Evidence map›Paper›PMID 38102135›Full record

ArticleNature communications2023

Uncertainties in critical slowing down indicators of observation-based fingerprints of the Atlantic Overturning Circulation.

Maya Ben-Yami, Vanessa Skiba, Sebastian Bathiany, Niklas Boers

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Maya Ben-YamiEarth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany. maya.ben-yami@tum.de.ORCID http://orcid.org/0000-0002-7355-8318
Vanessa SkibaPotsdam Institute for Climate Impact Research, Potsdam, Germany.ORCID http://orcid.org/0000-0002-0496-120X
Sebastian BathianyEarth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0001-9904-1619
Niklas BoersEarth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-1239-9034

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions) 956170EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 820970
6 · The paper itself

Abstract

Observations are increasingly used to detect critical slowing down (CSD) to measure stability changes in key Earth system components. However, most datasets have non-stationary missing-data distributions, biases and uncertainties. Here we show that, together with the pre-processing steps used to deal with them, these can bias the CSD analysis. We present an uncertainty quantification method to address such issues. We show how to propagate uncertainties provided with the datasets to the CSD analysis and develop conservative, surrogate-based significance tests on the CSD indicators. We apply our method to three observational sea-surface temperature and salinity datasets and to fingerprints of the Atlantic Meridional Overturning Circulation derived from them. We find that the properties of these datasets and especially the specific gap filling procedures can in some cases indeed cause false indication of CSD. However, CSD indicators in the North Atlantic are still present and significant when accounting for dataset uncertainties and non-stationary observational coverage.

Identifiers

PMID38102135
PMCPMC10724135

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.