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BAYSPLINE: A New Calibration for the Alkenone Paleothermometer
Author(s) -
Tierney Jessica E.,
Tingley Martin P.
Publication year - 2018
Publication title -
paleoceanography and paleoclimatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.927
H-Index - 127
eISSN - 2572-4525
pISSN - 2572-4517
DOI - 10.1002/2017pa003201
Subject(s) - alkenone , climatology , proxy (statistics) , paleoclimatology , sea surface temperature , calibration , geology , environmental science , oceanography , climate change , statistics , mathematics
The alkenone‐based U37K ′proxy is a cornerstone of paleoclimatology, providing insight into the temperature history of the Earth's surface ocean. Although the relationship between U37K ′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 U37K ′at very warm and cold SSTs. Using a data set of over 1,300 core‐top U37K ′measurements, we find compelling evidence of seasonal production in the North Atlantic, North Pacific, and Mediterranean Oceans. We also find significant attenuation of the U37K ′response to SST at warm temperatures (>24°C), with the slope reduced by nearly 50% as U37K ′approaches unity. To account for these observations in a calibration, we develop a new Bayesian B‐spline regression model, BAYSPLINE, for the U37K ′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 U37K ′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.