Assessing AMOC stability using a Bayesian  nested time-dependent autoregressive model

Hallali, Luc; Myrvoll-Nilsen, Eirik; Franzke, Christian L. E.

doi:10.5194/npg-32-383-2025

Articles | Volume 32, issue 4

https://doi.org/10.5194/npg-32-383-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Emerging predictability, prediction, and early-warning approaches...

https://doi.org/10.5194/npg-32-383-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 32, issue 4

Research article

|

20 Oct 2025

Research article |

| 20 Oct 2025

Assessing AMOC stability using a Bayesian nested time-dependent autoregressive model

Luc Hallali, Eirik Myrvoll-Nilsen, and Christian L. E. Franzke

Viewed

Total article views: 5,153 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
4,437	541	175	5,153	185	259

HTML: 4,437
PDF: 541
XML: 175
Total: 5,153
BibTeX: 185
EndNote: 259

Views and downloads (calculated since 05 Jun 2025)

Month	HTML	PDF	XML	Total
Jun 2025	194	50	14	258
Jul 2025	202	56	32	290
Aug 2025	582	20	4	606
Sep 2025	1,208	26	12	1,246
Oct 2025	220	43	15	278
Nov 2025	250	40	11	301
Dec 2025	354	52	13	419
Jan 2026	333	48	13	394
Feb 2026	434	39	23	496
Mar 2026	114	68	10	192
Apr 2026	113	33	5	151
May 2026	247	24	7	278
Jun 2026	33	11	1	45
Jul 2026	125	21	6	152
Aug 2026	28	10	9	47

Cumulative views and downloads (calculated since 05 Jun 2025)

Month	HTML	PDF	XML	Total
Jun 2025	194	50	14	258
Jul 2025	202	56	32	290
Aug 2025	582	20	4	606
Sep 2025	1,208	26	12	1,246
Oct 2025	220	43	15	278
Nov 2025	250	40	11	301
Dec 2025	354	52	13	419
Jan 2026	333	48	13	394
Feb 2026	434	39	23	496
Mar 2026	114	68	10	192
Apr 2026	113	33	5	151
May 2026	247	24	7	278
Jun 2026	33	11	1	45
Jul 2026	125	21	6	152
Aug 2026	28	10	9	47

Viewed (geographical distribution)

Total article views: 5,153 (including HTML, PDF, and XML) Thereof 4,946 with geography defined and 207 with unknown origin.

Country	#	Views	%

1

1

Cited

Saved (final revised paper)

Latest update: 18 Aug 2026

Short summary

We present an alternative statistical methodology to detect whether the Atlantic Ocean’s circulation system is approaching a tipping point. Our approach separates natural variability from real early warning signals of tipping, reducing false alarms. When applied to a proxy of the Atlantic Ocean’s circulation strength, we find significant signs that the system is undergoing destabilization, suggesting that it may be approaching a tipping point, which could have major impacts on global climate patterns.