Greenland Geothermal Heat Flow Database and Map (Version 1)

Abstract

Abstract. We compile and analyze all available geothermal heat flow measurements collected in and around Greenland into a new database of 419 sites and generate an accompanying spatial map. This database includes 290 sites previously reported by the International Heat Flow Commission (IHFC), for which we now standardize measurement and metadata quality. This database also includes 129 new sites, which have not been previously reported by the IHFC. These new sites consist of 88 offshore measurements and 41 onshore measurements, of which 24 are subglacial. We employ machine learning to synthesize these in situ measurements into a gridded geothermal heat flow model that is consistent across both continental and marine areas in and around Greenland. This model has a native horizontal resolution of 55 km. In comparison to five existing Greenland geothermal heat flow models, our model has the lowest mean geothermal heat flow for Greenland onshore areas. Our modeled heat flow in central North Greenland is highly sensitive to whether the NGRIP (North GReenland Ice core Project) elevated heat flow anomaly is included in the training dataset. Our model's most distinctive spatial feature is pronounced low geothermal heat flow (< 40 mW m−2) across the North Atlantic Craton of southern Greenland. Crucially, our model does not show an area of elevated heat flow that might be interpreted as remnant from the Icelandic plume track. Finally, we discuss the substantial influence of paleoclimatic and other corrections on geothermal heat flow measurements in Greenland. The in situ measurement database and gridded heat flow model, as well as other supporting materials, are freely available from the GEUS Dataverse (https://doi.org/10.22008/FK2/F9P03L; Colgan and Wansing, 2021).

GBaTSv2: a revised synthesis of the likely basal thermal state of the Greenland Ice Sheet

“…Drilling was completed in 2012, and repeat logging of borehole temperature after the 2011 profile reported by MacGregor et al (2015a) confirms a basal temperature of ∼ −3.5 • C, inferred from the deepest englacial thermistor. However, subsequent logging directly at the base measured a higher temperature of −2.4 • C, presumed to be due to the presence of subglacial water (Colgan et al, 2022). Combined with the recovery of several meters of refrozen, debris-rich ice from the bottom of the NEEM core (Dorthe Dahl-Jensen, personal communication, 2021), these observations indicate that the base of the NEEM ice core is thawed rather than frozen, as previously estimated by M16.…”

“…9b). This difference is not attributable to a new geothermal flux field, because most models from both ensembles use the older geothermal flux field derived from seismic data of Shapiro and Ritzwoller (2004) rather than a more recent field derived from aeromagnetic data (Martos et al, 2018) or machine learning (Colgan et al, 2022). Most ISMIP6 models used the IceBridge BedMachine Greenland v3 bed topography, which on average results in thicker ice than the various bed topographies used by SeaRISE.…”

On the Relation Between Basal Erosion of the Lithosphere and Surface Heat Flux for Continental Plume Tracks

“…Finally, there are two examples of plume‐craton interaction for which extensive focus has been placed on heat flux: Marie Byrd Land in Antarctica (Lösing et al., 2020; Maule et al., 2005; Seroussi et al., 2017; Shen et al., 2020), and the Iceland plume in Greenland (e.g., Colgan et al., 2021; Martos et al., 2018). In both locations, the heat flux associated with the plume can have significant effects on the melting rates of ice (Rogozhina et al., 2016; Rysgaard et al., 2018; Smith‐Johnsen et al., 2020).…”

Geologic Provinces Beneath the Greenland Ice Sheet Constrained by Geophysical Data Synthesis

“…Another application could be exploring relations between these apparent province boundaries and other subglacial properties of geophysical, glaciological, geomorphological or geochemical interest, such as geothermal heat flow (Jones et al., 2021), bedrock erodibility (Campforts et al., 2020), basal friction (Maier et al., 2022), drainage history (Jess et al., 2020; Keisling et al., 2020), or isotope geochemistry (Briner et al., 2022; Colville et al., 2011). While our results were based on conventional manual delineation of province boundaries and interpretation, machine learning techniques could also be applied to reveal such structures with reduced influence from expert biases (e.g., Colgan et al., 2022; Li et al., 2022; Rezvanbehbahani et al., 2017).…”

“…The ice sheet's large‐scale flow pattern, its discharge into the surrounding oceans and the island's response to changing ice loading are all influenced by solid‐Earth boundary conditions that are obscured by the GrIS and thus difficult to constrain. The solid‐Earth boundary conditions that have received the most attention are its subglacial topography, geothermal heat flux, crustal geology and mantle viscosity (e.g., Adhikari et al., 2021; Alley et al., 2019; Braun et al., 2007; Colgan et al., 2022; Martos et al., 2018; Morlighem et al., 2017; Rezvanbehbahani et al., 2017; Rogozhina et al., 2016). These properties are potentially related, for example, a geologically young province with a rough topographic surface may have a higher geothermal heat flux and overlie a less viscous mantle, but these relations remain difficult to constrain precisely despite decades of investigation.…”