Preprints
https://doi.org/10.5194/cp-2021-145
https://doi.org/10.5194/cp-2021-145
17 Nov 2021
 | 17 Nov 2021
Status: this preprint was under review for the journal CP but the revision was not accepted.

Assessing uncertainty in past ice and climate evolution: overview, stepping-stones, and challenges

Lev Tarasov and Michael Goldstein

Abstract. In the geosciences, complex computational models have become a common tool for making statements about past earth system evolution. However, the relationship between model output and the actual earth system (or component thereof) is generally poorly specified and even more poorly assessed. This is especially challenging for the paleo sciences for which data constraints are sparse and have large uncertainties. Bayesian inference offers a self-consistent and rigorous framework for assessing this relationship as well as a coherent approach to combining data constraints with computational modelling. Though “Bayesian” is becoming more common in paleoclimate and paleo ice sheet publications, our impression is that most scientists in these fields have little understanding of what this actually means nor are they able to evaluate the quality of such inference. This is especially unfortunate given the correspondence between Bayesian inference and the classical concept of the scientific method.

Herein, we examine the relationship between a complex model and a system of interest, or in equivalent words (from a statistical perspective), how uncertainties describing this relationship can be assessed and accounted for in a principled and coherent manner. By way of a simple example, we show how inference can be severely broken if uncertainties are erroneously assessed. We explain and decompose Bayes Rule (more commonly known as Bayes Theorem), examine key components of Bayesian inference, offer some more robust and easier to attain stepping stones, and provide suggestions on implementation and how the community can move forward. This overview is intended for all interested in making and/or evaluating inferences about the past evolution of the Earth system (or any of its components), with a nominal focus on past ice sheet and climate evolution during the Quaternary.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Lev Tarasov and Michael Goldstein

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on cp-2021-145', Natasha Barlow, 05 Jan 2022
    • AC1: 'Reply on RC1', Lev Tarasov, 30 Jul 2022
  • RC2: 'Comment on cp-2021-145', Danny Williamson, 25 Mar 2022
    • AC2: 'Reply on RC2', Lev Tarasov, 30 Jul 2022
  • EC1: 'Comment on cp-2021-145', Eric Wolff, 25 Mar 2022
    • AC1: 'Reply on RC1', Lev Tarasov, 30 Jul 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on cp-2021-145', Natasha Barlow, 05 Jan 2022
    • AC1: 'Reply on RC1', Lev Tarasov, 30 Jul 2022
  • RC2: 'Comment on cp-2021-145', Danny Williamson, 25 Mar 2022
    • AC2: 'Reply on RC2', Lev Tarasov, 30 Jul 2022
  • EC1: 'Comment on cp-2021-145', Eric Wolff, 25 Mar 2022
    • AC1: 'Reply on RC1', Lev Tarasov, 30 Jul 2022
Lev Tarasov and Michael Goldstein
Lev Tarasov and Michael Goldstein

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Latest update: 18 Jun 2024
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Short summary
This review: 1. Illustrates how current climate and/or ice sheet model-based inferences about the past tend to have limited interpretable value about the real world given inadequate accounting of uncertainties. 2. Explains Bayesian inference to a non-statistical community. 3. Sketches out tractable Bayesian inference for computationally expensive models in a way that meaningfully accounts for uncertainties. 4. Lays out some steps for the community to move forward.