Seeking more robust early warning signals for climate tipping points: the Ratio of Spectra method (ROSA)

Clarke, Joseph J.; Huntingford, Chris ORCID: https://orcid.org/0000-0002-5941-7770; Ritchie, Paul D.L.; Cox, Peter M.. 2023 Seeking more robust early warning signals for climate tipping points: the Ratio of Spectra method (ROSA) [in special issue: Focus on Earth system resilience and tipping behavior] Environmental Research Letters, 18 (3), 035006. 10, pp. https://doi.org/10.1088/1748-9326/acbc8d

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Abstract/Summary

Potential tipping points in the Earth System present challenges for society and ecosystems, especially as the global warming thresholds at which these may be triggered remain uncertain. Fortunately, a theory of 'critical slowing down' has been developed which could warn of approaching tipping points. Applications of this theory often implicitly assume stationary white-noise forcing, itself requiring a clean separation between forced trends and variability, which is especially difficult under contemporary climate change. This paper proposes a modified method to derive early warning signal in a system, such as the climate, which is forced by time correlated processes. The method looks at the ratio of spectra (ROSA) of a system state variable relative to a forcing variable. We demonstrate the ROSA method on an idealised forced dynamical system, before applying it to a particular challenging example from the Earth System: dieback of the Amazon rainforest. We show that ROSA identifies more examples of abrupt transitions in the Amazon than conventional early warning signals in state-of-the-art CMIP6 Earth System Models.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1088/1748-9326/acbc8d
UKCEH and CEH Sections/Science Areas:	Hydro-climate Risks (Science Area 2017-)
ISSN:	1748-9326
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	tipping points, climate, early warning signals, spectral analysis, Amazon dieback
NORA Subject Terms:	Ecology and Environment Meteorology and Climatology
Related URLs:	Dataset
Date made live:	03 Nov 2023 16:17 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/535448

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