Quantifying errors in coral-based ENSO estimates: Toward improved forward modeling of δ18O


  • S. Stevenson,

    Corresponding author
    1. International Pacific Research Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA
    • Corresponding author: S. Stevenson, International Pacific Research Center, University of Hawaii at Manoa, 1000 Pope Rd., Honolulu, HI 96822, USA. (

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  • H. V. McGregor,

    1. School of Earth and Environmental Sciences, University of Wollongong, Wollongong, New South Wales, Australia
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  • S. J. Phipps,

    1. Climate Change Research Centre and ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, New South Wales, Australia
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  • Baylor Fox-Kemper

    1. Department of Geological Sciences, Brown University, Providence, Rhode Island, USA
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[1] The oxygen isotopic ratio (δ18O) in tropical Pacific coral skeletons reflects past El Niño–Southern Oscillation (ENSO) variability, but the δ18O-ENSO relationship is poorly quantified. Uncertainties arise when constructing δ18O data sets, combining records from different sites, and converting between δ18O and sea surface temperature (SST) and salinity (SSS). Here we use seasonally resolved δ18O from 1958 to 1985 at 15 tropical Pacific sites to estimate these errors and evaluate possible improvements. Observational uncertainties from Kiritimati, New Caledonia, and Rarotonga are 0.12–0.14‰, leading to errors of 8–25% on the typical δ18O variance. Multicoral syntheses using five to seven sites capture the principal components (PCs) well, but site selection dramatically influences ENSO spatial structure: Using sites in the eastern Pacific, western Pacific warm pool, and South Pacific Convergence Zone (SPCZ) captures “eastern Pacific-type” variability, while “Central Pacific-type” events are best observed by combining sites in the warm pool and SPCZ. The major obstacle to quantitative ENSO estimation is the δ18O/climate conversion, demonstrated by the large errors on both δ18O variance and the amplitude of the first principal component resulting from the use of commonly employed bivariate formulae to relate SST and SSS to δ18O. Errors likely arise from either the instrumental data used for pseudoproxy calibration or influences from other processes (δ18O advection/atmospheric fractionation, etc.). At some sites, modeling seasonal changes to these influences reduces conversion errors by up to 20%. This indicates that understanding of past ENSO dynamics using coral δ18O could be greatly advanced by improving δ18O forward models.