Instrumentation

Snow temperature was measured with a digital thermometer (±0.2°C) for each 5 cm sampling layer. Water volume content was derived from dielectric permittivity measurements using a flat capacitance sensor (20 MHz, ±3% volumetric water content (Reference DenothDenoth, 1994; Reference Eller and DenothEller and Denoth, 1996). Samples were weighed to the nearest 0.1 g using a digital scale and subsequently converted to snow densities (kg m⁻³). The average analytical error resulting from uncertainty in sample volumes and weighing is estimated to be ±30 kg m⁻³.

Samples were thawed and bottled, without headspace, in 25 mL double-lidded HDPE sample bottles. Samples were stored in a refrigerator prior to laboratory analysis to minimize evaporation. All samples were analysed for isotopic ratios using a Thermo Finnigan mass spectrometer with a glassy carbon reactor optimized for simultaneous analysis of both δ¹⁸O and δ²H by the conversion of H₂O to H₂ and CO, with sampling errors of ±0.2 and ±1.0‰, respectively.

Total sampling error for density and isotope samples is the sum of both analytical error and sampling error. Analytical error is defined as error resulting from instrumental uncertainty, as outlined by instrument manufacturers and laboratory protocol (reported above). Sampling error refers to the repeatability of field measurements and is dominated by spatial variability in the snowpack stratigraphy. Sampling across horizontal strata in a snow pit should only introduce minor variations in density and isotopic ratios, resulting from local variations in wind redistribution, differences in glacier and snow-surface topography, dipping strata and local-scale variations in snow accumulation. In order to quantify sampling variations in density and isotopic ratios, three replicate samples were taken along horizontal strata during the sampling of each snow pit.

The sampling errors for both density and isotope ratios are averaged across all error samples from all snow pits, with the assumption that these errors are representative of local-scale processes at all sites across time. Average sampling error is estimated to be ±0.5 and ±3.8‰ for δ¹⁸O and δ²H, and ±17 kg m⁻³ for snow density; giving total error estimates of ±0.7, ±4.8‰ and ±47 kg m⁻³, respectively. Error bars displayed in snow-pit profiles of snow density and isotopic values are total error estimates. Note that these error estimates refer to point samples within the stratigraphy; the error is greatly reduced for depth-averaged isotopic values in the snowpack (scaled by , where N is the number of samples).

At TM380 and TM600, averaged in situ snow temperatures were recorded every 30 min from samples measured every 10 s, using 44002A thermistors from Yellow Springs Instruments. Thermistors were located every 5 cm vertically in the snowpack, beginning 3 cm below the snow surface. All thermistors were calibrated in an ice bath. Two sensors were found to have biases of +0.3°C. All data presented here have been corrected to account for this bias. Manufacturer instrument accuracy is reported to be ±0.2°C for temperatures from 0 to 70°C. While the manufacturer states that these thermistors are stable for temperatures from −80 to 50°C, their accuracy below 0°C is not given.

Sites TM380 and TM600 were equipped with TDR probes taking hourly water-content measurements. While traditionally developed to measure water content in soil and rock, these probes have been used in more recent years to measure water content and density in snowpacks (Reference Schneebeli, Coléou, Touvier and LesaffreSchneebeli and others, 1998; Reference Waldner, Schneebeli, Schultze-Zimmermann and FlühlerWaldner and others, 2004). The data derived from these probes are not presented here because the pre-melt water-content measurements had a large degree of sampling variation. These variations are probably due to the low density values of the thin Arctic snowpack and formation of air pockets around the probes. However, after melt onset, and the subsequent densification of the snowpack, the sensors in the upper portion of the snowpack showed strong diurnal variation in meltwater content, consistent with water-content values derived from the capacitance sensor. These sensors may be of great value to meltwater studies extending beyond the beginning of the melt season, and we recommend further exploration of TDR probes for studies of meltwater percolation in low-density snowpacks.

Snow temperature, water content and density

Figure 3 plots the progression of snow temperature, water content and density values at TM380 over the course of the study. Average snow temperatures increase from −9.1 °C in pit 1 to −1.5°C in pit 6 (Fig. 3a). From pit 1 to pit 3 there is an increase in snow temperature observed throughout the entire snow-pit profile, with surface snow temperatures in pit 3 reaching 0°C. Subsequent snow pits show a downward propagation of the 0°C isotherm, corresponding with increases in the water content (Fig. 3b). These results are similar to previous studies by Reference Conway and BenedictConway and Benedict (1994) and Reference Pfeffer and HumphreyPfeffer and Humphrey (1996), who used the position of the 0°C isotherm to track the movement of meltwater through a melting snowpack.

Water content and snow density at TM380 do not change notably until pit 5. Consequently, plots of these parameters are simplified to show results only from pits 1, 4, 5 and 6. Water content increased from a mean value of 0.1% in the pre-melt snow pit to a mean value of 1.7% in pit 6. A maximum water content of 5.0% is observed in the surface layers of pit 5 (Fig. 3b), with a visibly moist snow layer occurring immediately above an ice layer (Fig. 4, pit 5).

Fig. 4.

Snow-pit stratigraphies including snow type, hardness and grain size (mm) for all snow pits sampled at TM380. IL is ice layer, MWS is moist windslab, WC is wind crust and MC is melt crust. A normalized SWE value of 1 represents the snow surface; glacial ice is 0.

Mean snow-pit densities at TM380 increase from 256 kg m⁻³ in pit 1 to 277 kg m⁻³ in pit 6 (Fig. 3c). Corresponding to observed changes in water content, there is a sharp increase in snow densities in the upper layers of the snowpack from pit 4 to pit 5. The average density in the upper third of the snow pits increases 27% from 311 kg m⁻³ in pit 1 to 394 kg m⁻³ in pit 6.

Snow-pit stratigraphies

Snow-pit stratigraphies for all TM380 snow pits are shown in Figure 4. Snow types from these and stratigraphies performed at other sampling sites over the course of the study, can be divided into three broad categories: (1) hoar-frost, accumulating in autumn and early winter, (2) wintertime windslab, punctuated with thin wind crusts, and (3) fresh springtime snow. All snow-pit sites show a strong seasonal isotopic signal, with minimum δ¹⁸O values occurring within the fine-grained (∼1.0 mm) winter layers.

At TM380, snow grain size increased over the 16 day study from an initial average of 1.0 mm to a grain size of 1.5–2.0 mm. Qualitative measures of snow hardness show increases throughout the entire snow-pit profile. The largest changes were observed in the top half of the snow pit, where hardness increased from 2 finger/finger to finger/pencil. These results are consistent with the increases observed in snow-pit densities.

Two types of ice layers formed during this study: (1) continuous layers of solid ice without visible crystal structure and (2) more permeable ice layers, with discernible crystal structure. We refer to these as ‘ice layers’ and ‘melt crusts’, respectively. A total of four ice layers and nine melt crusts were identified at all snow-pit sites over the course of the study. All but one formed at previously identified transitions in snow type, hardness or grain size. Three of the melt crusts formed from previously identified ice layers as melt progressed.

By the end of the study the upper 75% of the snowpack had reached temperatures of 0°C, but overnight refreezing and cooling were measured to 13 cm depth, or a normalized SWE (h) value of 0.65 (T3). Similar results were found in the snow-pit stratigraphies at TM600 (not shown). The diurnal variations in air temperature play an important role in nighttime refreezing and the formation of ice layers in the upper layers of the snowpack. Nightly refreezing of meltwater in the snowpack slows progression of melt at these sites, as a large amount of heat energy at the onset of melt must be devoted to warming the snowpack and re-thawing these ice layers before ‘new’ melt can proceed.

In the case of TM380, the wind crust at a normalized SWE (h) value of 0.64 in pit 2 (Fig. 4) influences both the percolation of meltwater and the location of ice layers within the snow-pit stratigraphy. These effects can be tracked through the visual snow-pit stratigraphies (Fig. 4) and in the thermistor data (Fig. 5b).

Fig. 5.

(a) Initial location of thermistors and TDR probes in the TM380 snow-pit profile. (b) snow-pit temperatures from thermistors at the TM380 snow-pit sampling site from 7 to 14 June 2008. A normalized SWE value of 1 represents the snow surface; glacial ice is 0.

The ice layer observed in pits 4 and 5 (h = 0.65 and 0.57, respectively) is thought to be the same ice layer, as it falls within the degree of variability associated with snow-pit SWE at this site (average cumulative SWE for this site is 124.6 ± 15.4 mm, giving a normalized SWE of 1.0 ± 0.1). This ice layer was ∼4 mm thick at the time of formation and occurred at the location of the wind crust identified in pit 2. The ice layer identified in pits 4 and 5 persists in pit 6 as a more breakable melt crust (h = 0.62). A second melt crust is observed to form in pit 6 (h = 0.51), at a previously identified transition between windslab and hoar layers. The highest water contents observed in TM380 stratigraphies occur immediately above ice and melt crust layers (Fig. 4, pits 5 and 6).

Figure 5a shows the location of the seven thermistors (T1–T7) and four TDR probes (TDR1–TDR4) within the snowpack profile at TM380, with the temperature data from each thermistor probe plotted in Figure 5b. It is commonly acknowledged that temperature sensors as deep as 20 cm below the snow surface can be affected by the penetration of radiation through the snowpack (Reference Pfeffer and HumphreyPfeffer and Humphrey, 1996). While thermistors were covered in white shrink wrap to limit the amount of direct heating resulting from radiative penetration, the >0°C temperatures observed by T1–T3 indicate that it remained a factor. These sensors were not removed from the analysis however, because their records still provide insight into the large diurnal variations observed in snow-pit temperatures at TM380 over the course of the study (Fig. 5b).

The progression of meltwater percolation can be tracked through the snow-pit profile using the location of the 0°C isotherm. In situ temperatures for T2 and T3 (h = 0.82 and 0.67) are observed to stay at a temperature of ∼0°C on the evening of 7/8 June (day 158/159; Fig. 5b), while surrounding thermistors show a more classic diurnal temperature trend. This observation corresponds with the percolation of meltwater to h = 0.67 in the snow-pit stratigraphy (Fig. 4, pit 3).

On 9/10 June (day 160/161) at TM380, T4 maintains a temperature of 0°C throughout the night, while decreasing temperatures are observed at T3. The timing of this observation corresponds with the formation of the 4 mm thick ice layer identified in pits 4 and 5. We believe this observation is related to the release of latent heat to the snowpack during ice-layer formation.

Isotopic values

The isotopic profiles from the TM380 snow pits become less variable as melt progresses (Fig. 6). The δ¹⁸O values for the pre-melt snow-pit range from −20.3 to −35.3‰, with a density-weighted average of −26.3‰. (Fig. 6, pit 1). The final snow pit, pit 6, has δ¹⁸O values ranging from −20.7 to −33.3‰, with a density-weighted average of −25.9‰ (Fig. 6, pit 6).

Fig. 6.

Histograms showing the frequency distribution of δ¹⁸O values for the TM380 snow pits. The line in each plot indicates the density-weighted average δ¹⁸O value for each snow pit.

Mean density-weighted δ¹⁸O values show an altitudinal gradient of −0.4‰ (100 m)⁻¹, with an average density-weighted δ¹⁸O value (across all snow pits) of −26.7‰ at TM380 decreasing to −29.2‰ at TM1000 (Table 1). In addition to the altitudinal gradient, seasonal signals in δ¹⁸O values are discernible at all four snow-pit sites (Fig. 7), with an average δ¹⁸O range, defined as the difference between the minimum and maximum δ¹⁸O value within each snow pit, of 12.4‰. A maximum δ¹⁸O range of 15.3‰ is observed in pit 4 of the TM1000 snow-pit site, and a minimum δ¹⁸O range of 8.3‰ is seen in the final pit, pit 7, at TM600.

Fig. 7.

δ¹⁸O values for all snow-pit sites. (a) TM380; (b) TM600; (c) TM800; (d) TM1000. The legend in (a) applies to all of the snow-pit sites (except the error estimate, 0.7‰, which is the same for all sites, but is shown individually because of the differences in scale between the parts of the figure). A normalized SWE value of 1 represents the snow surface; glacial ice is 0.

All snow-pit sites show an increase in average density-weighted δ¹⁸O values over the course of the study (reported as positive Δδ¹⁸O values in Table 1). Significant increases in δ¹⁸O values are observed at the TM600 and TM1000 snow-pit sites; however, these sites are thought to have been influenced by fresh snowfall inputs (see below). Increases in mean δ¹⁸O values at TM380 and TM800 are not statistically significant, but because fresh snowfall amounts at these sites were observed to be lower than at TM600 and TM1000 they are thought to be indicative of isotopic changes occurring as a result of melt processes. Even with a positive degree-day (PDD) value of ≤7.5°C d (Table 1), increases in isotopic values are observed at all snow-pit sites, suggesting that isotopic enrichment has the potential to be significant under higher-melt scenarios.

Complications were observed in the TM1000 stratigraphies, as the minimum isotopic values observed in pits 2–7 were not captured in the pre-melt snow pit at this site (Fig. 7d). This discrepancy is probably the result of differences in snow-pit sampling location that occurred between pit 1 and subsequent sampling sites at this location. Similar inconsistencies can be observed between the isotopic stratigraphies of pits 1 and 2 of TM600 and subsequent snow pits at this site. As described above, the first two snow pits sampled at TM600 were located ∼1.5 m away from the sampling site established for pits 3–7, and are thoughtto have been sampled in an area where the winter snow was subject to wind redistribution. They show very similar isotopic profiles to one another, but not to subsequent sampling stratigraphies. Because of the complications observed in snow-pit stratigraphies, pits 2 and 3 were used as pre-melt (reference) snow pits for TM1000 and TM600, respectively.

Removal of pit 1 from the analysis increases the average isotopic range observed at TM1000 from 14.0‰ to 14.7‰, indicating that pit 1 did not capture the same seasonal isotopic range as other pits from the site. While similar improvements are observed at TM600, where average isotopic range increases from 7.9‰ to 9.2‰ with the removal of pits 1 and 2 from the analysis, the δ¹⁸O ranges observed at the site (mean = 9.2‰) are consistently lower than at other snow-pit sites, which had an average δ¹⁸ O range of 13.5‰. Additional complications arise in the analysis as the reference snow pits from the TM600 and TM1000 sites may have experienced a small degree of melt. TM600 and TM1000 experienced 0.7 and 1.2 PDD by pit 3 and pit 2, respectively.

Snow pits as an analogue for ice-core sites

PPD values are used to link isotopic modification observed at the low-elevation snow-pit sites with the amount of isotopic modification experienced at the firn-core site. The firn-core site has an average accumulation rate of 295 mm w.e. a⁻¹ . Detailed snow-pit stratigraphies from the site performed during the 2007 field season indicate that surface melt produces intermittent but localized ice layers up to 1 cm thick. There is no indication that meltwater percolation at this site penetrates into the previous year’s accumulation, although we cannot rule this out for exceptionally warm summers.

Isotopic values

Linear-regression analysis is used to determine whether temporal changes in isotopic values are significant. All snow-pit sites experience an increase in average snowpack isotopic values over the course of the study (Figs 7 and 8a). We limit the influence of fresh snowfall over the course of our study by removing fresh snow samples from our analysis, but in some instances fresh snow may have melted into the underlying snowpack. This was most problematic at the TM600 and TM1000 snow-pit sites, where fresh snowfall had the largest percentage contributions, with up to 8% and 14%, respectively, of the total SWE at these sites coming from fresh snowfall. Fresh snow samples from these sites had average isotopic compositions of −22.4‰ and −21.1‰, respectively. We estimate the density of these samples as 200 kg m⁻³, and calculate average isotopic enrichments of 0.3‰ and 1.1‰, respectively.

Fig. 8.

Temporal changes in (a) mean δ¹⁸O values and (b) δ¹⁸O ranges (defined as the difference between the minimum and maximum δ¹⁸O value within each snow pit) for all snow-pit sites.

By contrast, fresh snow contributes 0.2% and 2% of the total SWE at TM380 and TM800, respectively. Fresh snow was not sampled at either of these sites, so average isotopic values from the TM600 and TM1000 fresh snow samples were used to estimate the average isotopic enrichments of <0.1‰ and 0.1‰ resulting from melting and percolation of fresh snow at TM380 and TM800. These effects are negligible at TM380 and TM800, but the increases in δ¹⁸O values observed at TM600 and TM1000 may be heavily influenced by fresh snowfall inputs and are not included in the discussion.

Aeolian processes can also add snow to, or remove it from, snow-pit sampling sites. This potential source of error has been minimized by locating snow pits in close proximity to one another (i.e. by cutting snow-pit sampling walls back from one another). However, wind deposition was a concern at the TM600 sampling site where a hummocky glacial ice surface makes the region prone to both depositional and erosional processes within short distances of one another. This may explain the differences in stratigraphic profiles observed between the first two snow pits sampled at this site and the remaining pits (Fig. 7b), the lower than average isotopic ranges and the inconsistency in altitude effect observed at this site (Table 1). While wind redistribution is likely to have occurred at other snow-pit sites, the processes observed at these sites are believed to be more systematic.

The site that experienced the most melt, TM380, shows a significant decrease in isotopic range (Table 1; Fig. 8b), accompanied by an enrichment in δ¹⁸O values. As can be seen from Figure 7a, minimum δ¹⁸O values at TM380 do not experience a marked enrichment from the pre-melt snow-pit values until pit 5, between h = 0.47 and 0.62. Comparing this to the stratigraphy plots of Figure 4, pit 5, we see that meltwater percolated to a similar level (h = 0.57) in the snow-pit profile. TM800 shows similar results, where the depth of meltwater percolation corresponds to the changes in the isotopic profiles within the snowpack. Meltwater percolation is therefore considered the dominant process causing isotopic modification during the melt season.

Early in the melt season at TM380, reductions in isotopic range occur without a corresponding increase in mean δ¹⁸O values, suggesting that closed-system processes dominate early-melt-season modification of isotopic stratigraphies. However, as the amount of meltwater in the system increases, open-system processes become increasingly important, as demonstrated by the enrichment of mean snow-pit δ¹⁸O values during the latter part of the study period (Fig. 8a).

Because snow pits are an open system, there is potential for meltwater redistribution through both horizontal and vertical advection. Horizontal advection is assumed to have negligible effects on a snow pit’s isotopic composition because water is able to migrate both into and out of the system. Ice-layer development was also finite and spatially limited over the course of the study, so we suspect that horizontal advection resulting from this process was minimal. However, in the ablation zone of glaciated systems vertical advection is assumed to be a net loss, as meltwater is lost to runoff, superimposed ice, evaporation or erosive sublimation. No meltwater or superimposed ice was observed at the base of any of the snow-pit sites, so evaporation and sublimation are thought to be the dominant processes influencing mass loss from these sites.

The role of ice layers in limiting mass exchange

Similar to the findings of Reference Marsh and WooMarsh and Woo (1984) and Reference Conway and BenedictConway and Benedict (1994), ice layers in our study formed at stratigraphic boundaries in the upper layers of the snowpack, with water spreading out laterally to form horizontal zones of saturation and ice layers. We did not sample these ice layers directly for density, but Reference Marsh and WooMarsh and Woo (1984) report densities ranging from 630 to 950 kg m⁻³, with a mean value of 800 kg m⁻³ for ice layers formed in a Canadian Arctic snowpack.

These high-density, low-permeability layers near the surface of a snowpack are considered to be important in limiting the exchange of water vapour between the atmosphere and the snowpack (Reference Zhou, Nakawo, Hashimoto and SakaiZhou and others, 2008). As mentioned above, three out of the nine melt crusts observed in our snow-pit stratigraphies formed from the breakdown of ice layers during melt. While melt layers are denser than the surrounding snowpack, they represent a decrease in permeability from the antecedent ice layers. Thus the progression of the melt season and the consequent breakdown of impermeable ice layers into more permeable, loosely bonded melt crusts are thought to mark a significant transition in the factors controlling the modification of isotopic ratios within snowpacks, as these layers no longer limit exchange between the water vapour in the snowpack and the atmosphere. These findings are consistent with our results, where closed-system processes were found to dominate early in the melt season, with a transition to open-system processes as melt becomes more intense. While we did not directly measure vapour loss from the snowpack, the largest changes in mean δ¹⁸O values occurred late in the study at TM380 (Fig. 8a). These changes are consistent with fractionation and loss of depleted vapour from the snowpack.

Isotopic modification

Two considerations are relevant to the degree of meltwater-induced isotopic modification experienced at a site: (1) the absolute amount of melt and (2) the per cent melt. In Arctic snowpacks that do not experience meltwater runoff, the dominant processes resulting in mass loss and isotopic modification are evaporation and sublimation (Reference Stichler, Schotterer, Fröhlich, Ginot, Kull and GäggelerStichler and others, 2001). Because these processes are largely restricted to the surface layers of a snowpack, the absolute melt may be the best predictor of isotopic modification because it is a measure of the amount of free water available for evaporation.

Alternatively, because annual temperature signals derived from ice cores are calculated from the entire year’s accumulation, it could be argued that the total melt is less important than the per cent melt. For example, high-melt years that also experience high annual accumulation may not experience a large degree of isotopic modification because a relatively small portion of the snowpack is affected by melt. In contrast, low-melt years that also experience low amounts of accumulation may experience relatively large amounts of isotopic modification as meltwater is able to penetrate through a significant portion of the snowpack.

Other factors likely to affect the degree of isotopic modification at a site include: (1) the timing, thickness and depth of ice-layer formation; (2) the timing, amount and phase of summertime precipitation; (3) the timing and intensity of summertime melt; (4) windiness; and (5) relative humidity. Further investigation of melt processes accounting for these factors is likely to increase our ability to quantify isotopic modification resulting from melt processes.

Linking melt amount and isotopic modification

PDD values and per cent melt amounts are used to link isotopic modification observed at the low-elevation snow-pit sites with isotopic changes at the firn-core site. The trends in δ¹⁸O enrichment at TM380 and TM800 are not statistically significant; it is therefore recognized that these trends may prove to be negligible. However, these sites experienced a maximum PDD value of only 7.5°C d. Further study is therefore needed to determine whether this effect is real under higher-melt scenarios.

Degree-day factors (DDF, with units mm w.e.d⁻¹ °C⁻¹) are used to relate PDD values to total melt. Reference Arendt and SharpArendt and Sharp (1999) calculated snow DDF at three different locations on John Evans Glacier, Ellesmere Island, with values ranging between 2.7 and 5.5 mm w.e. d⁻¹ °C⁻¹. Because our study takes place at the beginning of the melt season when snow albedo is high, we use a relatively low DDF of 3.0 mm w.e. d⁻¹ °C⁻¹ to calculate the amount of ablation taking place at each snow-pit site over the duration of our study, as well as to estimate the amount of melt taking place at the firn-core site. These values are consistent with values for the Greenland ice sheet recommended by Reference BraithwaiteBraithwaite (1995).

Table 3 gives the SWE, PDD and absolute and per cent melt values calculated for each snow-pit sampling site as well as the historic values calculated for the firn-core site using NCEP 850c T data. Values presented for individual snow-pit sites were derived as follows: SWE was calculated directly from snow-pit depth and density measurements; PDD values were calculated from the temperature data collected at individual snow-pit sites over the course of the study; absolute melt amounts were calculated using PDD values from each snow-pit site and a DDF of 3.0 mm w.e. d⁻¹ °C⁻¹; and per cent melt was derived using the methods of Reference Fisher and KoernerFisher and Koerner (1994). Historical absolute and per cent melt values are derived from the NCEP 850c T dataset from 1967 to 2006 to span the time frame of the firn-core record and beyond. Accumulation values are measured from the firn-core stratigraphy, with the exception of 2000–01 and 2006 values, which come from snow-pit data. There are no accumulation data for 2003–05 at this site.

Table 3.

Average historical SWE, PDD values, and total and per cent melt for the firn-core site. Absolute melt values for the firn-core site are derived from PDD values calculated using 1967–2006 NCEP 850c T data. Accumulation values are derived from the firn-core stratigraphy, except for values from 2000–01 and 2006, which came from snow-pit data. There are no accumulation data for 2003–05 for this site. SWE, PDD values, and absolute and per cent melt are shown for all snow-pit sampling sites

The historical melt record for the firn-core site (Fig. 9) indicates that 2001 was a high-melt year (66 mm w.e.), exceeded only by estimated melt values for 1998 (90 mm w.e.). Because of the lower accumulation observed in 2001, the per cent melt values for the two years are very similar, 33% and 36%, respectively. Compared with the historical per cent melt average of 10%, these two years have very high per cent melt values, >10% higher than the next highest melt year, 1999. Average summertime melt for the entire 40 year record is 30 mm w.e.

Fig. 9.

Historical melt and per cent melt values for the firn-core site derived from PDD values calculated using 1967–2006 bias-corrected NCEP 850 mb T data. Accumulation values are derived from the firn-core stratigraphy, except for values from 2000–01 and 2006, which came from snow-pit data. There are no accumulation data for 2003–05 for this site. Average melt for the record is 30 mm w.e., mean per cent melt is 10% and average annual accumulation is 295 mm w.e.

Figure 10 shows the isotopic signal from the top of the firn core, where it is clear that even during years of intense melt (e.g. 2001) the seasonal isotopic signals are preserved. Thus we are still able to identify and count annual layers. However, without calculations of melt, the likely enrichment of isotopic values observed in 2000–01 would be overlooked. Based on our snow-pit results, this would lead to an overestimation of annual temperatures derived for those years.

Fig. 10.

Seasonal δ¹⁸O signals at the firn-core drill site. These data indicate the persistence of seasonal δ¹⁸O signals, even during years of intense melt, such as 2001.

We assert that the preservation of annual isotopic signals is not an adequate indication of the preservation of isotopic values. This research indicates that isotopic signals subject to meltwater percolation experience, not only a reduction in seasonal isotopic range, but also an accompanying isotopic enrichment, most likely due to increased evaporation and sublimation. These changes result in overestimates in annual temperature records derived from sites that experience (even intermittent) intense melt events.

Table 3 indicates PDD values observed at individual snow-pit sites were not as high as those experienced at the firn-core drill site over the 40 year record. Linear relationships between PDD or per cent melt and isotopic modification are used to extrapolate between the amount of isotopic modification observed at the lower-elevation snow-pit sites and the firn-core site. These empirically derived linear relationships are based on the conservative estimates of isotopic enrichment observed at TM380, and are estimated to be 0.08‰(PDD)⁻¹, with a PDD threshold of 2.5 days for the absolute melt scenario, and 0.03‰(% melt)⁻¹, with a threshold of 5% for per cent melt.

Linear extrapolation of these values is likely to underestimate temperature reconstruction errors, as there is thought to be a transition from closed- to open-system processes during the melt season which is more likely to result in an exponential relationship between melt amounts and isotopic modification, with an absolute threshold beyond which isotopic signals are lost. However, without the data to explore this assumption, we use the more conservative linear relationship between these variables.

In order to relate isotopic modification to temperature-error estimates, a δ¹⁸O–temperature relationship must be assumed. A broad range of δ¹⁸O–temperature relationships have been reported in the literature, with spatial slopes of 0.61‰(°C)⁻¹ derived by Reference Giovinetto, Holdsworth, Fisher, Waters and ZwallyGiovinetto and others (1997) for the eastern Canadian Arctic and 0.67‰(°C)⁻¹ derived by Reference Johnsen, Dansgaard and WhiteJohnsen and others (1989) for West and South Greenland. However, because this study focuses on temperature reconstructions from a single site over time, a lower temporal slope is considered to be more appropriate. Temporal slopes reported by Reference WhiteWhite and others (1997) for Greenland ice cores range between 0.16 and 0.54‰(°C)⁻¹, with an average value of 0.31‰(°C)⁻¹. Here we use a value of 0.54‰(°C)⁻¹.

The isotopic modification factors presented above for absolute or per cent melt can be used to determine the average annual isotopic modification expected across the entire historical firn-core record or for individual years. The firn-core site has an average historical PDD value of 10.0°C d from 1967 to 2006, which translates into average annual isotopic modifications of 0.6‰. Using the temporal δ¹⁸O–temperature relationship of 0.54‰(°C)⁻¹ presented above, we estimate average annual temperature overestimations of 1.1°C for the firn-core site. If this relationship is extended to our highest-melt summers, 2001 and 1998, with PDD values of 22.0 and 30.0°C d, respectively, isotopic enrichments of 1.5–2.2‰ could be expected, introducing annual average temperature errors of +2.7 and 4.1°C.

More conservative temperature-error estimates result if per cent melt values are used. These values result in an isotopic modification of 0.03‰(% melt)⁻¹, with a threshold of 5%. The 5% melt threshold is consistent with results presented by Reference Koerner, Fisher and Goto-AzumaKoerner and others (1999), where chemical signals were well preserved in an ice core drilled in Agassiz Ice Cap, Ellesmere Island, with a melt index of <5%. The average per cent melt value from 1967 to 2006 for the firn-core site is 10%. This translates into average annual isotopic modification of +0.2‰, resulting in an average annual temperature overestimation of 0.3°C for the firn-core site from 1967 to 2006. Isotopic enrichments of +0.8−0.9‰ would be expected if this relationship is extended to our high-melt years, 2001 and 1998, corresponding to average annual temperature overestimates of +1.5 and 1.7°C, respectively.

Annual accumulation at the firn-core site decreases over the 40 year record from 1967 to 2006 (Fig. 9). These decreases are accompanied by increases in absolute and per cent melt amounts at the site. As a result of these trends, the amount of isotopic modification observed at the firn-core site is expected to also be increasing.