Towards More Rigorous Thermal History Modeling Practices

Kendra Murray, Idaho State University
Alyssa Abbey, California State University, Long Beach
Andrea Stevens Goddard, Indiana University
Mark Wildman, University of Glasgow
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Abstract

Thermal history (time-temperature, tT) models are numerical tools for interpreting thermochronologic data, which integrate chronometer kinetics with what is already known about a rock's history in order to explore the unknown parts of that history. The distinctive ability of thermochronometers to fill knowledge gaps lies in their time-integrated sensitivity to a rock's temperature history. However, this sensitivity also means that cooling ages alone, without (and in some cases, even with) kinetics and geologic context, are non-unique. Therefore, when interpreting thermochronologic data, one has unavoidable and significant creative control over the result. This has a profound impact on the nature of new knowledge generated using thermochronology, but this reality is often cloaked by the apparent objectivity of tT modeling tools. Today, despite the dominant role of tT models thermochronology, we have insufficient community definitions of what makes a model result robust, how to rigorously demonstrate this, and how to communicate the choices that produced a preferred tT (and in turn, geologic) history. Consequently, published thermochronologic studies use a patchwork of modeling philosophies, assumptions, and auxiliary hypotheses that are rarely completely described, which can produce conflicting conclusions and spark distracting controversies. Recently, we published a pair of papers that aim to address part of this growing problem by offering an accessible suite of simple modeling exercises in the two most commonly used tT modeling programs, HeFTy (Murray et al., 2022) and QTQt (Abbey et al., 2023). We recommend everyone—new and experienced geoscientists alike—complete such exercises before using a tT modeling tool to interpret data for the first time; here we present a few key takeaways. We also look ahead to the next generation of modeling tools and the expanding community of users, because the thermochronology community needs to figure out how to both embrace a diversity of modeling approaches and collectively define tT modeling best practices. This will require deliberate, accessible, and ongoing conversations.

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