Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation
Abstract Various elements of the Earth system have the potential to undergo critical transitions to a radically different state, under sustained changes to climate forcing. The Atlantic meridional overturning circulation (AMOC) is of particular importance for North Atlantic heat transport and is tho...
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crioppubl:10.1088/1748-9326/ac7602 2024-09-15T18:23:38+00:00 Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation Lux, Kerstin Ashwin, Peter Wood, Richard Kuehn, Christian Department for Business, Energy and Industrial Strategy, UK Government European Union’s Horizon 2020 research and innovation programme 2022 http://dx.doi.org/10.1088/1748-9326/ac7602 https://iopscience.iop.org/article/10.1088/1748-9326/ac7602 https://iopscience.iop.org/article/10.1088/1748-9326/ac7602/pdf unknown IOP Publishing http://creativecommons.org/licenses/by/4.0 https://iopscience.iop.org/info/page/text-and-data-mining Environmental Research Letters volume 17, issue 7, page 075002 ISSN 1748-9326 journal-article 2022 crioppubl https://doi.org/10.1088/1748-9326/ac7602 2024-07-29T04:15:26Z Abstract Various elements of the Earth system have the potential to undergo critical transitions to a radically different state, under sustained changes to climate forcing. The Atlantic meridional overturning circulation (AMOC) is of particular importance for North Atlantic heat transport and is thought to be potentially at risk of passing such a tipping point (TP). In climate models, the location and likelihood of such TPs depends on model parameters that may be poorly known. Reducing this parametric uncertainty is important to understand the likelihood of tipping behaviour. In this letter, we develop estimates for parametric uncertainty in a simple model of AMOC tipping, using a Bayesian inversion technique. When applied using synthetic (‘perfect model’) salinity timeseries data, the technique drastically reduces the uncertainty in model parameters, compared to prior estimates derived from previous literature, resulting in tighter constraints on the AMOC TPs. To visualise the impact of parametric uncertainty on TPs, we extend classical tipping diagrams by showing probabilistic bifurcation curves according to the inferred distribution of the model parameter, allowing the uncertain locations of TPs along the probabilistic bifurcation curves to be highlighted. Our results show that suitable palaeo-proxy timeseries may contain enough information to assess the likely position of AMOC (and potentially other Earth system) TPs, even in cases where no tipping occurred during the period of the proxy data. Article in Journal/Newspaper North Atlantic IOP Publishing Environmental Research Letters 17 7 075002 |
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Abstract Various elements of the Earth system have the potential to undergo critical transitions to a radically different state, under sustained changes to climate forcing. The Atlantic meridional overturning circulation (AMOC) is of particular importance for North Atlantic heat transport and is thought to be potentially at risk of passing such a tipping point (TP). In climate models, the location and likelihood of such TPs depends on model parameters that may be poorly known. Reducing this parametric uncertainty is important to understand the likelihood of tipping behaviour. In this letter, we develop estimates for parametric uncertainty in a simple model of AMOC tipping, using a Bayesian inversion technique. When applied using synthetic (‘perfect model’) salinity timeseries data, the technique drastically reduces the uncertainty in model parameters, compared to prior estimates derived from previous literature, resulting in tighter constraints on the AMOC TPs. To visualise the impact of parametric uncertainty on TPs, we extend classical tipping diagrams by showing probabilistic bifurcation curves according to the inferred distribution of the model parameter, allowing the uncertain locations of TPs along the probabilistic bifurcation curves to be highlighted. Our results show that suitable palaeo-proxy timeseries may contain enough information to assess the likely position of AMOC (and potentially other Earth system) TPs, even in cases where no tipping occurred during the period of the proxy data. |
author2 |
Department for Business, Energy and Industrial Strategy, UK Government European Union’s Horizon 2020 research and innovation programme |
format |
Article in Journal/Newspaper |
author |
Lux, Kerstin Ashwin, Peter Wood, Richard Kuehn, Christian |
spellingShingle |
Lux, Kerstin Ashwin, Peter Wood, Richard Kuehn, Christian Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation |
author_facet |
Lux, Kerstin Ashwin, Peter Wood, Richard Kuehn, Christian |
author_sort |
Lux, Kerstin |
title |
Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation |
title_short |
Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation |
title_full |
Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation |
title_fullStr |
Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation |
title_full_unstemmed |
Assessing the impact of parametric uncertainty on tipping points of the Atlantic meridional overturning circulation |
title_sort |
assessing the impact of parametric uncertainty on tipping points of the atlantic meridional overturning circulation |
publisher |
IOP Publishing |
publishDate |
2022 |
url |
http://dx.doi.org/10.1088/1748-9326/ac7602 https://iopscience.iop.org/article/10.1088/1748-9326/ac7602 https://iopscience.iop.org/article/10.1088/1748-9326/ac7602/pdf |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Environmental Research Letters volume 17, issue 7, page 075002 ISSN 1748-9326 |
op_rights |
http://creativecommons.org/licenses/by/4.0 https://iopscience.iop.org/info/page/text-and-data-mining |
op_doi |
https://doi.org/10.1088/1748-9326/ac7602 |
container_title |
Environmental Research Letters |
container_volume |
17 |
container_issue |
7 |
container_start_page |
075002 |
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1810463887405875200 |