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Stability specifications for climate data records: their meaning and application in evaluating geophysical trend uncertainty

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Merchant, C. J. ORCID: https://orcid.org/0000-0003-4687-9850, Woolliams, E. R., Dorigo, W., Bulgin, C. E. ORCID: https://orcid.org/0000-0003-4368-7386, Gobron, K., Hohensinn, R., Loizeau, X. and Tynan, C. P. J. (2026) Stability specifications for climate data records: their meaning and application in evaluating geophysical trend uncertainty. Surveys in Geophysics. ISSN 1573-0956 (In Press)

Abstract/Summary

When quantifying changes over time in the natural environment, the stability of the observations used should be considered. Stability conceptually refers to how accurately true geophysical changes and trends are reflected in observational data. We argue the need for a better approach to defining and quantifying stability consistently across climate data records. We propose that the appropriate stability metric is the stability uncertainty for specified spatial and temporal scales. We formally define stability uncertainty by analogy with metrological measurement uncertainty. Informally, stability uncertainty informs data analysts about the plausible magnitude of a non-geophysical contribution to trend values arising solely from the observing system. Neglecting the stability uncertainty leads to overconfident assessment of the significance of geophysical trends inferred from observations. We recommend that adopting this metric would greatly improve the clarity and practical impact of the Global Climate Observing System (GCOS) statements of requirement for stability of essential climate variable (ECV) products. Moreover, GCOS stability requirements would then become a useful resource for users of ECV products when evaluating and interpreting trends in observations, helping them avoid unjustified claims for the significance of computed trends; a synthetic illustration of such usage is provided.

Item Type Article
URI https://centaur.reading.ac.uk/id/eprint/128460
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher Springer
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