Search for: All records

Projecting climate change is a generalization problem: We extrapolate the recent past using physical models across past, present, and future climates. Current climate models require representations of processes that occur at scales smaller than model grid size, which have been the main source of model projection uncertainty. Recent machine learning (ML) algorithms hold promise to improve such process representations but tend to extrapolate poorly to climate regimes that they were not trained on. To get the best of the physical and statistical worlds, we propose a framework, termed “climate-invariant” ML, incorporating knowledge of climate processes into ML algorithms, and show that it can maintain high offline accuracy across a wide range of climate conditions and configurations in three distinct atmospheric models. Our results suggest that explicitly incorporating physical knowledge into data-driven models of Earth system processes can improve their consistency, data efficiency, and generalizability across climate regimes.

Ocean circulation responses to interhemispheric radiative imbalance can damp north–south migrations of the intertropical convergence zone (ITCZ) by reducing the burden on atmospheric energy transport. The role of the Atlantic meridional overturning circulation (AMOC) in such dynamics has not received much attention. Here, we present coupled climate modeling results that suggest AMOC responses are of first-order importance to muting ITCZ shift magnitudes as a pair of hemispherically asymmetric solar forcing bands is moved from equatorial to polar latitudes. The cross-equatorial energy transport response to the same amount of interhemispheric forcing becomes systematically more ocean-centric when higher latitudes are perturbed in association with strengthening AMOC responses. In contrast, the responses of the Pacific subtropical cell are not monotonic and cannot predict this variance in the ITCZ’s equilibrium position. Overall, these results highlight the importance of the meridional distribution of interhemispheric radiative imbalance and the rich buffering of internal feedbacks that occurs in dynamic versus thermodynamic (slab) ocean modeling experiments. Mostly, the results imply that the problem of developing a theory of ITCZ migration is entangled with that of understanding the AMOC’s response to hemispherically asymmetric radiative forcing—a difficult topic deserving of focused analysis across more climate models.