Non-climatic signal in ice core records: lessons from Antarctic mega-dunes

Introduction Conclusions References


Introduction
Mega-dunes are one of the most intriguing and spectacular phenomena in Antarctica. The first reports on the existence of the huge waves on the surface of the Antarctic ice sheet was made soon after the beginning of the extensive exploration of the Antarctic interior during the IGY (Dolgushin, 1958), although the term "mega-dunes" was not yet 5 used at that time.
In 1988 Swithinbank suggested to call such waves "mega-dunes" (Swithinbank, 1988) based on their similarity to the desert sand mega-dunes. At present this term is conventionally used to describe the specific dunes observed in central East Antarctica 15 (Albert et al., 2004;Alberti and Biscaro, 2010;Arcone et al., 2012b;Fahnestock et al., 2000;Frezzotti et al., 2002b), which form the system of parallel ridges with the wavelength of 2-5 km, the amplitude 2-8 m, and the length of the ridges of up to 100 km.
The first observations of relationship between the ice sheet surface topography (surface slope) and snow accumulation rate have shown that the dunes strongly redis- 20 tribute the snow with the increased accumulation in the concaves and reduced accumulation on the convexities (Black and Budd, 1964). This relationship has been later confirmed in a number of studies, e.g. Anschütz et al. (2007), Dadic et al. (2013), Ekaykin et al. (2002), Frezzotti et al. (2007), Fujita et al. (2011), Hamilton (2004, Kaspari et al. (2004), Richardson et al. (1997), Rotschky et al. (2004). These studies have Introduction  (Black and Budd, 1964;Frezzotti et al., 2002b;Van der Veen et al., 1999;Whillans, 1975). The first dedicated ground survey of mega-dunes was made by Frezzotti et al. (2002b). It was shown, in particular, that snow is removed from the leeward slopes of the dunes where specific erosional type of snow, "glaze surface", is formed. In con-5 trast, snow accumulation is increased on the windward slopes that are characterized by the depositional types of the snow microrelief.
Since the 1980s the mega-dunes are observed with the use of the satellite methods (Alberti and Biscaro, 2010;Fahnestock et al., 2000;Scambos et al., 2012;Swithinbank, 1988), which has revealed that these snow features are widely presented in Antarctica 10 occupying in total about 500 000 km 2 .
The Antarctic glaciology has gained a lot from implementing the ground penetrating radar (GPR) technique (Eisen et al., 2008). The GPR survey has also been made in mega-dune areas (Anschütz et al., 2006;Arcone et al., 2012a, b;Eisen et al., 2005;Frezzotti et al., 2002a). In particular, this allowed discovering the mega-dune-like 15 structures in the central Antarctica outside the "classical" mega-dune areas. Similar to mega-dunes, they are characterized by persistent zones of snow erosion (glaze surfaces) and increased accumulation. The disturbed stratigraphy that marks the buried glaze surfaces is found at the depths more than 2000 m, which suggests that these structures have been persistent for tens of thousands of years (Arcone et al., 2012a, b). 20 The precipitated snow is not simply re-distributed in the mega-dune area. Indeed, it is widely recognized that the wind-driven sublimation is an important part of the surface snow mass-balance (Bintanja and Reijmer, 2001;Lenaerts et al., 2010;Thiery et al., 2012) removing from 20 to 75 % of precipitation (Frezzotti et al., 2004(Frezzotti et al., , 2007. In the mega-dunes this figure may increase to 85 % (Frezzotti et al., 2004).Thus, the wide 25 extent of the mega-dune fields and glaze surfaces (that occupy in total more than 10 % of the continent area), where snow drift processes are intensified, must be taken into account for correct estimate of the Antarctic surface mass balance (Das et al., 2013;Scambos et al., 2012;Zwally et al., 2015). Introduction Physical properties of snow in the mega-dune areas have been studied by Albert et al. (2004), Courville et al. (2007), Gregory et al. (2014, Severinghaus et al. (2010). In particular, the snow erosion zones of mega-dunes are represented by coarse-grained snow (depth hoar) characterized by increased air permeability. The processes taking place in snow under near-zero accumulation help to understand the data on isotopic 5 composition of gas trapped in the ice core air bubbles (Severinghaus et al., 2010). It is suggested that low-accumulation highly permeable snow zones, similar to that currently existing in the mega-dune areas, had large extent in Antarctica in the glacial times (Dreyfus et al., 2010).

Conclusions References
Chemical properties of the mega-dune snow were considered in very few studies (Dixon et al., 2013). It is noted that the surface slope may, at least in the coastal areas, affect the snow chemistry (Mahalinganathan et al., 2012). The strong post-depositional metamorphosis of snow in the mega-dunes has to modify its stable water isotope properties (Courville et al., 2007;Frezzotti et al., 2002b;Neumann et al., 2005). It is also known that irregular snow redistribution by wind due 15 to complex surface topography does affect the isotopic content of the deposited snow, which cause a poor correlation of isotopic profiles obtained in two points separated by only a short distance (Benoist et al., 1982;Ekaykin et al., 2014;Karlöf et al., 2006). However, no systematic study of snow isotopic composition in the mega-dunes has been conducted up to now. 20 In the summer seasons of 58th, 59th and 60th Russian Antarctic Expeditions (RAE), 2013-2015, we carried out complex glaciological investigations in the mega-dune area located about 30 km to the East from Russian Vostok Station (Fig. 1). In this paper we analyze the spatial distribution of the snow isotope content in the mega-dunes.

Glaciological and stable water isotope data
In January 2013 the Vostok mega-dune area was visited for the first time. The accumulation-stake profile was established perpendicular to the mega-dune crest. The total number of stakes was 21 (named MD00 to MD20), the distance between adjacent 5 stakes was about 100 m, and the total length of the profile was 1983 m (Fig. 1). The samples of the upper 1.5 m of snow were also taken near each stake to be analyzed for the concentration of the stable water isotopes (δD, δ 18 O and δ 17 O).
In January 2014 and January 2015 the stakes were revisited, and the repeated measurements of their heights and surface snow density allowed obtaining the amount of snow accumulated during 2 years (January 2013-January 2015). The snow samples were taken again for chemical and isotopic analyses.
In January 2015 we also drilled a 20 m borehole in point MD00 (Fig. 1). In the obtained firn core we measured snow density and took samples for stable water isotope analysis with a resolution of 10 cm. 15 The concentration of heavy water isotopes (δD and δ 18 O) in 42 snow surface samples taken in 58th and 59th RAE, as well as in 183 samples from MD00 core, was measured at Climate and Environmental Research Laboratory (CERL) using a Picarro L2120-i analyzer. Our working standard (VOS), measured after every 5 samples, was made of the light Vostok snow and calibrated against the IAEA standards VSMOW-20 2, GISP and SLAP-2. The reproducibility of results defined by re-measurements of randomly chosen samples was 0.04 ‰ for δ 18 O and 0.2 ‰ for δD, which is 2 orders of magnitude less than the natural variability of the snow isotopic composition (see below) and thus satisfactory for the purposes of the study.
In October 2015 we also measured 17O-excess values in the samples collected 25 during the 59th RAE using a Picarro L2140-i analyzer. For this, each sample was measured 15 times in the high-precision mode and we took an average of the last 10 measurements. against VSMOW-2, GISP and SLAP-2 (taking into account that they have 17O-excess values of, correspondingly, 0, 22 and 0 per meg; Schoenemann et al., 2013). The 17Oexcess value of VOS was found to be 0 per meg, similar to SLAP. The reproducibility of the 17O-excess values of individual samples was 8 per meg. All the data discussed in this paper is presented in Table 1.

GNSS positioning
The absolute altitude and location was determined with high accuracy along the profile using the geodetic GPS technique. Therefore the Bernese GPS Software 5.1 (Dach et al., 2007) was used to process the two kinematic GNSS profiles (K58B and K58C) as a combined differential solution from 10 GPS and GLONASS observations. As reference stations for this network solution we used two local receivers at Vostok station in a distance of less than 50 km and additional two reference stations at the coast with baseline lengths of about 1350 km (near the Russian research stations Progress and a station of the global IGS-network near the Australian Station Casey). After reducing the antenna positions to the snow surface 15 we estimated the accuracy by calculating the height differences at track crossovers. Crossovers inside one track imply an internal RMS of the differences of 2.9 cm (at 160 crossover points) for track K58B and 2.4 cm (at 9 crossover points) for track K58C. With a RMS of 7.7 cm at 5159 crossovers between the two tracks we can estimate the absolute precision of a single kinematic surface height according to the variance 20 propagation to about 5.4 cm.

GPR data
During the austral summer field season of the 58th Russian Antarctic Expedition (January 2013) the GPR profiling was performed to study the snow-firn layer structure of the mega-dune area. The GPR equipment was installed on 2 sledges towed by a ski-doo. The route of the GPR profiling was the same with the geodetic observations. In total, about 80 km of the GPR profiles were obtained ( Fig. 1), though in this paper we only use the 2 km section obtained along the glaciological profile (points MD00-MD20 in Fig. 1).
The main problem in the processing and interpretation of the GPR data is the di-5 electric properties of the media where the electromagnetic waves are propagating. We used the model published by Popov and Eberlein (2014) to transform the radio-echo time-section ( Fig. 2) into the depth section. To calculate the vertical electromagnetic wave speed we used the firn density data measured in MD00 core. In Fig. 2 we showed the GPR registration recorded along the glaciological profile 10 (MD00-MD20).

Results
The mega-dune formation is related to a sharp increase of the ice sheet slope in the prevailing wind direction (SPWD) (Frezzotti et al., 2002b). The Vostok mega-dunes are not an exception, as they form leeward from the eastern shore of the Lake Vostok, 15 where the SPWD changes from near zero or even negative values (interestingly, in the closest vicinities of Vostok Station the wind is blowing uphill) to about 1.6 m km −1 .
The latter figure generally agrees with the Frezzotti et al. (2002) conclusion that the mega-dunes only develop where the SPWD is from 1 to 1.5 m km −1 .
The wavelength of the Vostok mega-dunes are about 1.9 km, and the amplitude (the 20 elevation change between the dune crest and the nearest windward hollow) is about 1.2 m, i.e. they are relatively small compared to those reported in the above mentioned studies.
Below we present the results of the glaciological investigations in the Vostok megadune area (Fig. 3).

Accumulation rate and isotopic content of snow in mega-dunes
Due to the subsequent measurements of the heights of the stakes established across the mega-dunes, we were able to define the snow accumulation between January 2013 and January 2015 (Fig. 3e). One may clearly see the regular spatial variability of the snow build-up. In accordance with the previous studies (see the review in Introduction), 5 the snow is removed from locations with the increased surface slope (leeward side of the dunes) and deposited where the slope is decreased or inversed (hollow between dunes and windward side of the dunes). In a distance of few hundred meters the accumulation changes by an order of magnitude, from −0.5 to 16 cm of snow (or from −0.2 to 58 mm we according to the surface snow density, Fig. 3d). This range is larger than 10 that reported by Frezzotti et al. (2002b) (from 7 to 35 mm). The mean annual accumulation over the 1 dune wavelength is 22 mm, which is very similar to the accumulation at the Vostok stake network (23 mm). If the precipitation rate at Vostok station and in the mega-dune area was the same, then our result does not support the observation that over the mega-dune areas the accumulation is reduced due to the wind-driven The surface snow density does not show any distinct spatial variability (Fig. 3d). The mean snow density (0.355 g cm −3 ) is slightly higher than that measured at Vostok stake network (0.33 g cm −3 ).
During the field-works we also did not observe big difference between snow surface 20 character in leeward and windward slopes of the dunes (Fig. 4). The erosion zone does not demonstrate the dominance of the glaze surface, and no big sastrugi are observed in the accumulation zone, as reported by Frezzotti et al. (2002b) for the Victoria Land mega-dune field. The spatial variability of the accumulation rate covaries well with the surface slope: 25 the smaller is the slope, the higher is accumulation (Fig. 3f and e), in accordance with the previous observations (Anschütz et al., 2006).  Fig. 3a-c we show the isotopic composition (δD, dxs and 17O-excess) of the upper 1.5 m of snow sampled twice near each point of our profile. One can see a wave in snow isotopic content (δD) with the magnitude of about 20 ‰ and the wavelength similar to that of the mega-dune. There is a negative covariation between snow isotopic composition and accumulation rate (correlation coefficient, −0.38, is not statistically 5 significant due to the small number of points). A very similar picture was previously observed in the closest vicinity of Vostok, where positive spatial anomalies of isotopic composition correspond to the negative anomalies of snow accumulation, though on the smaller spatial scale (Ekaykin et al., 2002).
We explain this behavior of the snow isotopic composition by different post-10 depositional alteration of the initial isotopic composition of snow precipitation deposited in the low-and high-accumulation zones of the mega-dunes. Indeed, the erosion zone is characterized by "a long, multiannual, steep temperature-gradient metamorphism" (Frezzotti et al., 2002b, p. 8). Thus, the snow here should be enriched in heavy isotopes due to strong post-depositional modification (Town et al., 2008) that may be further facilitated by the increased permeability of the snow in such locations (Albert et al., 2004). We may speculate that in the mega-dunes described by Frezzotti et al. (2002b), characterized by a very strong modification of the snow physical properties, the isotopic transformation should be even stronger than in the Vostok dunes. An alternative explanation of negative spatial relationship of isotopic composition and 20 snow accumulation was suggested by Ekaykin et al. (2002). Since in winter the snow crystals are smaller and wind speed is higher, this snow could be easier re-distributed by wind comparing to snow precipitated in summer. If so, in the erosion zone of the mega-dunes the proportion of summer snow is larger than in the accumulation zone. We may use the isotopic data to determine which mechanism, "post-depositional" or 25 "re-distributional" (or both) is mainly responsible for the anomaly of the snow isotopic composition in the mega-dune area.
The observed dxs/δD and 17O-excess/δD slopes (ratios between the standard deviations of the smoothed profiles shown in Fig. 3a-c)  and 0.9 per meg/‰. During the post-depositional changes of the snow isotopic composition these slopes are −0.2 ‰/‰ and 0.4 per meg/‰ (Ekaykin et al., 2016). During the seasonal cycle of the isotopic composition of snow precipitation at Vostok, these parameters are related by slopes −0.1 ‰/‰ and 0.4 per meg/‰ (Landais et al., 2012). Thus we may conclude that the mixing of the summer and winter precipitation in dif-5 ferent proportions cannot explain the variability of snow isotopic composition observed in the mega-dune area, since the variability of 17O-excess and of dxs would be significantly smaller. The post-depositional factor would better explain the observed snow isotopic composition in the mega-dunes, but still the variability of 17O-excess seems to be too strong. Note, however, that the data of Ekaykin et al. (2016) were obtained in laboratory experiments, not in natural conditions, so the 17O-excess/δD slopes reported there may be underestimated. We should also note that the 17O-excess values positively covariate with the accumulation rate (Fig. 3c and e), though one would expect a negative covariation in case if the snow isotopic composition variability is due to the post-depositional processes. 15 At present we do not know if this positive covariation is caused by errors in the 17Oexcess values, or it suggests another mechanism that creates isotopic anomalies in the mega-dune area.

Mega-dune drift
We used the GPR data to reconstruct the previous positions of the dunes, and to 20 calculate the velocity of the dunes drift.
In the GPR profile taken across the mega-dunes (Fig. 2), we see several distinct internal reflection horizons (IRH). For 7 of them we defined the depths (Table 1) and, subtracting these depths from the ice sheet elevation, we could define the absolute altitude of each IRH (Fig. 3g). Thus we can see the buried surfaces of our dune and 25 may trace its drift in time.
For this, we first need to date each IRH. We used the density profile obtained from the MD00 core and the average snow accumulation rate in the mega-dune area in order 6919 Introduction

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | to calculate the depth-age function and determine the age of each IRH (Fig. 3g). The uppermost IRH marks the surface of the dune about 130 years ago, and the lowermost -530 years ago. We chose 3 fold hinges (the summit of crests and two lowest points of the fold dips) to trace the dune drift. On average, the dune is drifting upwind with the rate of 4.6 ± 1.1 m yr −1 . This corresponds very well with the value reported by Frezzotti et al. (2002b), 5 m yr −1 . With this velocity a dune drift by 1 wavelength in about 410 years.
As pointed by Arcone et al. (2005), the apparent dune drift velocity observed in the GPR images is a combination of the real dune velocity and the ice movement, and the 10 real dune velocity is higher than the observed one. According to Richter et al. (2013), ice flow velocities in this region do not exceed 2 m yr −1 , so the real dune drift velocity could be up to 6.6 m yr −1 . However, the ice is moving almost in parallel with the dune crests (from north-west to south-east). So, the projection of the ice speed vector on the MD profile is close to 0 m yr −1 , and the correction to the dune drift velocity due to 15 the ice movement should be close to zero, too. Finally, for the purposes of our study we need not real, but the resultant dune velocity observed by GPR, so in the further calculations we use the apparent dune velocity of 4.6 m yr −1 .

Non-climatic temporal oscillation related to the mega-dune drift
When the dune drifts, the spatial anomalies in snow physical properties, accumulation 20 rate and isotopic composition are drifting accordingly. For example, the point MD00, now located at the leeward side of the dune with reduced accumulation and enriched isotopic composition, about 300 years ago was in the hollow between dunes with increased accumulation and lower heavy isotope content. If one drills an ice core in the mega-dune area, he would see a quasi-periodic (with the period of 410 years) oscilla- 25 tions in snow accumulation and isotopic composition related to the dune drift.
Let us simulate such an oscillation that we would see in a core drilled at MD00 point.  Fig. 5a we showed a temporal variability of snow accumulation (blue) and isotopic composition (red) that should be seen in point MD00 when the dune crosses this point. To construct these curves, we simply divided the distance of each point in Fig. 3a and e by the above mentioned velocity of the dune drift. We also showed in Fig. 5a the climatic variability in Vostok region over the same time interval (Ekaykin et al., 2014) in purple.

5
Note that the amplitudes of the both components are similar.
Combining the dune-related and climatic components, we obtain the expected temporal variability of snow isotopic composition in MD00 (Fig. 5b). Then we transform it to a vertical isotopic profile using the depth-age function presented in Fig. 5c. This function takes into account the significant dune-related variability in snow accumulation rate ( Fig. 5a), this is why it is essentially non-linear. The resulting simulated vertical isotopic profile is presented in Fig. 5d by red line. In the upper part of the profile the isotopic oscillations are compressed due to the low accumulation rate, and deeper, when the accumulation is higher, they are stretched.
In our simulations we do not take into account that the mega-dune snow may ex- 15 perience enhanced diffusive smoothing due to the increased ventilation of the snow column. In this case the isotopic profile could be substantially smoothed.
In Fig. 5d we also showed by the blue line the real isotopic profile from the MD00 core. One can see a good resemblance between them, except for the very bottom part of the MD00 core. Indeed, at the depth of 20 m the core has isotopic composition of 20 −420 ‰. Neither climatic record, nor the isotopic profile from the mega-dunes (Fig. 5a) demonstrate such high isotopic value, this is why we could not reproduce it in our simulations.

Discussion -non-climatic variability in ice cores
In the previous sections we demonstrated that the snow isotopic composition has sig-25 nificant spatial variability in the mega-dune area, suggested a possible mechanism to explain this variability, and then explained how this "dune-related" signal is transferred to an ice core isotopic profile. We calculated an artificial ice core isotopic profile in the mega-dune area and compared it with the real ice core isotopic profile.
In the case of MD00 core we know that the "signal" we see is mostly related to a dune drift, but how can one separate the climatic signal from non-climatic variability in real ice cores?
Indeed, it is commonly understood that a mega-dune area is an unsuitable place to drill ice for climatic studies, but it does not mean that the locations outside the megadune fields are free from non-climatic, "relief-related" variability.
As an example we may mention the South Pole Station region that is not a megadune area, but detailed topographic survey shows mega-dune-like features with a typ-10 ical amplitude of few meters and wavelength of several kilometers -see Fig. 8 in Van der Veen et al. (1999) andFig. 2 in Hamilton (2004). Unlike the mega-dunes, these snow hills are not elongated, but rather round in shape. The authors suggest these structures are not stationary, but slowly change their locations, which causes temporal non-climatic variability of snow accumulation rate with the period of several hundred or 15 few thousand years. Very similar structures are observed around the Kohnen Station (Eisen et al., 2005) and in West Antarctica (Arcone et al., 2005).
Even the vicinities of the main domes cannot be considered as "dune-safe". Indeed, the study of the snow isotopic composition profile in two neighboring cores drilled at Dome C showed a very low signal-to-noise ratio likely related to the local ice sheet 20 topography (Benoist et al., 1982).
In Dronning Maud Land the ice cores drilled in relatively short distance one from another demonstrate opposite trends in the snow accumulation rates over the past 200 years (Oerter et al., 2000), which may be considered as the influence of the nonclimatic factors. 25 In general, in low-accumulation sites signal-to-noise ratio in both snow accumulation rate and isotopic composition is very small, being of the order of 0.2 (Ekaykin et al., 2014). The noise, related to the snow re-distribution by wind and/or post-depositional processes, is larger than the climatic signal even at the centennial scale. This means that to study climatic variability with the periods less than 10 3 -10 4 years in the low accumulation area (which comprises most of the East Antarctica (Arthern et al., 2006)) more than one ice core should be investigated for each location.
The influence of snow topography on snow accumulation is known and to large extent understood on the spatial scale from 10 −2 to 10 1 m (micro-relief) and from 10 3 to 10 6 m 5 (mega-dunes and continental scale). However, very little is known about the scale from 10 1 to 10 3 , the range of "meso-dunes" (Eisen et al., 2008;Ekaykin et al., 2002). It is likely that the drift of the meso-dunes causes the non-climatic temporal oscillations of snow isotopic composition and accumulation rate with a period of few tens of years due to mechanisms similar to those described in this paper for the mega-dunes. Further 10 studies of this phenomenon are needed.

Conclusions
The ice cores are priceless source of numerous and diverse paleo-climatic data, and this will hold true even despite the unavoidable limitations. One of the most important limitations is related to a high level of noise which contaminates the climatic signal 15 on relatively short time scales (years to millennia), especially in the low-accumulation areas. The main reason of this noise is a complex snow/ice sheet topography that leads to snow re-distribution due to wind activity, which is further complicated by the post-depositional processes.
In this paper we present the results of the field works carried out during three Antarc-20 tic summer seasons in the vicinity of Vostok Station. We mainly deal with the influence of large snow relief forms, mega-dunes, on the snow isotopic composition. We demonstrate that the leeward sides of the dunes are characterized by reduced accumulation and increased concentration of heavy water molecules likely due to post-depositional alteration of the snow isotopic content. In opposite, windward sides of the dunes accu- Using the GPR data, we were able to trace the drift of the dunes and to calculate their velocity, 4.6 ± 1.1 m yr −1 . This allowed us to simulate the temporal variability of the snow isotopic composition that would be observed in a given point due to the passing of the mega-dune across this point. Then we compared this artificial vertical profile of the snow isotopic composition with the real isotopic data from a firn core drilled in the 5 mega-dune cite. We showed that the two profiles are very similar.
Using the examples published in literature we suggest that similar non-climatic oscillations in snow accumulation rate and isotopic composition are widespread in Antarctica, even beyond the mega-dune fields.
We also suggest that the mega-dunes are a unique environment that provides the 10 necessary conditions to test different hypothesis. For example, in a short distance one can find locations absolutely different in terms of snow accumulation rate, isotopic composition, physical and (likely) chemical properties, which could be used to study the post-depositional processes, to model glacial conditions (Severinghaus et al., 2010) etc. 15 In the future studies we plan to investigate the spatial variability of chemical content, the concentration of microparticles and other compounds in the surface snow in the Vostok mega-dune area. Introduction  The values of snow accumulation rate (blue) and isotopic composition (red) that could be observed in point MD00 if one would measure them as long as the dune travel across this point. To calculate this we used the data from Fig. 3a and e, and data on the dune drift velocity. Purple -climatic variability of the snow isotopic composition in the Vostok region taken from Ekaykin et al. (2014). (b) A combination of climatic and dune-related isotopic variability (red + purple from Fig. 5a). (c) Depth-age function for the snow thickness in point MD00. (d) Simulated vertical profile of snow isotopic composition calculated using the data from Fig. 5b and depth-age function (Fig. 5c), in red, compared with the real vertical profile of snow isotopic composition measured in the core drilled in point MD00, in blue.