Preprints
https://doi.org/10.5194/egusphere-2022-1410
https://doi.org/10.5194/egusphere-2022-1410
 
06 Jan 2023
06 Jan 2023
Status: this preprint is open for discussion and under review for Climate of the Past (CP).

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

Lev Tarasov1 and Michael Goldstein2 Lev Tarasov and Michael Goldstein
  • 1Department of Physics and Physical Oceanography, Memorial University of Newfoundland and Labrador, St. John’s, Canada, A1B 3X7
  • 2Durham University, Durham, England

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, in principle, 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, whether Bayesian or not, 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 focus on past ice sheet and climate evolution during the Quaternary.

Lev Tarasov and Michael Goldstein

Status: open (until 03 Mar 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Lev Tarasov and Michael Goldstein

Lev Tarasov and Michael Goldstein

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