| 12 Nov 2025
Simplified modeling of the impact of lithospheric-scale geological processes on thermal histories and low-temperature thermochronometers
Abstract. Many geological processes influence or perturb the thermal state of the lithosphere. This presents a challenge for relating thermal history data modeled from thermochronometers such as apatite and zircon fission-track and (U-Th)/He dating to geological evolution, a primary goal of many thermochronology studies. Here we address this challenge by exploring the thermal and thermochronological evolution of tracked rock parcels in 1D models that simulate key lithospheric geological processes, including erosional exhumation, sedimentary burial and exhumation, dip-slip faulting and delamination of the lithospheric mantle. We compare results from common depth history scenarios in which the Moho either experiences exhumation/burial or remains at a fixed depth balanced by crustal flux and erosion. Results show that Moho depth changes have a significant effect on thermal histories and thermochronometers, though this is not often considered in thermal history studies. Further, our results show that the recorded response of thermal histories/thermochronometers in the upper crust and geological processes that disrupt the crustal thermal field may be disassociated in time, because of the time and length scales of different heat transfer mechanisms. For example, a delamination event produces younger thermochronometer ages than an identical crustal exhumation history without delamination, but younger ages do not record the timing of delamination.
OVERVIEW
This manuscript presents a simple 1D thermokinematic modeling tool that predicts the thermochronologic cooling ages of crust that has experienced lithosphere-scale processes. These processes, such as burial, fault, and delamination, produce prescribed km-scale burial and/or exhumation that perturbs the crustal thermal field. The thermal and thermochronologic consequences of these different processes are quantified by forward modeling particle time, temperature, and depth paths relative to Earth’s surface and varying the lithospheric thermal field with changes in exhumation rate, heat production, Moho depth, and/or fault motion. The goal of this tool is to provide a relatively simple thermokinematic modeling tool that permits exploration of how specific geologic processes are predicted to impact low-temperature cooling ages. The authors argue that although simple, the results of their demonstration models suggest that Moho depth evolution over tens of millions of years can impact upper crustal thermal fields in ways that are resolvable by low-T thermochronology. These models also demonstrate in what ways the thermal history of rocks, and the cooling ages that document these histories, can be decoupled in time from the processes that (eventually) produced rock cooling.
This work demonstrates a new tool for investigating one of the central problems in low-temperature thermochronology: the challenge of inferring the timing and magnitude of lithosphere-scale geological processes through their impact on the thermal history of upper-crustal rocks, as documented by He and FT cooling ages. I think that simple 1D approaches, like the one used here, can provide an outstanding first-order tool for building intuition about how cooling ages should be expected to document these processes. This is a welcome addition. However, I find the manuscript as currently written and illustrated has several substantial limitations. First, I do not think the model results support the conclusion that Moho depth evolution over tens of millions of years can impact upper crustal thermal fields in ways that are resolvable by low-T thermochronology in real rocks, because the predicted variability among “perfect” model ages is small (< 15% of ages in most cases) compared to the typical uncertainty in real thermochronologic datasets. Second, 1D approaches are only useful if their simplifications, and the corresponding limitations, are very clearly articulated at the outset. I find that this paper does not do this effectively as currently written in several key ways, which would substantially limit reader engagement with the paper and the tool it is promoting. Finally, the figures, tables, and text that describe the model design and results are challenging to follow. I expand upon these comments below, and hope the authors find it useful as they revise.
MAJOR COMMENTS.
1 Results do not support one of the conclusions
I disagree that a main takeaway from the results that the “moving Moho” produces “significant” differences cooling ages. Yes, the MM produces systematic differences in the predicted ages for especially the two highest-T systems, but the cooling age differences are, in the vast majority of cases, less than what is considered reproducible in most real low-T thermochronometer datasets. This signal would simply get swamped out by other things.
For the example highlighted in the discussion (line 416), EE1: “the resulting ZHe and ZFT ages are 3-7 Myr younger for the MM variant”. However, these ages appear to be (reading off the figure) ZHe: 21 Ma vs 18 Ma, and ZFT: 42 Ma vs. 37 Ma. In real ZHe data, for example, one would be hard pressed to convince me that such a 3 Myr age difference has geological significance, because the intra-sample reproducibility of “well-behaved” samples is generally ~10-20%. Add in the fact that ZHe ages can vary much more significantly due to U-Th compositional variability, and that makes this even more tenuous.
2 Several key assumptions and limitations are not clearly explained
Section 2.1 of the methods falls significantly short of explaining key assumptions and limitations of this 1D approach. Instead, the explanations that are given for those I highlight below (and others) are scattered throughout the methods and results sections is a way that is difficult to keep track of; it is confusing to know what applies to a subset of scenarios and what applies more broadly. This is even more important to lay out clearly for those who want to use this tool to build and interpret their own models. As a reader who has though a lot about some of these simplifications, I’m eager to know what these authors think about them! But I was frustrated and distracted by the need to scour the manuscript for this information.
(2a) surface boundary condition and relationship to rock uplift
This is currently described as a fixed boundary condition in the FD solution to the heat transfer equation (line 59) “Temperatures are fixed at the surface…” and in a single sentence (lines 63-64): “A variety of erosion models are built into Tc1D allowing users to explore many different burial (i.e., negative erosion) and exhumation histories (Whipp, 2022).”
But…what is a built-in erosion model? This is very vague, and it sounds like it could be a geomorphic transport law. The reference in Whipp, 2022 is a link to the zenodo page that hosts the code, but I'm not clear on what the purpose of this citation is—what is the reader being referred to exactly? This Zenodo page doesn't provide any obvious narrative details about the "many different burial and exhumation histories" and how they have been conceptually and/or numerically constructed. Perhaps this is embedded in the documentation, but I think it is asking too much of the reader to dig into that.
I think the essential thing that needs to be described is how the simple surface boundary condition defines the relationship between rock uplift, surface uplift, and rock exhumation (the latter being only one of these three things that actually cools off rocks).
Conceptually, is the model space “hung” (and fixed) at depth = 0 km, without a sea level datum? And therefore erosion “scenarios” are simply changes in rock uplift rate through this fixed surface? Or, are “erosion scenarios” superimposed changes on independent rock uplift rates?
A depth = 0 km datum certainly makes sense from a thermochronology perspective (since cooling ages are agnostic about surface elevation relative to sea level), and I think it would make practical sense to anyone who has designed a similar 1D model themselves. But readers who build their own thermokinematic models are not the audience for this work (e.g., line 35). Critically, if I understand what is being done here (surface is fixed at 0 km depth, no surface uplift?), it means that rock uplift is being imposed with no surface uplift (i.e., exhumation is keeping perfect pace with rock uplift). Imposing rock uplift with no surface uplift is a huge simplifying assumption with cascading thermal and geodynamic implications. Moreover, it’s a significant deviation from how the Earth works in many of the scenarios of interest here (or else we’d have no relief at Earth’s surface). This simplification and its consequences are not clear right now.
The Thrust Fault models are the extreme example, because motion on a thrust fault alone cannot cool off rocks; thrusts cannot bring particles closer to Earth’s surface (unless accompanied by erosion, a separate process with its own drivers). But, in these models, when a particle in the HW of a thrust fault moves up a ramp, it is assumed that erosional exhumation is perfectly keeping pace with that motion. Indeed, this assumption is mentioned in passing (line 127), but its implications are not discussed.
In sum, if rock uplift always strictly equal to rock exhumation in these models, in both magnitude and timing, this needs to be explicitly stated and discussed up front. This simplification also needs to be related to the key takeaways of this paper, for example: “our results show that the recorded response of thermal histories/thermochronometers in the upper crust and geological processes that disrupt the crustal thermal field may be disassociated in time, because of the time and length scales of different heat transfer mechanisms.” (abstract, lines 9-11).
(2b) thermochronometer behavior
The paragraph at line 65 in section 2.1 that describes the basics of the He and FT age calculations is missing some key information. For example, does the model only predict one age per system? Can the user control key decisions about how these ages are calculated, such as grain size and U-Th composition in the He systems?
Of course, a lot of the resolving power of these chronometers comes from age-eU trends (He) and track length distributions (FT); which are not not mentioned and I assume not being predicted here; but this is a critical simplification that should be emphasized more. The radiation damage models for the He systems are being implemented; this is great, but it means grain composition is another potential ‘knob’ that will change predicted He ages in some scenarios, not being explored in the examples here. But, a hypothetical future user of this tool, upon sitting down to design a model run, would immediately be presented with the challenge of choosing particular grains to model. I think more clearly describing in this section what the consequences of only predicting single ages are would significantly improve the communication of the method.
Some of this information is currently relegated to section 2.3, after the extensive overviews of each of the geodynamic scenarios in Section 2.2. For example: “Hence, most of the scenarios explored below involve a starting depth for which open system behavior is expected, and zircon or apatite should not have accumulated any alpha damage (∼ 300C). Where this is not the case, the implications are discussed”. However, I cannot find any discussion of these implications in the rest of the text. This is another example of relevant assumptions and their implications being challenging to find and keep track of in the current manuscript.
(2c) starting conditions
The starting thermal and age conditions may have a strong control of the model results, but the starting conditions are not completely explained or justified here. As someone with modeling experience, in most cases I can figure out why these models are designed the way that they are; but, I shouldn’t have to spend time doing this as a reader, and again, experienced modelers are not the primary audience here. Some of my questions are:
Why do some scenarios start with 5 Myr of thermal steady state, whereas other do not? Why 5 Myr? Is that sufficient in duration to equilibrate both thermal and age structure across the model domain? (There are key length-scaling relationships here). And what actually are the “steady state” conditions in each model that uses them to set the thermal and age structure of the lithosphere? Are they different between the various scenarios?
What are the geological implications of that 5 Myr of steady state? For someone designing their own scenario, how should they determine whether they need a period of steady state prior to implementing a geological process of interest?
3 The text, figures, and tables that communicate the model designs, results, and implications are difficult to follow and comprehend as written
Starting in Section 2.2, and for the rest of the paper, I found I had to simultaneously be looking at Table 1, the figures presenting the tT and Tdepth info (ex, figure 3), and the relevant text in order to follow any of the main points. Few readers will have the time and patience to constantly flip between Table 1, the text, and the figures.
I think revision of the tables and figures would address this problem. The biggest barrier from my perspective is the figures; especially figures 3, 4, and 7 do not stand on their own at all. The figure captions don’t say anything useful, there is no annotation, and the only way to understand how the plots relate to geologic process, model design, or the variables of interest—let alone the implications and limitations of the results, e.g., don’t pay attention to the ZFT ages (line 220)—is to have Table 1 and multiple sections of the text also visible. There doesn’t seem to be a practical (figure design limitation) reason for this. In figure 3, for example, identical legends take up space in all 12 panels. Scenario IDs, which contain no specific information, are the only other label. The panels are not visually organized by scenario type or question, and none of the model design information is annotated. There are many opportunities for improvement here; for example, the information in Table 1 is laid out on a time axis, why not just annotate the essential information from that table onto these panels?
A few other related comments regarding the figures and tables:
Figure 2, All panels are all given the same visual weight in this figure, but in fact panels (a) and (b) apply to c-g.
Figure 3: The x-axis is both time and predicted cooling age (right?). It would be useful to describe what the significance of plotting the predicted cooling ages here means. I assume the ages are simply placed at the depth that corresponds to that time in the forward model? What is the best way to think about that information geologically, if one wants to export this information into a geological framework? This is a not typical way of visualizing thermochron data (though I think it is an effective way to present the model results).
Where ZFT data should be ignored (in models where total exhumation is 10 km? line 220), modify the symbol in the figures to make this clear. Does this limitation apply to all models, or just those in the EE group?
Table 1. Eliminate some unnecessary abbreviations. SS = steady state (but there’s enough space to just spell it out). IHP, the same; consider also using numbers for IHP instead of high vs. avg. IHP is called “volumetric heat production” in table 2; consider using same terminology for clarity, unless a (conceptual) difference is reflected in the nomenclature difference. “CE 5 km” and “Erode 5 km, constant rate” is identical information, but the different phrasing makes it seem different; erosion rates would be a welcome addition to this table.