Glaciological setting and modeling efforts

The ice streams flow at roughly 400 m a^–1 despite having surface slopes and hence driving stresses orders of magnitude less than typical outlet glaciers (e.g. Byrd Glacier, Antarctica, or Jakobshavn Isbræ, Greenland). This high velocity is enabled by a several-meter thick layer of water-saturated dilatant till with a porosity that is capable of being increased, or dilated, by shear deformation (Reference Alley, Blankenship, Bentley and RooneyBlankenship and others, 1987). While there has been evolution in the ideas concerning how this till should be treated in models (e.g. as a viscous deforming till (Reference Alley, Blankenship, Bentley and RooneyAlley and others, 1987; Reference Kamb, Alley and BindschadlerKamb, 2001) or as a weak plastic bed (Reference KambKamb, 1991; Reference Tulaczyk and Kamb and EngelhardtTulaczyk and others, 2000a, b)), all ideas embrace basal water as an essential ingredient for the fast flow of these ice streams.

Early estimates predicted relatively large (~20 mm a^–1) basal melt beneath the Ross ice streams (Reference RoseRose, 1979; Reference Shabtaie and BentleyShabtaie and Bentley, 1987). Since then several studies (Reference Whillans, Bentley and van der VeenWhillans and others, 2001) have shown that ice-stream shear margins can support much of the driving stress, shifting the shear heating available to melt ice to the margins (Reference RaymondRaymond, 2000). Studies investigating the heat balance of ice streams have found that, at least in some well-lubricated areas, it is difficult to sustain basal melting (Reference Hulbe and MacAyealHulbe and MacAyeal, 1999; Reference RaymondRaymond, 2000). A modeling study has shown that, in the case of an undrained bed, Ice Stream C should rapidly freeze to the bed (Reference Bougamont, Tulaczyk and JoughinBougamont and others, 2003b). Other studies have suggested that the ice-stream tributaries and catchments provide sufficient melt to perhaps offset downstream freezing and enable fast motion (Reference Parizek, Alley, Anandakrishnan and ConwayParizek and others, 2002; Reference Bougamont, Tulaczyk and JoughinJoughin and others, 2003).

There are a number of feedbacks in a full thermodynamic ice-sheet model between ice-stream speed, basal lubrication and basal melt generation, making it difficult to reproduce both the current velocity and temperature distribution (Reference Hulbe and MacAyealHulbe and MacAyeal, 1999). Reference Bougamont, Tulaczyk and JoughinJoughin and others (2003) used measured velocities to estimate the basal melt beneath Whillans Ice Stream and Ice Stream C. The temperature model they used, however, did not include the effects of horizontal advection. Instead, they artificially adjusted the accumulation rate to match observed temperature profiles. The limitation of this method is that a parameter from a fit at one location is applied to the entire ice-stream catchment. A significant improvement can be made by using the measured velocity field to represent advective and heat-generation terms in numerical solutions for the temperature distribution and basal melt. Reference Vogel, Tulaczyk and JoughinVogel and others (2003) used measured velocities with a flowline model to include the effects of horizontal advection and achieved good agreement with measured temperature profiles without any fitting procedure. Here we use this approach over the catchments of Whillans Ice Stream and Ice Streams A, C and D. In addition, we improve upon past estimates by including internal strain heating and by using the velocity field to invert for the basal shear stress (e.g. Reference MacAyealMacAyeal, 1993b), which is needed to estimate basal shear heating. The remainder of this paper describes and discusses the results of this effort.

Geothermal heat flux

We used a spatially homogeneous value of G = 70 mW m^–2 in all our estimates, which is the value that was determined from a borehole at Siple Dome (Engelhardt, in press). Previously, Reference Alley and BentleyAlley and Bentley (1988) estimated even higher heat flow (~80 mW m^–2) from shallow borehole temperature measurements made on nearby ridge B/C. Temperature data from the deep borehole drilled at Byrd Station were used by Reference RoseRose (1979) to infer a lower geothermal flux of ~60 mW m^–2. The sensitivity of the basal melting estimate to G is approximately 1mm a^–1 change in m _r for a change in G of 10 mW m^–2. This level of sensitivity is consistent with results reported by Reference HulbeHulbe (1998). Although we do not rule out the presence of localized heat sources (e.g. Reference Blankenship, Bell, Hodge, Brozena, Behrendt and FinnBlankenship and others, 1993), we ignore such effects since the locations and magnitudes of any such sources are poorly constrained.

Temperature model

We solved for the temperature within the ice column lying atop a homogeneous bedrock slab with depth equal to one ice thickness. Following common practice (e.g. Reference HulbeHulbe, 1998), we neglect horizontal diffusion so that temperature within the ice is determined by the following simplified statement of thermal energy conservation:

where u, υ and w are respectively the x, y and z velocity components, and c _i is the thermal heat capacity for ice. Strain heating within the ice column is given by W in Equation (2). In the underlying bedrock we solve

which includes only thermal diffusion. These equations disregard possible heat advection due to groundwater flow, which we expect to be small.

The boundary condition at the ice-sheet surface is the specification of a surface temperature taken to be the mean annual surface temperature (Reference ComisoComiso, 1994, Reference Blankenship, Bentley, Rooney and Alley2000). At the bottom of the bedrock layer, the boundary condition is

where, as mentioned previously, G is the geothermal flux and k _r is the conductivity estimated for bedrock below the zone of any weathered or altered layers.

If the ice is frozen to the bed, Equations (2) and (3) are solved for temperature in the ice/bedrock column, subject to the upper- and lower-boundary conditions. If the bed is wet, Equations (2) and (3) are solved individually with the additional boundary condition that temperature equals the pressure-melting point, T _pmp, at the ice/bedrock interface.

The basal temperature gradient is an internal variable of the model described above, and is determined by solving Equations (2) and (3). For flexibility, an irregular grid is used to solve the numerical forms of the model equations, which allows variable horizontal resolution. Based on a simple analysis of the ice velocity data, to be described below, each node in the map view of the domain of interest is designated as an ice-sheet, tributary or ice-stream node. Slow-moving regions (e.g. ~25 m a^–1) were designated as ice-sheet nodes and fast-moving regions (~200 m a^–1) as ice-stream nodes. Nodes moving at intermediate speeds (~25–200 m a^–1) were classified as tributary nodes. While subjective, this simple discrimination between various regimes of ice flow follows common practice, and reflects best available experience in associating flow velocity regimes with ice-sheet flow styles. In Figure 1, the ice streams generally correspond to the red areas, the tributaries to the blue areas, and the ice sheet to the brown-green areas. Following MacAyeal (unpublished information, 1997), we recast Equations (2) and (3) to use a contour-following vertical coordinate and then solve them numerically.

Fig. 1. Ice-flow speed (colors) (Reference Bougamont, Tulaczyk and JoughinJoughin and others, 2002) over radar imagery from the RADARSAT Antarctic Mapping Project mosaic (Reference JezekJezek, 2002). Flow speed at100 m a^–1intervals is contoured with thin black lines. White vectors show subsampled velocity vectors in fast-moving areas. Catchment boundaries for individual ice streams are plotted with thick black lines. Red stars show borehole locations, and the blue star (FH shifted) shows a location discussed in the text.

We assume that most of the strain-heating rate is the result of vertical shear, W _vert, within the column and lateral shear at the margins, W _lat. Most of the heat from lateral shear is concentrated near the margin, and remains close to the margin even as it advects downstream. We assume that much of this heat, which is generated throughout the column, is advected across the grounding line before it has a significant effect on melt at the bed. Thus, we do not include W _lat in our model, and consequently we may slightly underestimate melt near the margins.

For ice motion arising solely from vertical shear, the strain heating can be calculated as (Reference PatersonPaterson, 1994)

The problem with this expression is that it is based on the shallow-ice approximation and, in practice, it does not necessarily conserve energy when applied to real data because it is proportional to . For example, with this equation an ice sheet with a smooth surface would generate much less heat than one with a very bumpy surface with the same mean slope. This is because other stresses are ignored that tend to smooth out the vertical strain rate near the bed at scales less than several ice thicknesses (e.g. at short length scales ice velocity does not fluctuate as (Reference Joughin, Tulaczyk, Bindschadler and PricePrice and others, 2002). Smoothing τ_d over several ice thicknesses potentially solves this problem, but it leaves the problems of what is the correct smoothing length to best conserve energy and smooth over sharp features such as shear margins.

Integration of Equation (5) over the ice thickness yields

for the total heat generated within the column. Since this expression is linear in τ _d, fluctuations in the driving stress may lead to local errors, but energy is conserved along the length of a flowline, provided there is an independent estimate of Ū _def. To estimate the heating within the column, we normalize the result from Equation (5) and multiply by the result from Equation (6). This may lead to errors in how the heating is distributed within the column, but unlike the direct application of Equation (5), energy should be conserved.

For the ice-sheet nodes in our model, we use the procedure just described to estimate the internal strain heating. For the tributary nodes, we partition the measured surface velocity into sliding and deformational components using the basal shear stress estimate. We then apply the above procedure using the basal shear stress in place of the driving stress to compute the strain heating. Since we use a shallow-ice approximation to partition the surface velocity into sliding and deformational components, we are subject to errors . Nevertheless, the combined basal shear heating and internal strain heating is capped at ~ U _measured τ_b. The main source of error relates to how we partition this fixed amount of heat generation between basal- and internal-shear heating. We expect that these types of errors tend to average out along flowlines. The sensitivity to errors in this assumption is described below. For the ice-stream nodes, we assume the vertical shear heating is negligible and ignore the lateral shear heating as described above.

We rely largely on interferometric synthetic aperture radar (InSAR) measurements for the horizontal velocity (Fig. 1) (Reference Bougamont, Tulaczyk and JoughinJoughin and others, 2002). In areas where there are gaps in the measured velocity, we either interpolate, or use balance velocities (Reference Bamber, Vaughan and JoughinBamber and others, 2000). For the fast-moving tributary and ice-stream nodes, we assume there is significant sliding so that the flow velocity is constant throughout the ice column. At ice-sheet nodes where the velocity is depth-dependent, we compute the normalized variation of velocity with depth for internal deformation (Reference PatersonPaterson, 1994, p. 251). This function is then multiplied by the measured surface velocity to estimate the depth-dependent velocities.

Assuming a steady state, the vertical velocity for the ice-stream and tributary nodes is well represented as varying linearly from a value equal to the accumulation rate at the surface to zero at the bed (MacAyeal, unpublished information). In the case of sheet flow, a linearly varying vertical velocity does not strictly apply. In such cases, the vertical strain rate is sometimes modeled as constant above a shearing layer of thickness h, below which it falls off linearly to zero (Reference Dansgaard and JohnsenDansgaard and Johnsen, 1969). We applied this model to the ice-sheet nodes in our solution of Equation (2) with h equal to 16% of the ice thickness. Sensitivity to the shear layer thickness is described below.

We initialized the model with an analytical solution for T, which neglects horizontal advection (Reference ZotikovZotikov, 1986). With this model, temperature depends on the ice thickness (Fig. 2) (Reference Lythe and VaughanLythe and others, 2001) and the surface accumulation rate (Reference Giovinetto and ZwallyGiovinetto and Zwally, 2000). Figure 3 shows the initial basal temperature gradient. As part of the initialization process, it must be determined which nodes are melted and which frozen. We assume that a wet bed enables the fast motion of the ice streams and their tributaries, so the basal temperature at these nodes was fixed at T _pmp. For ice-sheet nodes where the bed is frozen, we determine the bed temperature with the analytical solution in which G determines the basal temperature gradient. If the temperature is below the pressure-melting point, the initialization procedure designates the node as frozen. If the temperature is at or above the freezing point, then the node is considered melted and we initialize temperature by switching to the analytical solution for a wet bed (Reference ZotikovZotikov, 1986).

Fig. 2. Ice thickness map used to model basal temperature gradient for the Ross ice streams and their catchments (Reference Lythe and VaughanLythe and others, 2001). Flow-speed contours at 100 m a^–1 intervals (black) and at 50 m a^–1 (white) show locations of the ice streams. Stars show borehole locations discussed in the text.

Fig. 3. Basal temperature gradient computed from an analytical solution with no horizontal advection that was used to initialize the numerical solution. Flow-speed contours at 100 m a^–1 intervals (black) and at 50 m a^–1 (white) show locations of the ice streams. Stars show borehole locations discussed in the text.

During a model run, we test whether each ice-sheet node is frozen or melted at every time-step. We assume that beneath the ice sheet there is no flow of meltwater from adjacent nodes or local storage of meltwater so that a node freezes to the bed at any time-step when the basal temperature allows more upward conduction of heat than supplied by the geothermal heat flux. A frozen node becomes a melted node at any time-step where T equals or exceeds T _pmp. Since our model lacks subglacial drainage, we do not allow melt generated at one node to freeze at another, and thus do not allow any basal accumulation beneath ice-sheet nodes. For the ice streams and tributaries, we assume an infinite reservoir of basal water so that the bed remains wet (e.g. we assume the presence of fast motion indicates a wet bed, where either freezing or melting may be occurring).

Although there was little change for most nodes after 7500 years, we ran the model for 15 000 years for each ice-stream catchment to achieve a steady state. We attribute this relatively rapid convergence, in part, to our initialization with the vertical advection solution. Because most of this interval falls within the Holocene, and is therefore subject to relatively stable surface temperatures, we ran the model with the surface temperatures fixed with time. Figure 4 shows the final temperature gradient from the model.

Fig. 4. Basal temperature gradient, Θ_b, modeled to include the effect of horizontal advection. Flow-speed contours at 100 m a^–1 intervals (black) and at 50 m a^–1 (white) show locations of the ice streams. Stars show borehole locations discussed in the text.

Basal shear stress

We need the basal shear stress, τ_b, to determine the amount of basal shear heating that contributes to melt. A general slip law (Reference RaymondRaymond, 2000) gives the relationship between basal velocity and shear stress as

where the properties of the bed determine τ₀ and m. Laboratory tests on samples of till retrieved from boreholes through the ice suggest that the till behaves as a weak plastic material (m → ∞) that fails under a few kPa of applied shear stress (Reference KambKamb, 1991; Reference Tulaczyk and Kamb and EngelhardtTulaczyk and others, 2000a). In this case, all the motion is accommodated by sliding at the ice–till interface. Alternatively, a linear viscous deforming bed (m = 1) is often considered as the source of fast weak-bed ice-stream motion (Reference Alley, Blankenship, Bentley and RooneyAlley and others, 1987; Reference Kamb, Alley and BindschadlerKamb, 2001). For comparison, a conventional hard-bed sliding law would have m = 2.

With a homogeneous till layer it is easy to parameterize the power-law sliding dependence for a plastic or viscous bed, but, in practice, heterogeneities at the bed lead to “sticky spots”, yielding a more complicated relationship between basal shear stress and flow speed (Reference AlleyAlley, 1993; Reference RaymondRaymond, 2000). Consequently, over scales greater than an ice thickness, even with a purely plastic or viscous till, the “effective” value of m that may best represent flow behavior might lie anywhere between 1 and ∞.

Reference MacAyeal, Bindschadler and ScambosMacAyeal and others (1995) assumed a viscous deforming bed, and used velocity data in an optimal-control-method inversion to estimate the basal shear stress beneath Ice Stream E (Reference MacAyealMacAyeal, 1993b). The same techniques can be used to implement an inversion routine for a weak plastic bed (Joughin and others, in press). The weak plastic till and the linear viscous till are the easiest models to invert for the basal shear stress, and together they bracket the range of expected m. While there are differences in the overall goodness of fit for each model, the basal shear stress distributions from inversions of each model do not differ drastically (e.g. both cases achieve force balance while matching the observed velocity). Thus, we expect to get a reasonable distribution of basal shear stress even if the model we invert differs slightly from reality (e.g. as from spatially variable m and τ₀). We used the basal shear stress determined by these inversions (Joughin and others, in press) for the ice-stream and tributary nodes. At the ice-sheet nodes, we assumed τ_b = τ_d. Figure 5 shows the resulting distribution of basal shear stress for all nodes.

Fig. 5. Basal shear stress for the Ross ice streams. Beneath the ice streams and tributaries, τ_b was determined from inversions constrained by the velocity data in Figure 1. For the slow-moving ice sheet, τ_b is assumed to equal τ_d. Flow-speed contours at 100 m a^–1 intervals (black) and at 50 m a^–1 (white) show locations of the ice streams. Stars show borehole locations discussed in the text.

Basal velocity

While the data shown in Figure 1 provide U _s, the melt-rate calculations require basal velocity, U _b. With the ice-stream nodes, there is little internal deformation, so we can assume U _b ≈ U _s. This assumption also applies to areas beneath the tributaries where the bed is weak. Where the bed is strong beneath the ice sheet and some tributaries, however, internal deformation yields a significant contribution to U _s so that U _s > U _b. To compensate, we estimate the speed due to internal deformation for the tributary and ice-sheet nodes (Reference PatersonPaterson, 1994) and subtract it from U _s to estimate U _b: Since we use τ_b to compute the deformation velocity, this correction only has a significant effect in the regions where the bed is strong.

Basal temperature gradient

The basal temperature gradient modeled with horizontal advection (Fig. 4) differs markedly from that modeled with only vertical advection (Fig. 3). With the inclusion of strain heating, the bed beneath much of the ice sheet and tributaries is more prone to melting. In contrast, the ice streams are much more subject to freezing due to the addition of horizontal advection. The steepening of the gradient is most pronounced (e.g. blue regions in Fig. 4) where the ice thins rapidly as it moves from the deep interior to the shallow ice-stream beds (Reference Parizek, Alley, Anandakrishnan and ConwayParizek and others, 2002). Where the tributary beds are weak, horizontal advection can lead to changes in Θ_b that favor freezing. In other areas where the tributary beds are stronger, internal strain heating causes changes in Θ_b that promote melting.

The downstream area of Ice Stream C differs little between the models with and without horizontal advection. This is because Ice Stream C stopped roughly 150 years ago (Reference Retzlaff and BentleyRetzlaff and Bentley, 1993), and we have used post-stagnation velocities to model temperature. To examine conditions prior to the shutdown, we have used an ice-stream model (Reference MacAyealMacAyeal, 1989) to determine velocities that would roughly maintain the mass balance of the ice stream. Figure 6 shows the temperature gradient with active ice-stream velocities. As expected, the faster velocities cause the temperature gradient to decrease over much of the now stagnant area. There is a small area where there was little change or slight increase in the temperature gradient. This is because inaccuracies in the elevation data over some regions yield model velocities with flowlines that, when traced backward, originate on ridge B/C instead of the catchment interior. As a result, there is little thinning along these flowlines, leading to little change in the temperature gradient. Flow stripes visible in satellite imagery suggest the flowlines should indeed originate further inland, so it is likely that with our modeled velocity field the model overestimates Θ_b in the stagnant part of Ice Stream C. This is a good illustration of why measured velocities are preferable to modeled velocities.

Fig. 6. Basal temperature gradient for Ice Stream C estimated using modeled velocity field for the downstream end. The modeled velocity is shown with contours at 100 m a^–1 intervals (black) and at 50 m a^–1 (white).

Borehole/model comparison

Boreholes drilled through the ice yield measured temperatures at several locations (see Fig. 1) (Reference Gow, Ueda and GarfieldGow and others, 1968; Reference Engelhardt and KambEngelhardt and Kamb, 1993) that help to evaluate the quality of our estimates. Figure 7 shows the temperature profile measured at the “UpD” camp (Engelhardt, in press). This figure illustrates that the borehole thickness differs from that of the ice-thickness data used in the model. To improve the comparison, we have rescaled the model results to match the borehole thickness. The rescaled curve for the model with horizontal advection (green curve) provides a reasonably close match to the measured temperature profile. There is a large difference between the measured data and the vertical-advection-only model result (red curve), illustrating the importance of including horizontal advection in ice-sheet temperature models.

Fig. 7. Measured and modeled temperature profiles at the UpD camp. Blue stars show the measured temperature profile (Engelhardt, unpublished information). The black curve shows the result from the model with horizontal advection. The green curve shows the same model result as the black curve, but with the vertical coordinate rescaled so that the thickness matches the borehole thickness. The red curve shows the rescaled vertical-advection-only solution.

Since we are primarily interested in Θ_b, Table 1 provides a comparison of the measured and modeled temperature gradients at the locations shown in Figure 1. Because the thickness does not always agree with the measured thickness, we have also included the rescaled (as in Fig. 7) values for the model with horizontal advection to account for errors in the gridded thickness data.

The results in Table 1 show that the model with horizontal advection yields good agreement (particularly when re-scaled) between measured and modeled values at stations designated UpB, UpD and Byrd. There is a large difference at the “Fishhook” (FH) profile, which is located on an area of slow-moving ice adjacent to Whillans Ice Stream. There is evidence, however, that this was an area of rapidly moving flow approximately 190 years ago (Reference Clarke, Liu, Lord and BentleyClarke and others, 2000). If we compare the Fishhook profile with the model temperatures at a point shifted by 10 km from FH toward the fast-moving center of the ice stream (a blue star shows the location “FH shifted” in Figure 1), then, after rescaling, we obtain a value of Θ_b that is closer to the value measured at the FH borehole. Even in this case, there is still a significant difference that is probably related to non-steady flow in the region. Note that in this case the rescaling does not represent a correction for a thickness error, but instead approximates the effect of moving ice from “FH shifted” to FH.

At the station designated UpC, we get poor agreement between modeled and measured Θ_b. This discrepancy possibly reflects the fact that there has been relatively little time for the temperature profile to adjust thermally following the shutdown, so the measured profile likely has not changed significantly from when the ice stream was active. We get better agreement with the temperature solution (“UpC fast”) using modeled ice-stream velocities, but not as close as for the other profiles. This is not surprising, given that the modeled velocities provide only a rough approximation to the former flow field.

Overall, the borehole comparisons are encouraging. In areas with relatively steady flow, we get good agreement with measured values. Errors due to the thickness data are not a significant concern since they should average out when melt is evaluated over wide areas. The results illustrate that departures from our assumption of steady flow over the last 15 000 years lead to errors where there has been significant flow variability (e.g. Ice Stream C and FH) and we need to factor this into the interpretation of our results. Although this is a weakness of our approach, in general the measured velocities provide significantly better basal temperature gradients than results relying solely on modeled velocities (Reference Hulbe and MacAyealHulbe and MacAyeal, 1999).

Estimated melt rates

Figure 8 shows our map of estimated melt rate. There are several trends readily visible in this figure. First, large areas beneath Ice Stream C and Whillans Ice Stream are subject to freeze-on at rates of a few mm a^–1. Note here and in the following discussion that we treat Ice Stream A as a branch of Whillans Ice Stream. Ice Streams D and E also have pockets subject to freeze-on, but there are also extensive areas of melt (more so on E than D). Areas beneath the ice streams where there is significant melt generally coincide with the presence of sticky spots in the basal shear stress map (Fig. 5). The ice-stream tributaries stand out clearly as areas subject to high melt (>5 mm a^–1). Beneath much of the ice sheet, however, there is significantly less melt (<5 mm a^–1), with some areas that are frozen to the bed.

Fig. 8. Estimated basal melt/freeze rates. Flow-speed contours at 100 m a^–1 intervals (black) and at 50 m a^–1 (white) show locations of the ice streams. Stars show borehole locations discussed in the text.

We have tabulated the melt for each of the four roughly equal-sized ice-stream catchments in Table 2. Note that the Ice Stream A/Whillans catchment has been truncated in the region near the Transantarctic Mountains because reliable ice-thickness data are lacking.

With a total melt of 0.53 km³ a^–1, Whillans Ice Stream and its catchment produces a similar amount of melt to the other active ice streams. The majority of this melt (0.29 km³ a^–1) occurs beneath the Whillans tributaries, with an additional 0.16 km³ a^–1 of melt taking place beneath the inland ice. Much of this melt takes place beneath faster-moving ice-sheet nodes that move at near-tributary speeds. Although 0.07 km³ a^–1 of melt is produced beneath the fast-moving ice stream, most of the area beneath the ice stream is freezing (Fig. 8), except for a few strong melting patches located at isolated sticky spots. We remark, however, that the poor quality of the elevation data on the ice plain of Whillans Ice Stream may have introduced erroneously large sticky spots in the inversion of surface velocity data for τ_b, and this may mean that our still somewhat positive melt rate for Whillans Ice Stream is in error. In addition, the gaps in the velocity data (Fig. 1) may have affected the quality of the inversion. If, instead of the inversion result, we had used a uniform value of τ_b = 2 kPa, we would have estimated a net freezing rate of –0.01 km³ a^–1 (–0.3 mm a^–1) for a total melt of 0.45 km³ a^–1. This value of τ_b is consistent with force-balance estimates (Reference Whillans and van der VeenWhillans and Van der Veen, 1997) and labratory tests on recovered till samples (Reference Tulaczyk and Kamb and EngelhardtTulaczyk and others, 2000a; Reference Kamb, Alley and BindschadlerKamb, 2001). As a result, we conclude that the total melt for Whillans Ice Stream lies somewhere between 0.45 km³ a^–1 (τ_b = 2 kPa) and 0.53 km³ a^–1 (τ_b as in Fig. 5).

The total melt estimate of 0.53 km³ a^–1 derived for the entire ice-stream area is more than double an earlier estimate of 0.25 km³ a^–1 for Whillans Ice Stream (Reference Bougamont, Tulaczyk and JoughinJoughin and others, 2003). The main reasons for this are that the earlier estimate used a uniform value of τ_b = 2 kPa on the ice stream, neglected strain heating and ignored melt beneath the ice sheet.

Non-steady flow, changes in the surface topography since stagnation, and sparse elevation data complicate melt calculations for Ice Stream C. Our estimate of 0.32 km³ a^–1 for Ice Stream C is smaller than that for any of the other Ross ice streams. There is a net basal freeze-on beneath the stagnant region of –0.05 km³ a^–1, which likely is an underestimate because present-day velocities were used to include horizontal advection in the model.

With the fast-flow model for an active Ice Stream C with basal shear heating, the total melt rises to 0.48 km³ a^–1, which is only slightly less than the melt generated below Whillans Ice Stream. This fast-flow model yields average ice-stream melt rates of 4.5 mm a^–1, which seem too large to have allowed stagnation. The fact that we appear to overestimate the basal temperature gradient (Table 1) at least partially explains some of the large ice-stream melt rates. In addition, thickening of the ice stream since stagnation has steepened the surface topography on parts of the ice stream (Reference JoughinJoughin and others, 1999; Reference Joughin, Tulaczyk, Bindschadler and PricePrice and others, 2001). This means that to yield realistic velocities, the model for ice-stream velocity requires a stronger bed to resist the larger driving stresses from the now steeper slopes. To test the sensitivity to a weaker bed, we also estimated the melt with a uniform value of τ_b = 2 kPa on the fast-flowing ice stream, which yielded freezing of –0.04 km³ a^–1 (–1.8 mm a^–1) for the ice-stream nodes and total melt of 0.34 km³ a^–1.

An earlier estimate of –0.11 km³ a^–1 (Reference Bougamont, Tulaczyk and JoughinJoughin and others, 2003) for the active ice stream indicates more basal freeze-on than our estimates (–0.04 km³ a^–1 with τ_b = 2 kPa and 0.1 km³ a^–1 with the model τ_b). Since the earlier estimate used a model tuned to match the nearby temperature profile measured at UpC, it is possible that lacking velocity data from when the ice stream was active, the earlier model yields a more accurate estimate of basal freeze-on for this particular region. Taking into account the earlier estimate of melt beneath the ice stream yields a range for the total melt prior to stagnation of 0.26 (ice-stream freezing of –0.11 km³ a^–1 and tributary and sheet melt as in Table 2) to 0.48 km³ a^–1.

The total melt for the Ice Stream D catchment is 0.52 km³ a^–1. While there are pockets beneath the ice stream where freeze-on takes place, sticky spots yield an average melt rate of 3.6 mm a^–1, which is smaller than the value for its tributaries. Ice Streams D and E are covered by the European Remote-sensing Satellite (ERS) altimeters, so the quality of the elevation used in the τ_b inversion is much better than that used for much of Ice Stream C and Whillans Ice Stream. Average values of τ_b are consistent with force-balance estimates for Ice Streams D and E (Reference Bougamont, Tulaczyk and JoughinJoughin and others, 2002), giving us a reasonable degree of confidence in the ι_b inversions used for the melt-rate averages. Although the melt rate is relatively high beneath Ice Stream D, the tributaries (0.28 km³ a^–1) and ice sheet (0.21 km³ a^–1) are responsible for the majority of the total melt.

The Ice Stream E catchment produces an estimated total melt of 0.63 km³ a^–1, which is greater than for any of the other Ross ice streams. Unlike the other ice streams, the melt rate beneath Ice Stream E (9.6 mm a^–1) is larger than beneath its tributaries (6.7 mm a^–1). The large melt rates are the result of a larger number of sticky spots beneath the ice stream, as suggested by previous studies (e.g. Reference MacAyeal, Bindschadler and ScambosMacAyeal and others, 1995).

The addition of strain heating significantly increases melt-rate estimates relative to earlier results that did not include this effect (Reference Bougamont, Tulaczyk and JoughinJoughin and others, 2003; Reference Vogel, Tulaczyk and JoughinVogel and others, 2003). To examine sensitivity to strain heating, we ran the model with no strain heating and with a 50% reduction in strain heating. For Ice Stream D, the 50% reduction in shear heating reduced the melt rates to 0.19 and 0.25 km³ a^–1 for ice-sheet and tributary nodes, respectively. With no strain heating, the corresponding melt rates are decreased to 0.16 and 0.22 km³ a^–1. There were similar reductions for the other catchments with reduced or no shear heating. Overall the total melt rates would be about 40% less without any strain heating.

As described above, we estimate the deformational component of velocity, which we subtract from the surface velocity to estimate sliding velocity in the tributaries. This has the effect of partitioning the energy available for heating between shear heating at the bed and internal strain heating within the column. The heat generated by internal strain influences melt through its effect on the basal temperature gradient, but does not directly melt ice. In contrast, shear heating at the bed contributes directly to melt. This partitioning represents one of the larger uncertainties in our model because of the non-linear dependence of deformational velocity on driving stress. We assume that these errors tend to average out when computing basin-wide averages. To put an upper bound on the error, we ran the model assuming the extreme case that there is no deformational velocity for the tributaries (i.e. all motion is due to sliding). This increased tributary melt rates by about 40% and increased the total melt-rate estimates by about 18%.

We used a Reference Dansgaard and JohnsenDansgaard and Johnsen (1969) approximation for the ice-sheet nodes, with h equal to 16% of the ice thickness. This parameter is not well constrained, so to test the model sensitivity to this parameter, we also ran the model with h equal to 0 and 30% of the ice thickness. With zero shear-layer thickness, the model produced 13% less melt overall, most of which was due to a 29% reduction in ice-sheet melt. When we increased the shear layer thickness to 30% of the ice thickness, the model yielded an 8% increase in total melt that was mostly the result of a 17% increase in ice-sheet melt. Thus, over a reasonable range of shear-layer thicknesses, total melt can vary by about ±10% and ice-sheet melt by roughly ±25%.