Articles | Volume 8, issue 1
14 Feb 2022
 | 14 Feb 2022

A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level

Erica L. Ashe, Nicole S. Khan, Lauren T. Toth, Andrea Dutton, and Robert E. Kopp

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Cited articles

Abdul, N. A., Mortlock, R. A., Wright, J. D., and Fairbanks, R. G.: Younger Dryas sea level and meltwater pulse 1B recorded in Barbados reef crest coral Acropora palmata, Paleoceanography, 31, 330–344,, 2016. a
Marks, K. W.: AGRRA Database, version (2018-03), (last access: 4 Ferbruary 2022), 2018. a
Ashe, E. L.:, Zenodo [data set and code], (last access: 8 February 2022), 2021. a
Ashe, E. L., Cahill, N., Khan, N. S., Kemp, A. C., Engelhart, S. E., Horton, B. P., Parnell, A. C., and Kopp, R. E.: Statistical modeling of rates and trends in sea level, Quaternary Sci. Rev., 204, 58–77,, 2019. a, b
Blanchon, P. and Perry, C. T.: Taphonomic differentiation of Acropora palmata facies in cores from Campeche Bank Reefs, Gulf of México, Sedimentology, 51, 53–76,, 2004. a
Short summary
We develop a new technique to integrate realistic uncertainties in probabilistic models of past sea-level change. The new framework performs better than past methods (in precision, accuracy, bias, and model fit) because it enables the incorporation of previously unused data and exploits correlations in the data. This method has the potential to assess the validity of past estimates of extreme sea-level rise and highstands providing better context in which to place current sea-level change.