Uncertainties in steric sea level change estimation during the satellite altimeter era: concepts and practices

MacIntosh, C. R., Merchant, C. J. ORCID: https://orcid.org/0000-0003-4687-9850 and von Schuckmann, K. (2017) Uncertainties in steric sea level change estimation during the satellite altimeter era: concepts and practices. Surveys in Geophysics, 38 (1). ISSN 0169-3298 doi: 10.1007/s10712-016-9387-x

Abstract/Summary

This article presents a review of current practice in estimating steric sea level change, focussed on the treatment of uncertainty. Steric sea level change is the contribution to the change in sea level arising from the dependence of density on temperature and salinity. It is a significant component of sea level rise and a reflection of changing ocean heat content. However tracking these steric changes remains still a significant challenge for the scientific community. We review the importance of understanding the uncertainty in estimates of steric sea level change. Relevant concepts of uncertainty are discussed and illustrated with the example of observational uncertainty propagation from a single profile of temperature and salinity measurements to steric height. We summarise and discuss the recent literature on methodologies and techniques used to estimate steric sea level in the context of the treatment of uncertainty. Our conclusions are that progress in quantifying steric sea level uncertainty will benefit from: greater clarity and transparency in published discussions of uncertainty, including exploitation of international standards for quantifying and expressing uncertainty in measurement; and the development of community ‘recipes’ for quantifying the error covariances in observations and from sparse sampling, and for estimating and propagating uncertainty across spatio-temporal scales.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/66849
Identification Number/DOI	10.1007/s10712-016-9387-x
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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