Discussion Paper: A Bayesian multinomial regression model for paleoclimate reconstruction with time uncertainty

• Published in: Environmetrics
• Main Author: Parnell, Andrew C.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2017
• Subjects: Time series analysis; Palaeoclimate science; Arctic
• Online Access: http://hdl.handle.net/10197/8332; https://doi.org/10.1002/env.2401

In this discussion I hope to highlight some of the real contributions of this paper, to point out some of the important non-statistical considerations (which, as applied statisticians in this area we should be cognisant), and to contrast with the rapidly expanding mostly-Bayesian palaeoclimate statistics literature. In particular, accounting for time uncertainty is, I suspect, almost a unique challenge for time series analysis in palaeoclimate science. For this reason it has been ignored for decades. Now with tools as in this paper, they can start to draw proper inferences on climate over time with suitably quantified uncertainties. Academy of Finland project Ecological History and Long-Term Dynamics of the Boreal Forest Ecosystem (EBOR) Nordic top-level research initiative Cryosphere-Atmosphere Interactions in a Changing Arctic Climate (CRAICC)