Constraining the geothermal heat flux in Greenland at regions of radar-detected basal water

Abstract

The spatial distribution of basal water critically impacts the evolution of ice sheets. Current estimates of basal water distribution beneath the Greenland Ice Sheet (GrIS) contain large uncertainties due to poorly constrained boundary conditions, primarily from geothermal heat flux (GHF). The existing GHF models often contradict each other and implementing them in numerical ice-sheet models cannot reproduce the measured temperatures at ice core locations. Here we utilize two datasets of radar-detected basal water in Greenland to constrain the GHF at regions with a thawed bed. Using the three-dimensional ice-sheet model SICOPOLIS, we iteratively adjust the GHF to find the minimum GHF required to reach the bed to the pressure melting point, GHFpmp, at locations of radar-detected basal water. We identify parts of the central-east, south and northwest Greenland with significantly high GHFpmp. Conversely, we find that the majority of low-elevation regions of west Greenland and parts of northeast have very low GHFpmp. We compare the estimated constraints with the available GHF models for Greenland and show that GHF models often do not honor the estimated constraints. Our results highlight the need for community effort to reconcile the discrepancies between radar data, GHF models, and ice core information.

Five decades of radioglaciology

“…The reflection coefficient can provide a constraint on where the bed is frozen or thawed, the reach and character of ocean water at the grounding line, and basal conditions of ice streams (Peters and others, 2005; Jacobel and others, 2009; Ashmore and others, 2014; Christianson and others, 2016). The presence and volume of inferred basal water bodies have also been used to place constraints on the basal thermal state and/or geothermal flux, while layer drawdown has also been used to constrain basal melt rates and geothermal flux (Fahnestock and others, 2001; Catania and others, 2006; Buchardt and Dahl-Jensen, 2007; Schroeder and others, 2014b; Rezvanbehbahani and others, 2017, 2019; Seroussi and others, 2017; Jordan and others, 2018a,b).…”

Greenland ice sheet mass balance from 1840 through next week

“…Due to a lack of direct observations, the geothermal flux is poorly constrained under most of the Greenland ice sheet. Different approaches have been employed to infer the value of the BMB GF often with diverging results (see e.g., Rogozhina et al (2012); Rezvanbehbahani et al (2019)). Lacking substantial validation that favours one BMB GF map over the others, Karlsson et al (2021) instead use the average of three widely used BMB GF estimates: Fox Maule et al ( 2009); Shapiro and Ritzwoller (2004), and Martos et al (2018).…”

Topographic Correction of Geothermal Heat Flux in Greenland and Antarctica

“…Subglacial ridges are also cooled by thinner overlying ice, which increases the pressure‐melting‐point temperature relative to warm valleys overlaid by thick ice. The combination of decreased local geothermal heat flux and increased local pressure‐melting‐point temperature is expected to result in sharp spatial contrasts in basal thermal conditions that promote preferential refreezing of subglacial water at cold subglacial ridges (Rezvanbehbahani et al., 2019).…”

“…The apparent spatial discontinuity of basal water identifications beneath the Greenland ice sheet represents an unresolved challenge to larger‐scale but smoother inferences of that ice sheet's basal thermal state (Chu et al., 2018; Jordan et al., 2018; MacGregor et al., 2016; Oswald et al., 2018; Rezvanbehbahani et al., 2019). Similarly, the distribution of subglacial lakes beneath the Antarctic and Greenland ice sheets may partly reflect such basal thermal state transitions (e.g., Bowling et al., 2019; Smith et al., 2009).…”

“…The apparent spatial discontinuity of basal water identifications beneath the Greenland ice sheet represents an unresolved challenge to larger-scale but smoother inferences of that ice sheet's basal thermal state (Chu et al, 2018;Jordan et al, 2018;MacGregor et al, 2016;Oswald et al, 2018;Rezvanbehbahani et al, 2019).…”