Probability Estimates of a 21st Century AMOC Collapse (2406.11738v1)

Abstract: There is increasing concern that the Atlantic Meridional Overturning Circulation (AMOC) may collapse this century with a disrupting societal impact on large parts of the world. Preliminary estimates of the probability of such an AMOC collapse have so far been based on conceptual models and statistical analyses of proxy data. Here, we provide observationally based estimates of such probabilities from reanalysis data. We first identify optimal observation regions of an AMOC collapse from a recent global climate model simulation. Salinity data near the southern boundary of the Atlantic turn out to be optimal to provide estimates of the time of the AMOC collapse in this model. Based on the reanalysis products, we next determine probability density functions of the AMOC collapse time. The collapse time is estimated between 2037-2064 (10-90% CI) with a mean of 2050 and the probability of an AMOC collapse before the year 2050 is estimated to be 59 +/- 17%.

• The paper estimates the probability of an Atlantic Meridional Overturning Circulation (AMOC) collapse in the 21st century using empirical analysis of observational data and climate model simulations.
• The research calculates a 59% (± 17%) probability of an AMOC collapse occurring before 2050, with the estimated timeframe between 2037 and 2064.
• Findings emphasize the urgency for continuous monitoring in identified optimal regions and suggest a critical reevaluation of climate models and mitigation policies.

Summary of "Probability Estimates of a 21st Century AMOC Collapse"

The paper entitled "Probability Estimates of a 21st Century AMOC Collapse" presents an empirical analysis of the likelihood of the Atlantic Meridional Overturning Circulation (AMOC) collapsing within this century. By utilizing observational data in conjunction with climate model simulations, the authors assert critical insights regarding the probability of such an event and its temporal framework.

Key Contributions and Methodology

The authors extend beyond conventional approaches of using proxy data and conceptual models by harnessing reanalysis datasets for a more observational perspective on AMOC collapse probabilities. This innovative approach enables an estimation of the AMOC collapse timeframe between 2037 and 2064, with a mean estimate around 2050. The notable finding is a calculated probability of 59% (± 17%) for a collapse occurring before 2050. Key methodological steps include:

1. Optimal Regions Identification: The authors exploit recent climate model simulations to identify optimal regions where salinity data near the southern Atlantic boundary is crucial for predicting an AMOC collapse.
2. Probability Density Functions (PDFs): The paper elucidates the determination of PDFs for collapse timing, derived from reanalysis data, thus streamlining the uncertainty analysis regarding the time to collapse.
3. Simulation Analysis: Utilizing the Community Earth System Model (CESM) of the CMIP5 family, the paper demonstrates that classical early warning signals (EWS) using sea surface temperatures (SSTs) from the sub-polar gyre are ineffective for AMOC warnings, leading to alternative region-specific indicators.

Numerical Highlights and Bold Assertions

• Temporal Estimate of Collapse: The research discusses the probability of the AMOC's collapse happening between 2037 and 2064, featuring a 10-90% confidence interval, suggesting a critical conjecture in climate system analysis.
• Strong Probability Claims: A bold declaration is the near 60% probability of the AMOC collapsing before mid-century, a profound claim challenging existing perception levels inferred in existing IPCC assessments.

Implications and Future Directions

The implications from this research are multifaceted. Practically, ongoing and continuous monitoring at the optimal identified regions is crucial for refining early warning systems. Theoretically, the findings call into reevaluation the stability and sensitivity of the AMOC to anthropogenic forces, with particular attention needed for climate models with better observational alignments.

Future developments should emphasize:

• Refined Data Integration: More comprehensive datasets should be integrated, especially those extending beyond the current reanalysis periods, enhancing temporal estimations.
• Model Biases Mitigation: Continued efforts to reduce biases in model simulations to better align with observational reality will potentiate more accurate future collapse estimates.
• Urgency in Policy Contexts: The potentially underestimated collapse probabilities underline an urgency for climate policies that can pre-empt adverse consequences on global climate patterns.

In conclusion, this paper provides a significant contribution to our understanding of the AMOC's stability under climate change pressures, urging the necessity for directed research and policies aimed at mitigating potential disruptive climate impacts.