11 citations as recorded by crossref.

1. Learning Causal Estimates of Linear Operators from Noisy Data F. Cacace & A. Germani https://doi.org/10.1109/TAC.2022.3195151
2. On some aspects of the response to stochastic and deterministic forcings M. Santos Gutiérrez & V. Lucarini https://doi.org/10.1088/1751-8121/ac90fd
3. Timescale dependence of airborne fraction and underlying climate–carbon-cycle feedbacks for weak perturbations in CMIP5 models G. Torres Mendonça et al. https://doi.org/10.5194/bg-21-1923-2024
4. Detecting and Attributing Change in Climate and Complex Systems: Foundations, Green’s Functions, and Nonlinear Fingerprints V. Lucarini & M. Chekroun https://doi.org/10.1103/PhysRevLett.133.244201
5. CMIP6 models agree on similar carbon cycle feedbacks between enhancing terrestrial and marine carbon sinks H. Wey et al. https://doi.org/10.1088/1748-9326/adc617
6. Learning Nonlinear Systems via Volterra Series and Hilbert-Schmidt Operators F. Cacace et al. https://doi.org/10.1109/TAC.2023.3338462
7. Climate response and sensitivity: time scales and late tipping points R. Bastiaansen et al. https://doi.org/10.1098/rspa.2022.0483
8. Carbon system state determines warming potential of emissions A. Winkler et al. https://doi.org/10.1371/journal.pone.0306128
9. Bridging the Gap Between Koopmanism and Response Theory: Using Natural Variability to Predict Forced Response N. Zagli et al. https://doi.org/10.1137/24M1699206
10. Identification of linear response functions from arbitrary perturbation experiments in the presence of noise – Part 2: Application to the land carbon cycle in the MPI Earth System Model G. Torres Mendonça et al. https://doi.org/10.5194/npg-28-533-2021
11. Separating internal and externally forced contributions to global temperature variability using a Bayesian stochastic energy balance framework M. Schillinger et al. https://doi.org/10.1063/5.0106123