Bathymetric control of tidewater glacier mass loss in northwest Greenland
Introduction
The mass budget of the Greenland ice sheet has decreased from over the period 1992–2000 to over the period 2002–2011, contributing to a rise in global mean sea level since 1992 (Rignot et al., 2012, Shepherd et al., 2012). Most of the ice sheet's mass loss is occurring at its margins, but the pattern of change is complex. There is considerable spatial and temporal variability in the observed ice surface velocity (Moon et al., 2012, Padman et al., 2012, Rignot and Jacobs, 2002) and mass wastage (Jakobsson et al., 2012, Kjeldsen et al., 2013, Pritchard et al., 2009, Shepherd et al., 2012) of outlet glaciers, complicating regional interpretations of change. Although tidewater glaciers in northwest Greenland showed an overall acceleration from 2000–2010, the changes in ice speed were not uniform (Melling et al., 2001, Moon et al., 2012). In several instances, while one glacier sped up dramatically, its neighbors accelerated less or even slowed. This large degree of spatial variability precludes the scaling up of local thinning rates to ice sheet-wide mass wastage estimates (Gardner et al., 2013, Rignot et al., 2012), while the interannual variability hampers extrapolation of these trends into the future. Understanding this observed variability is the next step in identifying the first-order components of the tidewater glacier system.
The external forcings of a tidewater glacier system that contribute to decadal scale glacier advance and retreat are surface energy and mass balance (SMB) (Box et al., 2012, O'Leary and Christoffersen, 2013), ocean heat content (Xu et al., 2012), and the subglacial environment (e.g. geothermal heat flux and subglacial and englacial hydrology) (Phillips et al., 2013). Adequate constraints of these forcings remain elusive due to both the inaccessibility and spatial variability of the glacial environments. This presents a significant challenge to understanding the observed variability in glacier retreat in Alaska, Greenland, and Antarctica.
Ice flow models have suggested that tidewater glaciers are most sensitive to forcing at the terminus (Nick et al., 2009), with the thinning and speed up response propagating inland (Howat et al., 2007). Furthermore, marine-terminating glaciers are most sensitive to melting at the base of the grounded ice at the grounding line (O'Leary and Christoffersen, 2013, Reeh, 1968). The grounding line is typically the site of the largest thermal forcing, the difference between the temperature of warm, deep water and the freezing point of salt water (Jacobs et al., 2012). The bed topography beneath the grounded outlet glacier may control the extent of the retreat (Enderlin et al., 2013, Schoof, 2007) while the fjord bathymetry controls the access of relatively warm water to the ice front at the grounding line (Holland et al., 2008).
Here, we analyze a pair of neighboring glaciers to minimize the differences in external forcings between the two systems. This case study approach assumes the glaciers terminating in the same fjord will experience similar changes in ocean properties. We also assume the subglacial thermal and hydrological environment is similar between neighboring glaciers. Finally, while SMB can vary widely across Greenland (Vernon et al., 2012), proximal glaciers will have similar SMB forcings. We analyze Tracy and Heilprin Glaciers, two similarly sized neighboring glaciers in northwest Greenland that both empty into Inglefield Gulf (Fig. 1).
Section snippets
Tracy and Heilprin Glaciers
Tracy and Heilprin Glaciers are the widest (∼5 km) of the marine-terminating glaciers that flow into Inglefield Gulf in NW Greenland (77°N) (Fig. 1). A 115-year record of terminus positions of Tracy and Heilprin Glaciers, compiled from reports of early Arctic explorers, geologists, and more recently aerial and satellite images, reveal disparate long term mass-wasting of these two neighboring glaciers (Dawes and van As, 2010). At the start of the 20th century, the terminus of Tracy Glacier
Mass wastage and surface lowering
We use NASA Airborne Topographic Mapper (ATM) lidar (Krabill et al., 2002) to detect surface elevation change rates using airborne altimetry. We derive thinning rate estimates from coincident ice surface elevation measurements (Martin et al., 2012). We focus mostly on springtime comparisons of along-flight repeat surface elevation measurements to have confidence that thinning rates are due to the large-scale mass wastage of the ice sheet instead of seasonal changes. From 1994–1999, flights over
Bathymetry from inversion of IceBridge gravity data
We used Operation IceBridge gravity data to invert for bathymetry beneath Inglefield Gulf at the terminus of the two glaciers. OIB gravity data were obtained with a Sander Geophysics AIRGrav airborne gravimeter (Argyle et al., 2000, Sander et al., 2004). The AIRGrav system provides high-quality data during draped flights, flown at a constant elevation above the ice surface (Studinger et al., 2008), such as the OIB centerline flights along Tracy and Heilprin Glaciers, flown at a nominal height
A mass balance approach for estimating ocean forcing
Following Hulbe et al. (2013), we write out the mass balance equation as follows: where is the mass balance from integrating ATM thinning rates (discussed in Section 3.1), is surface accumulation from the Regional Arctic Climate MOdel version II for GReenland (RACMO2/GR) (van Angelen et al., 2012) integrated over the surface catchment area, is mass flux (described in Section 3.2), and is ocean forcing. As discussed above in Section 3, the mass flux term is
Conclusions
Defining and quantifying the impact of fjord bathymetry (including the depth of the grounding line, the presence of sills, and troughs across the shelf) on glacier mass loss is crucial for modeling the interactions between warm Atlantic Water and deep-grounded ice, ultimately improving estimates of mass wastage and sea level rise. We show that airborne gravity inversions of fjord bathymetry, although inherently limited in resolution due to the height and groundspeed of the airplane, have proven
Acknowledgments
The authors would like to thank very helpful assistance from Indrani Das, Tim Creyts, Andreas Münchow, and Ben Smith, for their assistance in developing this paper. Jan van Angelen provided the RACMO2/GR surface accumulation data. This project was funded through NASA grants NNX12AB70G, NNX10AT69G, and NNX13AD25A.
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