Geothermal heat flow fields for ISMIP7 – Community recommendations for Antarctica & Greenland

Geothermal heat flow (GHF) plays a fundamental role in regulating basal thermal conditions of ice sheets, influencing basal sliding, internal deformation, and lithospheric rheology. Despite its importance, GHF in polar regions remains poorly constrained due to the scarcity of borehole measurements and substantial divergence among existing geophysical and glaciological estimates. These discrepancies stem from differences in methodology, data availability, and underlying assumptions, leading many ice sheet models to rely on spatially uniform values, ensemble means, or legacy products that inadequately represent spatial variability. We review all available continent-wide GHF fields, analysing their methodologies and data sources, and provide recommendations on their use. GHF fields generally fall into three categories: (1) outdated due to improved data availability, (2) overly simplified parametrization, and (3) preferred fields. To further assess applicability, we conducted an online expert elicitation survey to identify the most suitable fields for ice sheet modeling, particularly for ISMIP7. For preferred fields, we discuss uncertainty and data dependency to guide their use in different applications.

In Antarctica, all fields agree on the broad division between low heat flow in East and higher heat flow in West Antarctica, though spatial patterns vary. Preferred fields serve as a baseline for local studies, which can incorporate additional datasets like magnetic depth estimates or regional geological constraints. In Greenland, uncertainty is particularly high at NGRIP, where estimation and observations are difficult to reconcile. Local heterogeneity impacts heat flow observations in ways that regional fields cannot yet fully address. Nonetheless, recent estimates suggest low to moderate heat flow under the Greenland ice sheet, indicating that the Iceland hot spot has a limited impact, while subglacial geology plays a dominant role in controlling local variations.

Results from the expert survey indicate broad support for multivariate, data-driven approaches that integrate geological and geophysical constraints, including recent fields by Stål et al. (2021), Lösing & Ebbing (2021), and Colgan et al. (2022). These methods are generally regarded as better equipped to use all existing information, represent spatial heterogeneity, provide uncertainty information, and remain consistent with inferred basal conditions. Importantly, the survey captures, as objectively as possible, the reasons why a given GHF field is a good choice as a representation to be used for ice sheet modelling, and hence, model intercomparisons.

Continued progress in GHF estimation will require both methodological innovation and improved data coverage. Integrating machine learning with physics-based models, fostering cross-disciplinary data integration, and increasing spatial resolution are key priorities. In the context of ISMIP7, we recommend moving beyond outdated or purely interpolated GHF products and adopting modern, data-driven fields that better reflect current understanding.