29 citations as recorded by crossref.

1. Quantifying future climate change M. Collins et al. https://doi.org/10.1038/nclimate1414
2. Oscillations in a simple climate–vegetation model J. Rombouts & M. Ghil https://doi.org/10.5194/npg-22-275-2015
3. Feedback temperature dependence determines the risk of high warming J. Bloch‐Johnson et al. https://doi.org/10.1002/2015GL064240
4. The physics of climate variability and climate change M. Ghil & V. Lucarini https://doi.org/10.1103/RevModPhys.92.035002
5. Climate bistability of Earth-like exoplanets G. Murante et al. https://doi.org/10.1093/mnras/stz3529
6. Predicting Critical Transitions in ENSO Models. Part I: Methodology and Simple Models with Memory D. Mukhin et al. https://doi.org/10.1175/JCLI-D-14-00239.1
7. Extreme Sensitivity and Climate Tipping Points P. Ashwin & A. von der Heydt https://doi.org/10.1007/s10955-019-02425-x
8. The Drape: a new way to characterize ecosystem states, dynamics, and tipping points from process-based models C. Hély et al. https://doi.org/10.3389/fevo.2023.1108914
9. Nonautonomous modelling in energy balance models of climate. Limitations of averaging and climate sensitivity I. Longo et al. https://doi.org/10.1016/j.physd.2025.135038
10. Theoretical and paleoclimatic evidence for abrupt transitions in the Earth system N. Boers et al. https://doi.org/10.1088/1748-9326/ac8944
11. A stable hothouse triggered by a tipping mechanism E. Chavez et al. https://doi.org/10.1098/rsta.2024.0489
12. Making sense of palaeoclimate sensitivity https://doi.org/10.1038/nature11574
13. Solution to the paradox of climate sensitivity S. Pueyo https://doi.org/10.1007/s10584-011-0328-x
14. Global instability in the Ghil–Sellers model T. Bódai et al. https://doi.org/10.1007/s00382-014-2206-5
15. Bayesian optimization of empirical model with state-dependent stochastic forcing A. Gavrilov et al. https://doi.org/10.1016/j.chaos.2017.08.032
16. Potential stabilizing points to mitigate tipping point interactions in Earth's climate C. Gaucherel & V. Moron https://doi.org/10.1002/joc.4712
17. Lessons on Climate Sensitivity From Past Climate Changes A. von der Heydt et al. https://doi.org/10.1007/s40641-016-0049-3
18. How sensitive is climate sensitivity? G. Roe & K. Armour https://doi.org/10.1029/2011GL047913
19. Feedbacks, climate sensitivity and the limits of linear models R. Knutti & M. Rugenstein https://doi.org/10.1098/rsta.2015.0146
20. Concave–convex nonautonomous scalar ordinary differential equations: from bifurcation theory to critical transitions* J. Dueñas et al. https://doi.org/10.1088/1361-6544/ae0231
21. FAT-TAILED UNCERTAINTY, LEARNING, AND CLIMATE POLICY J. BISTLINE https://doi.org/10.1142/S2010007815500098
22. A discrete-time benchmark for assessing critical slowing down indicators S. Jafari et al. https://doi.org/10.1088/2632-072X/ae5384
23. Disconcerting learning on climate sensitivity and the uncertain future of uncertainty A. Hannart et al. https://doi.org/10.1007/s10584-013-0770-z
24. Dependency of Feedbacks on Forcing and Climate State in Physics Parameter Ensembles M. Yoshimori et al. https://doi.org/10.1175/2011JCLI3954.1
25. Climate Sensitivity Increases Under Higher CO2 Levels Due to Feedback Temperature Dependence J. Bloch‐Johnson et al. https://doi.org/10.1029/2020GL089074
26. Beyond equilibrium climate sensitivity R. Knutti et al. https://doi.org/10.1038/ngeo3017
27. On simple representations of the climate response to external radiative forcing T. Rohrschneider et al. https://doi.org/10.1007/s00382-019-04686-4
28. Sensitivity and resilience of the climate system: A conditional nonlinear optimization approach H. Dijkstra & J. Viebahn https://doi.org/10.1016/j.cnsns.2014.09.015
29. Crisis of the chaotic attractor of a climate model: a transfer operator approach A. Tantet et al. https://doi.org/10.1088/1361-6544/aaaf42