Designing optimal greenhouse gas observing networks that consider performance and cost D. Lucas et al. https://doi.org/10.5194/gi-4-121-2015
6. On observational and modelling strategies targeted at regional carbon exchange over continents C. Gerbig et al. https://doi.org/10.5194/bg-6-1949-2009
7. Optimising the deployment of renewable resources for the Australian NEM (National Electricity Market) and the effect of atmospheric length scales R. Huva et al. https://doi.org/10.1016/j.energy.2015.12.082
8. 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
9. Designing optimal greenhouse gas monitoring networks for Australia T. Ziehn et al. https://doi.org/10.5194/gi-5-1-2016
10. 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
11. Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case T. Ziehn et al. https://doi.org/10.5194/acp-14-9363-2014
12. Optimal reduction of the ozone monitoring network over France L. Wu et al. https://doi.org/10.1016/j.atmosenv.2010.04.012
13. Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models M. Bocquet et al. https://doi.org/10.5194/acp-15-5325-2015