| 15 Sep 2026
TAlkEaSy: the Total Alkalinity Earth System Model v1.0 for exploring climate, redox and ocean chemistry over geologic time
Abstract. Here, we present the TAlkEaSy (Total Alkalinity Earth System) model, a framework for exploring the coupling of changes in the major ion balance of the ocean, biogeochemical cycling and global temperature and for testing hypotheses against proxy records. The model incorporates: (1) dynamic biogeochemical cycles of major ions (Ca, Mg, S, Na, K, Cl) and C, O and nutrients (N, P); (2) a complete alkalinity system with major ions and dissolved inorganic carbon (DIC) species; (3) novel proxies of Mg, Ca and U stable isotopes, together with C, S and Sr isotopes. The motivation for developing TAlkEaSy was that few existing models incorporate complete biogeochemical cycles of carbon, oxygen, nutrient, and ocean major ions with carbonate chemistry, and they either rely on data-driven approaches, or have problems accurately predicting major ion concentrations over geologic time. This impedes mechanistic understanding of the interactions between Earth’s climate, redox and ocean chemistry. TAlkEaSy is an extension of the COPSE model. We present the model configuration of TAlkEaSy and the functional forms, feedbacks, and parameterization of the biogeochemical processes included. The responses of TAlkEaSy to an idealised pulse injection of CO2 or a step increase in degassing are evaluated, to differentiate the responses to abrupt perturbation and slower changes in forcing.
General Comments
The development of "deep time" Earth system models built on a physical basis often limits the number of processes that can be explored, primarily because the underlying physics of the system remains incompletely understood. Conversely, the development of more "phenomenological" models—which incorporate numerous biogeochemical cycles and processes within a global-scale representation of the Earth’s surface—is particularly valuable for exploring complex couplings and feedback mechanisms.
The current evolution of the COPSE model, presented here as the TALkEaSy model (though TALES would arguably be a cleaner acronym, this remains the authors' choice), belongs to this second category. TALkEaSy is arguably the most comprehensive model currently available for describing the geological evolution of biogeochemical cycles. While spatially resolved models typically include only the carbon, alkalinity, and occasionally phosphorus and oxygen cycles, TALkEaSy further simulates the calcium, sodium, potassium, and chlorine cycles from a global perspective. However, introducing these additional cycles inevitably brings a large number of new parameters and assumptions regarding the mathematical expressions of the associated fluxes.
The introduction provides a thorough and highly useful review of existing models, clearly outlining their respective capabilities and objectives.
The model description is clear and easy to follow. A major step forward from COPSE is the division of the single atmosphere-ocean reservoir into two distinct reservoirs with dynamic exchange. This upgrade allows for a dynamic representation of ocean-atmosphere behavior in response to massive perturbations, moving past COPSE’s steady-state assumption of an instantaneous balance between silicate rock weathering and solid Earth degassing.
Main Comment
Regarding the results section, the evaluation is less convincing. The authors present results from two "academic" test simulations designed to simplify output interpretation and verify model mechanics. However, given the vast number of added parameters, a sensitivity analysis of the key outputs is essential. To what extent does the CO2Â response to a sudden degassing burst depend on specific parameter choices? Identifying the most critical parameters controlling this response would significantly strengthen the paper.
Minor Points
Recommendation
This is a high-quality contribution that will serve as a valuable reference for future users of the TALkEaSy model. It merits publication in Geoscientific Model Development (GMD) once the authors address the parameter sensitivity and clarify the underlying structural assumptions noted above.