Introduction
Grounding zones are located between the most landward site of ice flexure from tidal movement and the most landward site where the ice reaches approximate hydrostatic equilibrium (Reference VaughanVaughan, 1994; Reference Fricker and PadmanFricker and Padman, 2006). They are typically several kilometers long (Reference Brunt, Fricker, Padman, Scambos and O’NeelBrunt and others, 2010), but can be as long as 20–30km depending on the strength of tides and the elastic properties of ice (Reference Sykes, Murray and LuckmanSykes and others, 2009). Because the flow of upstream ice is strongly controlled by the grounding zones (e.g. Reference SchoofSchoof, 2007) there is strong motivation to improve understanding of conditions at the basal interface across the grounding zones.
Interpretation of basal conditions across grounding lines from radar data is complicated because the basal interface in the vicinity of grounding zones is subject to influences from ocean water, sediment-rich glacier meltwater from upstream, sediments and bedrock properties. For example, Reference MacGregor, Anandakrishnan, Catania and WinebrennerMacGregor and others (2011) examined radar power returned from the basal interface along 11 profiles across the Siple Coast (West Antarctica) grounding zone. Results showed no strong contrast in basal reflectivity, which was attributed to a thin (>~0.2 m) water film that extended several kilometers upstream of the grounding zone.
Here we present radar data collected across an ice-rise promontory and the adjacent ice shelf in Dronning Maud Land, East Antarctica (Fig. 1). To derive a proxy of basal conditions, we calculated englacial attenuation using two different methods: one employs a widely used radar algorithm and the other uses a temperature-dependent attenuation model with input from thermomechanical ice-flow models. We discuss the differences in basal conditions inferred from these methods.
Methods
Radar/GPS profiling
A 42 km long profile was made from the ice-rise promontory to the adjacent ice shelf (Figs 1 and 2). We used a 5MHz ground-based radar-profiling system positioned with a geodetic L1 GPS receiver (Reference Pattyn, Matsuoka and BertePattyn and others, 2010). Radio-wave propagation speed in ice is assumed to be 168.4mμs–1, which corresponds to permittivity of 3.17. Surface topography was determined by a kinematic GPS survey using a temporary base station located near the crest of the ice promontory. The position of the base station in the International Terrestrial Reference Frame was determined by the Precise Point Positioning method. Earth Gravitational Model 1996 (EGM96) shows that the geoid height is ~24m above the World Geodetic System 1984 ellipsoidal elevation (WGS84) in the vicinity of the grounding zone and the floating ice that we surveyed. Therefore, we added 24 m to the GPS-measured elevations in order to derive elevations relative to regional sea level.
The measured radar power P basal returned from the base of the ice column is affected by instrumental factors S, geometrical factors G basal, two-way englacial attenuation L ice and basal reflectivity R basal. The relationship between these factors in the decibel scale ([x]dB = 10 log10 x) can be written as (e.g. Reference Matsuoka, Morse and RaymondMatsuoka and others, 2010)
Figure 2a shows the absence of englacial scatters such as buried crevasses, so losses from L ice and G basal are expected to dominate. The ratio of the ice thickness (up to 700 m) to the radio-wave wavelength (~30 m) is small, so extinction of power due to birefringence caused by alignments of ice crystals is probably insignificant (Reference Matsuoka, Gades, Conway, Catania and RaymondMatsuoka and others, 2009a). Therefore, Equation (1) is a reasonable approximation for our analysis.
The geometric factor G basal is a function of ice thickness H and depth-averaged permittivity ε (assumed to be 3.17): . G basal varies by ~10 dB for ice-thickness variations between 200 and 700 m, but it is negligibly affected by possible variations of the depth-averaged permittivity (i.e. density). Therefore, assuming that instrumental factors S remain stable over time, variations in the geometrically corrected returned power Pc basal are caused by variations in englacial attenuation and basal reflectivity:
Values for Pc basal come from measurements of returned power and ice thickness (calculated from the two-way travel time). Here we derive an accurate estimate L ice in order to calculate [Pc basal]dB + [L ice]dB along the profile, thereby providing a proxy of spatial variations of [R basal]dB.
Attenuation estimates
We estimated depth-averaged englacial attenuation rates in two ways. The first method uses measurements of the geometrically corrected returned power as a function of ice thickness (e.g. Reference Winebrenner, Smith, Catania, Conway and RaymondWinebrenner and others, 2003; Reference Jacobel, Welch, Osterhouse, Pettersson and MacGregorJacobel and others, 2009). The thickness dependence of the returned power can be used as a proxy for englacial attenuation if the basal reflectivity is independent of ice thickness, that is when , (Equation (2)). This method is appropriate when englacial losses (e.g. scattering from buried crevasses) other than G basal and L ice are significant (e.g. Reference Raymond, Catania, Nereson and Van der VeenRaymond and others, 2006).
The second method uses an attenuation model that depends on depth profiles of ice temperature and chemistry. Englacial attenuation is a result of contributions from pure ice, acidity and sea salt in the ice column, which have different temperature dependences. However, the lack of information on depth profiles of chemistry precludes calculating the contributions from acidity and sea salt, and here we consider only the pure-ice contribution. Acidity and sea salt contribute 26% and 21% of the total depth-averaged attenuation rate at Siple Dome and Vostok ice-core sites, respectively (Reference Matsuoka, MacGregor, Pattyn and CroccoMatsuoka and others, 2011). The local one-way attenuation rate N (dBkm–1) is
Here σ pure = 9.2 μsm–1, E pure = 0.51 eV, T r = 251 K and k is the Boltzmann constant (Reference MacGregor, Winebrenner, Conway, Matsuoka, Mayewski and ClowMacGregor and others, 2007; Reference MatsuokaMatsuoka, 2011). These values have significant uncertainties because there are few published measurements of the temperature dependence of dielectric properties. Consequently, uncertainty in attenuation sensitivity to ice temperature and in estimated attenuation is also large. We ignore this uncertainty in the analysis below.
The ice temperature T for the attenuation model (Equation (3)) is calculated using a two-dimensional (2-D) thermomechanical high-order model (Reference PattynPattyn, 2002, Reference Pattyn2003). The model calculates the horizontal velocity field in the ice sheet using higher-order physics, taking into account vertical shearing as well as longitudinal stress gradient. The velocity fields for both the ice sheet and ice shelf are derived simultaneously. Vertical velocities are obtained from mass conservation and by considering the present-day ice topography in steady state (Reference HindmarshHindmarsh, 1999). The velocity field is fully coupled to the temperature field, based on vertical diffusion, horizontal and vertical advection and friction. Flow enhancement factor m is assumed to be uniform at 0.8 or 1.0. Boundary conditions to the ice-flow field are obtained from balance velocity calculations at either side of the profile presented in Figure 2, and a basal friction parameter at the bottom, relating basal velocities to basal shear stress (Reference Pattyn, Huyghe, de Brabander and De SmedtPattyn and others, 2006). Basal friction in the ice shelf is set to be zero.
Surface temperature T s over the entire profile and geothermal flux GF over the grounded ice are assumed to be uniform: T s = –12˚C and GF = 42 or 54 mWm–2. Since the model is not coupled with the ocean, a temperature of –2˚C, an approximate melting point of sea water corrected for pressure at depth, is prescribed at the ice–water interface of floating ice. In this area, neither measurements nor model estimates of ocean temperature have been made. Surface accumulation rates are determined from the shallowest radar-reflector pattern and a regional mean of the recent accumulation rate of 0.27ma–1 from a continental mass-balance model (Reference PattynPattyn and others, in press). For each geothermal flux and flow-enhancement factor, the model was run more than 20 000 years until the ice-flow and temperature fields reached a steady state.
The radar transect across the ice promontory was aligned perpendicular to surface contours, which is an approximation of the ice-flow direction. However, the radar transect on the ice shelf may deviate from the flowline. There are no depth variations of ice-flow speed over the ice shelf (plug flow), so the vertical velocity profile is linear so that the steady-state depth profile of temperature is a function of vertical advection rates and constrained by the upper and lower surface temperatures, regardless of the upstream ice-flow field (e.g. Reference HindmarshHindmarsh, 1999). Therefore, the effects of transverse stress coupling and the deviation of the radar profile from the true flowline on the estimated temperature field are expected to be small, as horizontal (advection) effects are negligible.
Results and Discussion
Radar and GPS measurements
Figure 2a shows a radargram with surface elevation adjustments using GPS-measured surface elevations z s. Figure 2b shows details of the surface topography in the vicinity of the grounding zone, and Figure 2c shows δz = z s – z float, where z float is the thickness of freely floating ice that can be derived from the ice thickness H and densities of ice ρ i and of ocean water ρ w:
When ice is in hydraulic equilibrium (and all ρ i, ρ w and H are accurate), δz is zero. In earlier work we showed that δz is minimal over the downstream side (x a > 25.6 km) of this profile (Reference PattynPattyn and others, in press. At landward sites (x a < 25.6 km), δz increases rapidly, so the ice is no longer in hydrostatic equilibrium. Therefore, we determined that the most landward site of freely floating ice is at x a = 25.6 km.
We did not find a topographic minimum or a break in slope associated with the non-hydrostatic ice flexure response typically found in grounding zones (Reference Brunt, Fricker, Padman, Scambos and O’NeelBrunt and others, 2010). Although our repeat GPS profiles between the ice promontory and the ice shelf do show some changes in elevation at sites landward of freely floating ice, they do not allow us to determine the most landward site affected by tidal forcing.
Attenuation estimates using thermomechanical model
Figure 3 shows englacial attenuation rates N estimated using the thermomechanical model for (GF,m) = (54mWm–2, 1.0). In the model, we prescribe the grounding line at x a = 25.6 km, although in reality it is slightly landward of this position. Ice temperature increases with depth monotonically, as does the attenuation rate. The model predicts that the basal temperature of grounded ice is at the pressure-melting point, except for the vicinity of the ice-rise crest when the geothermal flux is 54 mWm–2 regardless of the flow-enhancement factor. For a geothermal flux of 42 mWm–2, the basal temperature of the grounded ice is below the pressure-melting point by several degrees.
Figure 2d shows the spatial pattern of depth-averaged attenuation rate ⟨N⟩, which is derived by integrating local attenuation rates N (Fig. 3) vertically at sites along the profile. Total attenuation [L ice]dB is proportional to the ice thickness H and the depth-averaged attenuation rate ⟨N⟩: [L ice]dB = 2⟨N⟩ H[ (the factor of 2 is to account for the two-way travel). Although ⟨N⟩ increases with geothermal flux GF and decreases with flow-enhancement factor m, the amplitudes of ⟨N⟩ variations along the profile are 1.3– 1.7 dBkm–1 and the spatial pattern remains similar regardless of GF and m (Fig. 2d). Differences in the flow-enhancement factors have negligible effects on ⟨N⟩.
It is still an open question whether the temperature in Equation (3) is relative to the pressure-melting point, because all dielectric properties used to determine σ pure and E pure were measured with meteoric or laboratory-grown ice at the standard atmospheric pressure, so the (pressure-) melting point of the ice specimen for those measurements is close to 0˚C. If an attenuation approximation (Equation (3)) is more appropriate for temperature relative to the pressure-melting point, then the estimated variations in ⟨N⟩ over the shelf ice would be larger than those shown in Figure 2 by ~1dBkm–1. This difference is nearly uniform along the profile, so this uncertainty in the attenuation parameterization (Equation (3)) does not significantly affect our interpretations of the basal environment.
Basal returned power dependence on ice thickness
Figure 4 shows basal returned power dependence on ice thickness for four linear fits: (1) for the entire dataset; (2) for floating ice 5 km or more seaward of the prescribed grounding line; (3) for grounded ice 5 km or more landward of the grounding line; and (4) in the vicinity (±5 km) of the grounding line. The attenuation rate 〈N〉 varies by a factor of 2, depending on the choice of data ensembles used in the fit (Fig. 4): 58 dB km–1 (all data), 56 dB km–1 (floating ice), 38 dB km–1 (grounding zone) and 28 dB km–1 (grounded ice). In contrast, results from the temperature-dependent attenuation model (Equation (3)) indicate relatively uniform depth-averaged values, 30–33 dB km–1 (Fig. 2d). As discussed earlier, the temperature-dependent attenuation model used here does not account for contributions from ice chemistry, which could increase these calculated 〈N〉 by ~10 dB km–1 if sea salt of 17 μmol L–1 is included in the ice.
The thickness dependence of the basal returned power does not give a regional mean attenuation rate when the attenuation rates vary significantly in the data ensemble or the bed reflectivity depends on ice thickness (Reference MatsuokaMatsuoka, 2011). Along our profile, the attenuation rate estimated from the attenuation temperature model is nearly uniform within ±1dBkm–1 (Fig. 2d). However, the grounded ice is generally thicker than the floating ice, and a significant thickness variation is found in the floating ice (Fig. 4; color of markers show the locations along the profile (see Fig. 2)). These features yield apparent thickness dependence of the basal reflectivity, which is a likely reason why attenuation rates estimated with the thickness dependences of the basal returned power do not match well with the model estimates.
Inferring conditions at the basal interface
Although the radar instrument factor is unknown, the transmitter used here is known to be stable (Reference Matsuoka, Wilen, Hurley and RaymondMatsuoka and others, 2009b). So, [Pc basal]dB + [L ice]dB provides a proxy of spatial variations of [R basal]dB (Equation (1)). The anomalous basal returned power Δ[Pc basal]dB from values predicted with the traditional radar method (Fig. 4) also provides a proxy of spatial variations of [R basal]dB:
Figure 2e shows Δ[Pc basal]dB anomalies from the mean of Δ[Pc basal]dB for each data ensemble along the profile as a proxy of relative basal reflectivity. Attenuation-rate estimates depend on the geothermal flux (Fig. 2d), but the spatial patterns of [R basal]dB estimated here are not sensitive to the magnitude of the geothermal flux because the ‘pattern’ of ⟨N⟩ is controlled primarily by the ‘pattern’ of ice thickness and accumulation rate.
Figure 2e shows four distinct features in [R basal]dB estimated with attenuation modeling and in Δ[Pc basal]dB. First, Δ[Pc basal]dB for the entire dataset show similar values for the grounded ice and floating ice in general, although basal conditions for the grounded and floating ice are presumably distinct. Near the profile end on the floating ice (x a >~35 km), Δ[Pc basal]dB for the entire profile and for the floating ice are smaller than for the grounded ice. However, radar-measured ice thickness gives surface elevation for the freely floating ice consistent with the GPS-measured elevation over this area (Fig. 2b). The presence of marine ice is therefore unlikely, and basal conditions should be more or less constant over the floating ice. Also, attenuation estimates used for these Δ[Pc basal]dB over the entire profile and over the floating ice are extremely high (56–58 dB km–1 for one way). Therefore, we conclude that these Δ[Pc basal]dB values for the entire dataset and for the floating ice do not represent variations in the basal conditions.
Second, Δ[Pc basal]dB for the grounding-line vicinity varies ~20 dB. This variation happens in the horizontal distance of ~5 km. A similar feature is found in [R basal]dB estimated with attenuation modeling. In the grounding-line vicinity, the modeling predicts an attenuation variation less than 1 dB km–1 for one way; the ice thickness varies <150m in this area, giving minimal variations in the total attenuation [L ice]dB within the grounding zone. Thus, the predicted variations in [R basal]dB are essentially identical to variations in [P c basal]dB. In practice, basal reflectivity is insensitive to the attenuation estimates in such areas where the ice thickness and attenuation rate vary little.
Third, [R basal]dB estimated with attenuation modeling has a broad minimum near the crest (x a =~12 km). It becomes larger towards both ends of the profile over the grounded ice. This pattern is also found in the modeled basal temperature, when geothermal flux is 54 mWm–2 (Fig. 3). The range of [R basal]dB over the grounded ice is ~20 dB from the crest to the western end of the profile and 10 dB from the crest to the grounding line. However, basal reflectivity is related to the local amount of water, rather than local melting rate, so our 2-D modeling cannot be used to constrain the flow-model parameters such as geothermal flux, which alter the ice temperature, using the pattern of the observed bed reflectivity.
Finally, variations of Δ[Pc basal]dB depend on data ensembles used for constructing the fit between returned power and ice thickness (Fig. 4). For example, 〈d[P c basal]dB /dH〉H derived for the floating ice is –144 or –112 dB km–1 when the data ensemble includes or excludes, respectively, the 5 km portion of the profile close to the grounding line. However, 〈d[P c basal]dB /dH〉H derived for the grounded ice varies only 3dBkm–1 if the data ensemble includes or excludes the grounding-line vicinity. Therefore, the analysis of the spatial pattern of Δ[Pc basal]dB is not rigorous. [R basal]dB derived from four modeled temperature-dependent attenuation rates show similar spatial patterns (Fig. 2e). These results suggest that basal conditions revealed by the temperature-dependent attenuation modeling are robust despite uncertainties in the modeling parameters and boundary conditions.
Conclusions
A sharp increase in basal reflectivity was found in the vicinity of the grounding zone using a temperature-dependent attenuation model in combination with a thermomechanical model to estimate temperature profiles in the ice. This increase is consistent with a step change in the basal environment from a grounded (possibly wet) bed to an ice– ocean interface. This conclusion is robust even with the inherent uncertainties in the model, such as geothermal flux, flow-enhancement factor and location of the grounding line. Such a step change is also detected using a traditional radar method that assumes uniform attenuation rate, probably because variations in attenuation in this area are minimal. However, the radar method and temperature-dependent modeling give distinctly different patterns of anomalous basal reflectivity over the grounded ice and over the floating ice. The results argue strongly for a temperature-dependent attenuation model, when the radar returned power is analyzed to extract a proxy of basal conditions.
Acknowledgements
We acknowledge logistic support from the Belgian Antarctic Research Expedition (BELARE). This project was supported by the Belgian Federal Science Policy Office (grant No.: EA/ 11/3A), the University of Washington Royalty fund (grant No.: 4208) and the Center for Ice, Climate and Ecosystems at the Norwegian Polar Institute. We are indebted to A. Hubert, R. Wagemans, K. Soete and other BELARE field participants for assistance in the field. D.C. is funded by an FNRS–FRIA scholarship and by the YGGDRASIL mobility program, Research Council of Norway. Comments by Sasha Carter, an anonymous reviewer and the scientific editor, Poul Christoffersen, improved the paper significantly.