Beyond Forcing Scenarios: Predicting Climate Change through Response Operators in a Coupled General Circulation Model

Abstract

Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Here we show how to use statistical mechanics to construct operators able to flexibly predict climate change for a variety of climatic variables of interest. We perform our study on a fully coupled model - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO${}_2$ increase on a vast range of temporal scales, from inter-annual to centennial, and for very diverse climatic quantities. We investigate within a unified perspective the transient climate response and the equilibrium climate sensitivity and assess the role of fast and slow processes. The prediction of the ocean heat uptake highlights the very slow relaxation to a newly established steady state. The change in the Atlantic Meridional Overturning Circulation (AMOC) and of the Antarctic Circumpolar Current (ACC) is accurately predicted. The AMOC strength is initially reduced and then undergoes a slow and only partial recovery. The ACC strength initially increases as a result of changes in the wind stress, then undergoes a slowdown, followed by a recovery leading to a overshoot with respect to the initial value. Finally, we are able to predict accurately the temperature change in the Northern Atlantic.

arXiv comment17 pages, 8 figures. Improved discussion of the results and expanded bibliography compared to the previous version

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Cited by in corpus (18)

• The Physics of Climate Variability and Climate Change
• Theoretical tools for understanding the climate crisis from Hasselmann's program and beyond
• Global Stability Properties of the Climate: Melancholia States, Invariant Measures, and Phase Transitions
• Dynamical Landscape and Multistability of a Climate Model
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• A data-driven framework for dimensionality reduction and causal inference in climate fields
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• Universal Upper Estimate for Prediction Errors under Moderate Model Uncertainty
• Thermal Noise Magnetometry of magnetic nanoparticles: simulations and experiments
• A handy fluctuation-dissipation relation to approach generic noisy systems and chaotic dynamics
• A Stochastic Model for Induced Seismicity at the Geothermal Systems: A Case of the Geysers
• Predictors and Predictands of Linear Response in Spatially Extended Systems
• Introduction to the Special Issue on the Statistical Mechanics of Climate
• Kolmogorov Modes and Linear Response of Jump-Diffusion Models
• Projections of the Transient State-Dependency of Climate Feedbacks