Status: this preprint is open for discussion and under review for The Cryosphere (TC).
Greenland fjord processes have a depth-dependent influence on predicted submarine melt rates
Emma F. Cameron,Tom R. Cowton,Alexander T. Bradley,and Paul R. Holland
Abstract. Recent ice loss from the Greenland Ice Sheet has been driven in part by the retreat of marine-terminating glaciers in response to ocean warming. Efforts to quantify ocean forcing often rely on far-field ocean properties, which differ from those adjacent to glacier termini in fjords. To quantify these differences and their significance for glacier ablation, we analyse 58 pairs of near-glacier and fjord-mouth conductivity-temperature-depth measurements from 38 fjords around Greenland collected between 2016 and 2021. Relative to fjord mouth properties, near-glacier profiles show consistent near-surface cooling, attributed to iceberg melt, and intermediate-depth warming caused by plume-driven upwelling of deeper waters. Available results from Southeast Greenland appear different, with near-glacier waters colder and fresher than fjord mouths at all depths. Our results show that while it is generally reasonable to use shelf water properties to model submarine melt at depths > 250 m (except for fjords with shallow sills), this approach will significantly overestimate melt near the surface and underestimate at mid depth, potentially influencing the predicted rate of glacier ablation.
Received: 22 Sep 2026 – Discussion started: 02 Oct 2026
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Review of Cameron et al. 2026: Greenland fjord processes have a depth-dependent influence on predicted submarine melt rates
Review by Jesse Cusack, Oregon State University, Oct 21, 2026.
Thermal forcing, the difference between the ocean temperature at some reference location and ice interface freezing temperature, is often used to quantify glacier melt rates in parameterizations. The authors use CTD observations from Greenland to show that thermal forcing estimates are sensitive to which part of the ocean you use as your reference. They demonstrate that the thermal forcing calculated using data from fjord mouths is different in vertical structure to that estimated using profiles from closer to glacier termini, with consequences of estimate melt rates. The difference is attributed to water modification processes taking place in fjords, such as iceberg melting, plumes, and mixing.
Overall, I thought this was a well written and concise analysis with a useful message; that we should think about how we define thermal forcing and its depth dependence. I only had minor comments. For convenience I have attached an annotated PDF with my comments for the authors. Below, I rehash one of the more important (but still minor) comments.
Missed variability. With only one pair of profiles for most fjords, it is not possible to estimate the uncertainty due to intrinsic variability in the system. I am not intimately familiar with the details of the OMG dataset, so perhaps that is just the data available. However, if there are any fjords which contain more profiles in the near terminus region < 10 km, then they could be used to assess the variability and provide some more confidence in the result. Of course, mélange or other logistical constraints restrict spatial sampling. I would certainly expect more spatial and temporal variability near the surface depending on the nature of the discharge flow and the presence of big icebergs. I might expect the surface freshening signal that you see to keep getting stronger toward the terminus as the concentration of icebergs and bergy bits gets higher. I note that 10 km is still quite a long way away from the terminus.
CTD Analysis and Figure Scripts for "Greenland Fjord Processes Have a Depth-Dependent Influence on Predicted Submarine Melt Rates" (v2.0)Emma F. Cameron, Tom R. Cowton, Alexander T. Bradley, Paul R. Holland https://doi.org/10.5281/zenodo.22769296
Emma F. Cameron,Tom R. Cowton,Alexander T. Bradley,and Paul R. Holland
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Many of Greenland’s glaciers end in fjords, where they are melted by the ocean. Fjords are too small to resolve in ocean models, so melt rates are often estimated from offshore temperatures. We compared temperatures in 38 fjords from mouth to interior: change below 250 metres is small, but in the upper 250 metres, water near glaciers is warmer at mid-depth yet colder at the surface than offshore. These observations can inform use of offshore temperatures to predict near-glacier melt rates.
Many of Greenland’s glaciers end in fjords, where they are melted by the ocean. Fjords are too...
Review of Cameron et al. 2026: Greenland fjord processes have a depth-dependent influence on predicted submarine melt rates
Review by Jesse Cusack, Oregon State University, Oct 21, 2026.
Thermal forcing, the difference between the ocean temperature at some reference location and ice interface freezing temperature, is often used to quantify glacier melt rates in parameterizations. The authors use CTD observations from Greenland to show that thermal forcing estimates are sensitive to which part of the ocean you use as your reference. They demonstrate that the thermal forcing calculated using data from fjord mouths is different in vertical structure to that estimated using profiles from closer to glacier termini, with consequences of estimate melt rates. The difference is attributed to water modification processes taking place in fjords, such as iceberg melting, plumes, and mixing.
Overall, I thought this was a well written and concise analysis with a useful message; that we should think about how we define thermal forcing and its depth dependence. I only had minor comments. For convenience I have attached an annotated PDF with my comments for the authors. Below, I rehash one of the more important (but still minor) comments.
Missed variability. With only one pair of profiles for most fjords, it is not possible to estimate the uncertainty due to intrinsic variability in the system. I am not intimately familiar with the details of the OMG dataset, so perhaps that is just the data available. However, if there are any fjords which contain more profiles in the near terminus region < 10 km, then they could be used to assess the variability and provide some more confidence in the result. Of course, mélange or other logistical constraints restrict spatial sampling. I would certainly expect more spatial and temporal variability near the surface depending on the nature of the discharge flow and the presence of big icebergs. I might expect the surface freshening signal that you see to keep getting stronger toward the terminus as the concentration of icebergs and bergy bits gets higher. I note that 10 km is still quite a long way away from the terminus.