Layered Uncertainty in Planetary Thermal History Models: Implications for Hypotheses Discrimination and Habitability Modeling

TL;DR

This paper introduces a layered uncertainty analysis for Earth's thermal history models, highlighting how model ambiguity affects planetary habitability assessments and emphasizing the need for probabilistic evaluation of model predictions.

Contribution

It develops a layered uncertainty framework for planetary thermal models, integrating data, initial conditions, and structural uncertainties to improve habitability predictions.

Findings

Multiple models can fit Earth's data, leading to ambiguity.

Model uncertainty causes large forecast spreads for Earth's cooling history.

Layered uncertainty analysis enhances understanding of exoplanet habitability potential.

Abstract

Multiple hypotheses/models have been put forward regarding the cooling history of the Earth. The search for life beyond Earth has brought these models into a new light as they connect to one of the two energy sources life can tap. The ability to discriminate between different Earth cooling models, and the utility of adopting such models to aid in the assessment of planetary habitability, has been hampered by a lack of uncertainty analysis. This motivates a layered uncertainty analysis for a range of thermal history models that have been applied to the Earth. The analysis evaluates coupled model input, initial condition, and structural uncertainty. Layered model uncertainty, together with data uncertainty and multiple working hypotheses (another form of uncertainty), means that results must be evaluated in a probabilistic sense even if the models are deterministic. For the Earth's cooling history uncertainty leads to ambiguity - multiple models, based on different hypotheses, can match data constraints. This has implications for using such models to forecast conditions for exoplanets that share Earth characteristics but are older than the Earth, i.e., it has implications for modeling the long-term life potential of terrestrial planets. Even for the most Earth-like planet we know of, the Earth itself, model uncertainty and ambiguity leads to large forecast spreads. Given that this comes from the planet with the most data constraints we should expect larger spreads for models of terrestrial planets in general. The layered uncertainty approach can be expanded by coupling planetary cooling models to climate models and propagating uncertainty between them to assess habitability from a probabilistic versus a binary view.