Simulating AMOC tipping driven by internal climate variability with a rare event algorithm
(2024) npj Climate and Atmospheric Science — Vol. 7, n° 31 (2024)
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- Authors
Ragone, Francesco 
- Abstract
- This study investigates the possibility of Atlantic Meridional Overturning Circulation (AMOC) noise-induced tipping solely driven by internal climate variability without applying external forcing that alter the radiative forcing or the North Atlantic freshwater budget. We address this hypothesis by applying a rare event algorithm to ensemble simulations of present-day climate with an intermediate complexity climate model. The algorithm successfully identifies trajectories leading to abrupt AMOC slowdowns, which are unprecedented in a 2000-year control run. Part of these AMOC weakened states lead to collapsed state without evidence of AMOC recovery on multi-centennial time scales. The temperature and Northern Hemisphere jet stream responses to these internally-induced AMOC slowdowns show strong similarities with those found in externally forced AMOC slowdowns in state-of-the-art climate models. The AMOC slowdown seems to be initially driven by Ekman transport due to westerly wind stress anomalies in the North Atlantic and subsequently sustained by a complete collapse of the oceanic convection in the Labrador Sea. These results demonstrate that transitions to a collapsed AMOC state purely due to internal variability in a model simulation of present-day climate are rare but theoretically possible. Additionally, these results show that rare event algorithms are a tool of valuable and general interest to study tipping points since they introduce the possibility of collecting a large number of tipping events that cannot be sampled using traditional approaches. This opens the possibility of identifying the mechanisms driving tipping events in complex systems in which little a-priori knowledge is available. © 2024, The Author(s).
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Citations
Cini, M., Zappa, G., Ragone, F., & Corti, S. (2024). Simulating AMOC tipping driven by internal climate variability with a rare event algorithm. npj Climate and Atmospheric Science, 7(31). https://doi.org/10.1038/s41612-024-00568-7 (Original work published 2024)