BAYSPLINE: A New Calibration for the Alkenone Paleothermometer

Jessica E. Tierney, Martin P. Tingley

Research output: Contribution to journalArticlepeer-review

139 Scopus citations

Abstract

The alkenone-based U UK’37 proxy is a cornerstone of paleoclimatology, providing insight into the temperature history of the Earth's surface ocean. Although the relationship between U UK’37 and sea surface temperatures (SSTs) is robust and well supported by experimental data, there remain outstanding issues regarding the seasonality of production of alkenones and the response of U UK’37 at very warm and cold SSTs. Using a data set of over 1,300 core-top U UK’37 measurements, we find compelling evidence of seasonal production in the North Atlantic, North Pacific, and Mediterranean Oceans. We also find significant attenuation of the U UK’37 response to SST at warm temperatures (>24°C), with the slope reduced by nearly 50% as U UK’37 approaches unity. To account for these observations in a calibration, we develop a new Bayesian B-spline regression model, BAYSPLINE, for the U UK’37 paleothermometer. BAYSPLINE produces similar estimates as previous calibrations below ∼24°, but above this point it predicts larger SST changes, in accordance with the attenuation of the U UK’37 response. Example applications of BAYSPLINE demonstrate that its treatment of seasonality and slope attenuation improves paleoclimatic interpretations, with important consequences for the inference of SSTs in the tropical oceans. BAYSPLINE facilitates a probabilistic approach to paleoclimate, building upon growing efforts to develop more formalized statistical frameworks for paleoceanographic reconstruction.

Original languageEnglish (US)
Pages (from-to)281-301
Number of pages21
JournalPaleoceanography and Paleoclimatology
Volume33
Issue number3
DOIs
StatePublished - Mar 2018

Keywords

  • Bayesian statistics
  • alkenones
  • paleothermometry

ASJC Scopus subject areas

  • Oceanography
  • Atmospheric Science
  • Palaeontology

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