Introduction
Global warming affects the cryosphere, increasing the flow and melt rates of large ice masses, thus accelerating sea level rise. A better understanding of ice mechanics is essential for improving projections of ice loss under various climate-change scenarios and refining ice dynamics models used for dating paleoclimate ice-core records (IPCC, 2021). The foundations of ice mechanics have been investigated through laboratory-based tests (e.g., Glen, Reference Glen1955; Jacka and Maccagnan, Reference Jacka and Maccagnan1984; Budd and Jacka, Reference Budd and Jacka1989; Treverrow and others, Reference Treverrow, Budd, Jacka and Warner2012). Experience suggests that polycrystalline isotropic ice flow follows a power law known in glaciology as Glen's Flow law:
where $\dot{\varepsilon }$
is the secondary (minimum) strain rate, A the flow parameter, σ the stress and the power exponent usually set to n = 3 (Glen, Reference Glen1952, Reference Glen1955). The flow parameter (A) is dependent on ice temperature, impurities and other factors (Kostecka and Whillans, Reference Kostecka and Whillans1988; Reeh, Reference Reeh1988; Dahl-Jensen, Reference Dahl-Jensen1989; Cuffey and Paterson, Reference Cuffey and Paterson2010). The nature of the impurities is diverse, ranging from volcanic ash and sea salt to mineral dust and other aerosols (generated e.g. by forest fires or human activities). Once these aerosols are deposited over the snow surface, they become part of the ice in the form of dissolved or undissolved impurities (particles). The scientific literature refers to high-impurity layers as cloudy bands (CB) due to their turbid and darker appearance compared to the surrounding ice (e.g. Gow and Williamson, Reference Gow and Williamson1976; Faria and others, Reference Faria, Weikusat and Azuma2014). Impurities affect the ice flow through their interactions with the ice microstructure, including its grain sizes and shapes (grain stereology; Faria and others, Reference Faria, Kipfstuhl and Lambrecht2018), and the fabric (preferential orientations of the c-axes). Ice cores extracted from polar areas (Siberia, Alaska, Northern Canada, Antarctica, Greenland) revealed a sharp decrease in the grain size inside the CB and a higher amount of this type of layers in glacial periods (Paterson, Reference Paterson1991; Thorsteinsson and others, Reference Thorsteinsson, Kipfstuhl, Eicken, Johnsen and Fuhrer1995; Faria and others, Reference Faria, Weikusat and Azuma2014). For instance, that effect is noticeable in ice belonging to the transition between the Holocene and the Last Glacial Maximum (Duval and Lorius, Reference Duval and Lorius1980; Petit and others, Reference Petit, Duval and Lorius1987; Lipenkov and others, Reference Lipenkov, Barkov, Duval and Pimienta1989; Thorsteinson and others, Reference Thorsteinsson, Kipfstuhl and Miller1997).
Some of the early works linking the debris-rich levels to changes in ice rheology were Swinzow (Reference Swinzow1962), Gundestrup and Hansen (Reference Gundestrup and Hansen1984), Etheridge (Reference Etheridge1989) or Paterson (Reference Paterson1991). For example, one of the analyses consisted of monitoring a borehole closure rate in the Devon Island ice cap (Canadian Arctic), where results revealed an anomalous closure rate near the bottom. Subsequent dating showed the ice with this peculiar mechanical behaviour belonged to the Last Glacial Cycle (~115–11.5 ka; Dansgaard, Reference Dansgaard1973). Later, Fisher and Koerner (Reference Fisher and Koerner1986) observed the same phenomena in the Agassiz ice cap. Paterson (Reference Paterson1991) found that, for a given temperature and shear stress value, the ice strain rate of the Last Glacial Maximum ice was three times higher than the Holocene ice. Furthermore, it was observed that the crystallographic c-axes tended to approach a vertical maximum (Paterson, Reference Paterson1991) due to the rotation of grains under a simple shear regime, forcing the basal planes (where preferential slip occurs) to lie parallel to the shear plane, creating a favourable condition for ice deformation and flow. That maximum will be more marked compared to other fabrics where the c-axes exhibit similar arrangements, such as those caused by uniaxial compression, in which they are around the vertical in a girdle-like shape (Jacka and Maccagnan, Reference Jacka and Maccagnan1984). In addition, diffusional creep and grain boundary sliding have been considered by some authors, offering the possibility of grain-size-sensitive deformation mechanisms (Goldsby and Kohlstedt, Reference Goldsby and Kohlstedt1997, Reference Goldsby and Kohlstedt2001; Cuffey and others, Reference Cuffey, Thorsteinsson and Waddington2000; Faria and others, Reference Faria, Hamann, Kipfstuhl and Miller2006). These impurity effects of the ice flow have been identified in deep ice cores like Dye 3 (Dahl-Jensen and Gundestrup, Reference Dahl-Jensen and Gundestrup1987; Shoji and Langway, Reference Shoji and Langway1987), GRIP (Miyamoto and others, Reference Miyamoto1999), EDC (Durand and others, Reference Durand2009), WAIS (Fitzpatrick and others, Reference Fitzpatrick2014), EPICA-DML (Faria and others, Reference Faria, Hamann, Kipfstuhl and Miller2006, Reference Faria2009, Reference Faria, Freitag and Kipfstuhl2010; Weikusat and others, Reference Weikusat2017) or NEEM (Montagnat and others, Reference Montagnat2014).
Ice microstructure in mountain glaciers
Microstructure analyses have been usually carried out in polar regions (Greenland and Antarctica ice sheets), whose thickness can surpass 4000 m, providing the opportunity to study the long-term evolution of deep ice layers under stable temperature and stress conditions and perform paleoenvironmental reconstructions up to 800 000 years (EPICA Community Members, 2004; Jouzel and others, Reference Jouzel2007). In contrast, conducting the same type of microstructure studies on mountain glaciers is much less common, as it involves more technical difficulties due to their steeper topography and smaller volume, which imply shorter time series, a more heterogeneous deformation and a higher sensitivity to seasonal temperature variations and global warming. Strong temperature variations hinder microstructural studies because they can trigger thermodynamic processes that continuously modify the ice microstructure and fabric (e.g. dynamic recrystallization), especially in glaciers located in temperate regions. However, thanks to their sensitivity, mountain glaciers are excellent regional records of environmental variations of proxies like air temperature, precipitation, atmospheric chemistry, etc. (Dyurgerov and Meier, Reference Dyurgerov and Meier2000; Grunewald and Scheithauer, Reference Grunewald and Scheithauer2010; Marshall, Reference Marshall2014). Furthermore, these glaciers are good indicators of the effects of past and current human activities, since they are usually close to densely inhabited regions (Zhang and others, Reference Zhang, Kang, Gabrielli, Loewen and Schwikowski2015).
Regarding studies focused only on ice microstructure or fabric in mountain glaciers, one of the first works was by Perutz and Seligman (Reference Perutz and Seligman1939), which investigated the glacier structure and flow mechanisms of the Great Aletsch glacier. Twelve years later, Rigsby (Reference Rigsby1951) analysed the ice fabrics of an ice core extracted from Emmons Glacier (Washington, USA) and used the results some years later in a comparative study that included glaciers from different climatic contexts, such as the Malaspina Glacier (Alaska), Saskatchewan Glacier (Alberta, Canada), Moltke Glacier and the Nunatarssuaq and Tuto ice ramps near Thule (Greenland; Rigsby, Reference Rigsby1960). A coetaneous study is the fabric analysis of Blue Glacier (Olympic National Park, Washington state; Kamb, Reference Kamb1959). In recent decades, we can highlight studies on the Tsanfleuron Glacier (Switzerland; Tison and others, Reference Tison and Hubbard2000), Cole Gnifetti Glacier (Swiss-Italian Alps; Kerch, Reference Kerch2016), Storglaciären glacier (Sweden; Monz and others, Reference Monz2021), Rhone Glacier (Swiss Alps; Hellmann and others, Reference Hellmann2021), an ice apron in the Triangle du Tacul (Mont Blanc Massif; Guillet and others, Reference Guillet, Preunkert, Ravanel, Montagnat and Friedrich2021) and Jarvis Glacier (Alaska; Clavette, Reference Clavette2020). However, most works focus only on the fabrics, superficially describing other microstructural features like the shape, size and interactions between grains.
Our research group is part of a network whose aim is the study of the Monte Perdido Glacier. In this context, we are contributing by characterizing, for the first time, the microstructure of its ice, looking at the interaction between its elements (i.e. grain boundaries; GB, sub-grain boundaries; sGB, bubbles and impurities). For this we used high-quality photos and micrographs, cross-polarizers observations and transmitted light microscopy. In this study, we focus on a section of the central part of an ice core drilled in the lower accumulation zone of the glacier, characterized by its high impurity content.
Study area
Monte Perdido Glacier (42°40′50″N, 0°02′15″E), located in the Ordesa y Monte Perdido National Park (Central Spanish Pyrenees; Fig. 1a), is the third largest glacier in the Pyrenees (0.37 km2 in 2016; Rico and others, Reference Rico, Izagirre, Serrano and López-Moreno2017), although recent studies have reported a 12.9% area loss from 2011 to 2020 (Vidaller and others, Reference Vidaller2021). The glacier lies on the northern slope of the Monte Perdido Massif, below its main summit (3355 m a.s.l.; Fig. 1b). The thickness varies from 30 to 50 m in the best-preserved areas of the glacier (López-Moreno and others, Reference López-Moreno2019). The Glacier's meltwater drains via the Cinca River, which flows through a longitudinal (E-W) basin called Tucarroya Cirque (5.8 km2) that bonders the Tucaroya Ridge and Eastern Astazu Peak (3071 m a.s.l.) on the north, the Western Astazu Peak (3013 m a.s.l.) on the west and an immense cliff of 500–800 m (García-Ruiz and Martí-Bono, Reference García Ruiz and Martí Bono2002), composed by the Monte Perdido Peak (3355 m a.s.l.), Cilindro Peak (3322 m a.s.l.) and the Marboré Peak (3247 m a.s.l.) on the south (Fig. 1b). Currently, the glacier is formed by two bodies: the upper one and the lower one, with average elevations of 3110 and 2885 m a.s.l., respectively (Julián and Chueca, Reference Julián and Chueca2007). The climatic context is high-mountain Atlantic-Mediterranean transition, with a mean annual temperature of 5°C (measured at Góriz station, 2250 m a.s.l., 2.7 km from the glacier, on the south face), and a mean summer temperature (June–September) measured at the foot of the glacier in the period 2014–2017 of ~7°C (López-Moreno and others, Reference López-Moreno2019). Assuming a temperature drop of 0.55–0.65°C every 100 m, the average annual elevation of the 0°C isotherm is at ~2945 m a.s.l., involving a small or even non-existent accumulation area during warm years (López-Moreno and others, Reference López-Moreno2019). Snowfall events can occur at any time of the year, but generally, the accumulation process takes place from November to May, and the melting extends from June to September (López-Moreno and others, Reference López-Moreno2016). Despite the elevation of the upper section, the low avalanche activity and the high slope of ~40° limit the snow accumulation (López-Moreno and others, Reference López-Moreno2019). Results of chronological analyses carried out by Moreno and others (Reference Moreno2021) showed that the glacier's ice record covers the last 2000 years. The Little Ice Age (LIA) period, characterized by glacial advances, is not recorded in the Monte Perdido Glacier ice, since more than 600 years of accumulated ice have been lost due to the anthropogenic warming that followed the LIA.
Figure 1. The red dot indicates the location of the Monte Perdido Glacier. (a) Geographical situation of Monte Perdido Glacier in the Pyrenees. (b) Main peaks in the Marboré Cirque. The yellow box indicates the MP1 ice core extraction site. (c) Zoom into the yellow box of Figure 1b. Brownish areas on the top-right and centre-left parts of the figure are the result of mineral dust deposition events. The rocky outcrop on the right is composed of Paleocene limestones. (d) Detail of the MP1 borehole after extraction.
Materials and methods
In the fall of 2017, three vertical ice cores were recovered from the glacier's lower section (Moreno and others, Reference Moreno2021 and Fig. 1b). The microstructural analyses were carried out at the low-temperature laboratory IzotzaLab, located at the Basque Centre for Climate Change (BC3). The ice cores were stored in a chest freezer at −70°C to limit the microstructural changes triggered by the increases in temperature. During the analyses, the conditions at the laboratory were −25°C and 45% RH. One of the ice cores belongs to the end of the accumulation zone, very close to the equilibrium line (MP1; 42°40′47.7″N, 0°02′15.9″E; Fig. 1d), with a total depth of 410 cm and consisting of several segments (labelled downward from MP1–1 to MP1–11). The dominant structure throughout the MP1 core is that of bubbly ice, with some unclear vestiges of firn in certain layers. The target segment (MP1–6) was made of two sections (the upper one, S 1, and the lower one, S 2) with a total length of 22.6 and 8 cm in diameter, comprising a depth range between 251 and 273 cm within MP1 (Fig. 2a).
Figure 2. MP1–6 segment. (a) MP1–6 lower (S 1) and upper (S 2) sections. (b) Zones (Z) with different bubble number densities delimited by dashed lines. In the lower section, the impurity layer (I.L.) is visible. (c) Position of M 1 and M 2 samples.
Visual stratigraphy
For describing ice features like bubble distribution, ice appearance, or layers with different colouration (e.g. cloudy bands), we photographed the ice core using a zenithally arranged digital camera, a black backdrop and scattered lateral illumination. The picture's output format was ‘raw’, allowing subsequent image processing. Due to the high light scattering produced by the air bubbles, it is hard to identify the ice core's internal features in the visual stratigraphy (Fig. 2a). To solve this problem and reveal the ice-core inner features, we adjusted the RGB channels simultaneously, decreasing the mid-tones brightness level and increasing the contrast with the Affinity Designer™ image software (Fig. 2b). Using a bandsaw (Metabo™ BAS 318), we prepared the samples for cross-polarized and microstructural observations, one from the central part of S 1 (M 1) and another from S 2 (M 2; Fig. 2c).
Observations between crossed polarizers
To determine the polycrystalline natural ice fabric, we can use an optical approach based on ice crystals' birefringence and extinction angle (Rigsby, Reference Rigsby1951; Langway, Reference Langway1958; Kamb, Reference Kamb1959). The birefringence colour of each grain depends on the c-axes orientation, allowing us to distinguish the grain's outlines. For this analysis, we fixed samples to the sample holder with water droplets (water acts as a ‘natural glue’ at −25°C) and used a microtome (Leitz™ 1400) to polish the upper surface to eliminate the irregularities produced by the band saw. Then, we turned around the sample and repeated the same process on the other surface, polishing it until a thickness between 100 and 400 μm was reached, to reveal most of the grains through crossed polarizers. For the observation, each sample was placed between two linear polarizing films, the lower one fixed and the upper one rotated until the polarization directions were 90° to each other (cross-polarization).
Optical microscopy
A microstructural analysis is necessary to understand the grain size evolution and its variations due to interactions with other elements such as sGB, bubbles or impurities. Employing a Leica™ DM6M microscope set inside the IzotzaLab, we scanned the microstructure through transmitted light along bands (2.3 mm × 80 mm) parallel to core axis. The preparation process is similar to that used for the polarization samples, but with a thicker final thickness of 0.5 cm. Before observations, the samples' polished surfaces were subjected to a sublimation process to reveal the microstructure. Sublimation is more intense in the areas where the GB, sGB or point defects intercept the surface, due to their higher free energy. Besides, sublimation eliminates the surface grooves caused by the microtome blades, allowing a clearer observation. The sGB boundaries have shallower, greyish sublimation grooves (Saylor and Rohrer, Reference Saylor and Rohrer1999), unlike GB with higher contrast and a dark grey or nearly black colour. The microstructural elements observable by this method are known as surface elements, and when we move the focus towards the sample inside, they become blurred. By contrast, the interior elements are located inside and are not sublimation products (e.g. slip bands, air bubbles or impurities; Kipfstuhl and others, Reference Kipfstuhl2006; Faria and others, Reference Faria, Kipfstuhl and Lambrecht2018). The time and quality of sublimation depend on the laboratory environmental conditions (temperature, temperature gradient, humidity and air velocity just above the sample surface). To accelerate this thermodynamic process, the sample can be placed under a light bulb or a dry air stream. The microscopy method described above has been widely used in glaciology (e.g. Mullins, Reference Mullins1957; Nishida and Narita, Reference Nishida and Narita1996; Kipfstuhl and others, Reference Kipfstuhl2006). One characteristic of our samples is they have levels with high air bubble content. When we try to observe these samples with the transmitted light microscope, the bubbles appear as black regions, making it hard to distinguish the surface elements, even using a specialized software. Therefore, for better visualization of these elements, we had to resort to a hand-drawn outlining of the GB, sGB and bubbles (e.g., Figs 3–5).
Figure 3. M 1 ice microstructure. To improve the visualization of grain size and shape, the grain boundary (GB) outline is depicted below each scanned band, including also the parts of bubbles exposed to the surface (in black). (a) and (b) Micrographs representing the sample's general appearance. (c) Nucleation of tiny grains along a GB. (d) Cluster of tiny grains, possibly an example of particle-stimulated nucleation (PSN) process. (e) Detail of M 1 under crossed polarizers.
Figure 4. M2 ice microstructure. The dashed black/yellow lines represent the upper limit of the impurity layer. (a) and (b) Microstructure of the upper part of the sample, where the impurity concentration is low. (c) and (d) Microstructure within the impurity layer. (e) Detail of M 2 under crossed polarizers.
Figure 5. Microstructure outlines of the M 1 (Right) and M 2 (left) micrographs. Grain boundaries (GB, black lines), sub-grain boundaries (sGB, red lines) and bubbles (black areas). Grey rectangles represent regions where the sample microstructure is damaged by fractures. The stepped black line represents the upper limit of the impurity layer in M 2. Below it, there is a decrease in grain size and roundness index.
Chemical analysis
To perform a preliminary chemical characterization of the crystalline species of the impurities inside S 2, we extracted a 3 cm3 sample from the central part of M 2 and placed it inside a Petri dish. Subsequently, the sample was melted and evaporated inside a stove at 30°C, partially covered with aluminium foil to avoid external contamination and to allow the water vapour to escape. The chemical analyses consisted of Raman spectroscopic characterization of the precipitated salts and the original impurities remained at the bottom of the Petri dish. The instrument used was the Renishaw inVia confocal micro-Raman spectrometer (Renishaw, UK), which is calibrated daily using a standard silicon slice. Although analyses were carried out with all lasers (785, 633 and 523 nm), the 532 nm diode laser (Renishaw UK RL532C50 with a nominal 300 mW output power) brought the best results. The Micro-Raman spectrometer is also equipped with a CCD detector cooled by the Peltier effect, with a LEICA DMLM microscope (Bradford, UK), which employs an XYZ Stage Control toolbar and a micro camera to explore the target particles. For visualization and focusing, we used the 5× N PLAN (0,12 NA) and 20× N PLAN EPI (0,40 NA) objectives.
Results
In MP1–6, variations in bubble number density (ρ bn) and impurity content define the stratigraphy, but the stratigraphic boundaries defined by bubbles and impurities do not always coincide. The zones with high ρ bn values can be identified by a whitish appearance, in contrast to the low-density zones, where the ice is more translucent and has a dark aspect due to the dark background. We could identify eight zones of high and low ρ bn values, labelled from Z 1 to Z 8 (Fig. 2b). The zones Z 1, Z 3, Z 5 and Z 7 have higher value than Z 2, Z 4, Z 6 and Z 8, being Z 2 the zone with the lowest density. The impurities only define a single reddish-brown layer located in the middle part of S 2, with a thickness of ~3 cm and a tilt of ~10°. Its limits are not well-defined, and the lower limit coincides with the transition between Z 7 and Z 8. It is noteworthy to mention that we are reporting 2D descriptions of structural characteristics with volumetric (3D) variations, so this is only an approximate view. The distribution of bubbles and impurities will vary depending on the observed section.
To analyse the morphological characteristics of the bubbles, we photographed two samples previously prepared for the microscopic observation, named M 1 (extracted from S 1) and M 2 (from S 2), as indicated in Figure 2c. Both samples belong to the central part of each section and are parallel to the ice core axis. Generally, M 1 has bubbles in greater number and size than M 2. We could identify eight domains of different bubble morphological characteristics in both samples, labelled from D 1 to D 8, each one characterized by differences in bubble shape, size and ρ bn values (Fig. 6; Table 1). Domains 2 (D 2) and 8 (D 8) had the smallest and most rounded bubbles, coinciding with the fact that they are areas with the lowest ρ bn values. The pattern of bubbly size and shape observed in D 2 spreads homogeneously across M 1 and M 2. A remarkable feature of D 8 is its morphology because it forms an indentation (notch shape) towards the interior of D 7, with a higher bubble number density. Over the upper limit of D 8, there are clusters with high ρ bn values (Fig. 6b). In the rest of the domains, bubbles with irregular morphologies prevail, and from D 4 to D 7, it seems like bubbles have coalesced, generating larger compound bubbles. There are some correspondences with the visual stratigraphy: D 2 correlates directly with Z 2, while Z 4 can be related to D 5. In the other zones, there is no apparent correlation with domains.
Figure 6. Domains (D) with different values of bubble number density (ρ bn), sizes and shape, delimited by the yellow dashed lines. (a) M 1 sample. (b) M 2 sample. Arrows indicate zones with high ρ bn values.
Table 1. Air bubble morphological characteristics in the ice samples M 1 and M 2
Observations through crossed polarizers revealed the grains that make up both samples, allowing the analysis of their morphology and size. The sample thickness determines the dominant birefringence hue, and the colouration of each grain reveals variations in the directions of the c-axes. Although birefringence hues in M1 and M2 are different (Figs 3e, 4e), the colour distributions of the grains in both samples suggest a nearly isotropic ice fabric. Concerning grain size, we identified two main grain groups:
• Group 1 (G1) encompasses big grains, whose boundaries and birefringence colours are well-defined (Fig. 3e).
• Group 2 (G2) includes smaller grains without well-defined boundaries or birefringence colours due to grain edge interference, presenting an iridescent appearance (central and lower part of Fig. 4e)
Aspect differences between these two groups are directly related to grain size and samples' thicknesses. In G 1, the grains are larger than the sample thickness, so we observed a section of almost every single grain. In G 2, the grain size is smaller, so there is more than one grain within the total sample thickness. Owing to these dissimilarities, we used cross-polarization photographs for G 1 and microscopy photographs for G 2. On the one hand, G 1 grains are dominant in M 1, although the distribution of both groups is homogeneous throughout the sample. On the other hand, G 1 only prevails in the upper third of M 2 because G 2 is dominant in the central and lower part of the sample. The average grain size of G 1 is similar in both samples (0.104 mm2 in M 1 and 0.138 mm2 in M 2), while the shape is roughly polygonal with a roundness index (inverse of the aspect ratio) of 0.79 in M 1 and 0.87 in M 2. Group 2 (G 2) has an average size of 0.006 mm2 (two orders of magnitude smaller than G 1) and a roundness index of 0.67, the smallest value of the entire sample set. Grains belonging to G 1 inside the zone of the predominance of G 2 have similar size compared to the rest of the sample (0.132 mm2), but the roundness is smaller, with a value of (0.75; Table 2).
Table 2. Grain size and roundness in the ice samples M 1 and M 2
Regarding chemical analyses (Fig. 7), the first crystalline compound identified in the M2 micro-Raman analysis was Quartz [SiO2] due to its characteristic bands using different laser intensities: very weak (295 cm−1), weak (262 and 396 cm−1), medium (131, 209 and 358 cm−1) and very strong (467 cm−1; Huidobro and others, Reference Huidobro, Aramendia, Arana and Madariaga2021). Anatase [TiO2] was also occasionally detected thanks to its most characteristic Raman band at 144 (vs) cm−1 (Huidobro and others, Reference Huidobro, Aramendia, Arana and Madariaga2021). Finally, atacamite [Cu2Cl (OH)3] was also recognized several times. Although this mineral has several Raman patterns, the principal Raman bands always appear at the same positions: 155 (vs), 266 (m), 289 (strong, s), 335 (w), 374 (w), 455 (m), 477 (m), 513 (s) and 808 (vw) cm−1 (Marcaida and others, Reference Marcaida2019; Li and others, Reference Li, Wang, Chen and Ma2020).
Figure 7. Micro-Raman analyses of the M 2 impurity layer. Quartz (SiO2 polymorph; blue line), atacamite ([Cu2Cl (OH)3]; red line) and anatase (TiO2; grey line).
Discussion
The origin of ice layering
Variations in grain size and shape, bubble number density (ρ bn) and impurity concentration may define an ice stratification (Allen and others, Reference Allen, Kamb, Meier and Sharp1960; Hambrey, Reference Hambrey1975, Reference Hambrey1977; Hambrey and Milnes, Reference Hambrey and Milnes1977; Hudleston, Reference Hudleston, Saxena, Bhattacharji, Annersten and Stephansson1977). The stratification defined by ρ bn can be primary (i.e. sedimentary) or secondary (also called foliation). The origin of primary stratification lies in the snow accumulation parallel to the glacier surface and its subsequent transformation into firn and ice (Lewis, Reference Lewis1960; Hambrey, Reference Hambrey1976, Reference Hambrey1994; Hambrey and Lawson, Reference Hambrey and Lawson2000). In general, this stratification generates isochronous layers and it is common in glacier accumulation zones, meaning above glaciers' equilibrium-line altitude (ELA). The different characteristics of the layers can reflect the environmental (atmospheric) conditions that prevailed at the time of the snow deposition (e.g. seasonal variations), as well as the post-depositional processes that could have affected the snowpack or glacier ice (e.g. Schytt, Reference Schytt1955; Shumskii, Reference Shumskii1964; Wadham and Nuttall, Reference Wadham and Nuttall2002). In this vein, in glaciers that used to suffer partial melting and refreezing (e.g. temperate glaciers like Monte Perdido Glacier), layers with high ρ bn values may represent the winter season. Conversely, layers with a transparent appearance (low ρ bn values) could indicate of the summer season, and are usually located at the base of the snowpack or at different firn depths, where they acquire a lenticular morphology (Hambrey, Reference Hambrey1994; Hambrey and Lawson, Reference Hambrey and Lawson2000). Besides, porosity and other void-space characteristics may be useful indicators of the transition zone between firn and bubbly ice. The transition of this depth differs between temperate glaciers, where there is a significant influence of melting and refreezing processes creating a complex stratigraphy (Kawashima and Yamada, Reference Kawashima and Yamada1997), and glaciers in polar areas, where the transition occurs in a more ordered and gradual fashion, mostly in a dry state (Alley and others, Reference Alley, Bolzan and Whillans1982).
Secondary stratification is directly related to the ductile deformation of ice and is responsible for variations in the distributions of size, shape and position of grains and bubbles. The higher the deformation, the more intense and marked the foliation (Barnes and Tabor, Reference Barnes and Tabor1966; Hambrey and Milnes, Reference Hambrey and Milnes1977; Hooke and Hudleston, Reference Hooke and Hudleston1978; Brepson, Reference Brepson1979; Hambrey and others, Reference Hambrey, Milnes and Siegenthaler1980). Foliation forms perpendicular to the maximum compressive stress (Glen, Reference Glen1956; Meier, Reference Meier1960; Hooke and Hudleston, Reference Hooke and Hudleston1978; Pfeffer, Reference Pfeffer1992), which in case of well-developed simple shear leads to foliation arranged parallel to the shear plane (Chamberlin and Salisbury, Reference Chamberlin and Salisbury1909; Perutz and Seligman, Reference Perutz and Seligman1939; Ragan, Reference Ragan1969). Thus, this particular type of air-bubble layering may reflect decadal-scale deformation processes in temperate glaciers or even millennial-scale in polar ice sheets (e.g. Paterson, Reference Paterson1994).
Based on this information and the results of our analyses, in the following sections, we will try to find out the possible origin of the layering that characterizes the MP1–6 section, defined by ρ bn and impurities.
Primary origin
For the first argument, it is necessary to consider the annual mean altitude of the 0°C isotherm (2945 m a.s.l.; López-Moreno and others, Reference López-Moreno2019) and the glacier's ELA (3050 m a.s.l.; López-Moreno and others, Reference López-Moreno2016). The MP1 ice core was extracted at ~2900 m a.s.l., meaning in the upper limit of the ablation zone (Figs 1b, c). However, it is not a well-defined boundary and exhibits natural spatial variability. Therefore, the characteristic processes of the accumulation zone may influence the drilling site. If we consider this possibility valid, the levels with lower and higher ρ nb values likely represent the summer and winter seasons, respectively.
Second, in our samples, there is no preferential elongation of the crystals (Figs 3, 4) nor the bubbles (Fig. 6), which could exclude the presence of deformation processes. Instead, the samples show ice crystals with a predominantly polygonal shape, while the bubbles display circular or irregular morphologies. For example, researchers observed crystal elongations in glaciers like Storglaciären (Sweden; Hudleston, Reference Hudleston2015), and in the case of air bubbles, samples of glaciers located in cold regions exhibit typical deformation morphologies (Gow, Reference Gow1968; Hudleston, Reference Hudleston, Saxena, Bhattacharji, Annersten and Stephansson1977; Alley and Fitzpatrick, Reference Alley and Fitzpatrick1999).
The third piece of evidence derives from the micro-Raman results (Fig. 7). The chemical composition of the three main minerals (i.e. atacamite, anatase and quartz) is consistent with previous chemical studies. Moreno and others (Reference Moreno2021) reported that the Al-normalized enrichment factors of Ti, Mn, Cr, Co, Ni, Cu and Pb are higher compared to the concentrations measured at the Ordesa monitoring station (8 km from the glacier and 1190 m a.s.l.), with Cu and Pb presenting a higher enrichment factor (>6). Moreover, the characteristically high values of Cu/Mn, As/Se and Pb/Zn ratios indicate a significant impact of Cu mining and smelting activities (Corella and others, Reference Corella2018). In Bielsa Valley, these activities were active during pre-industrial periods (Callén, Reference Callén1996), like the former Parzán mines, one of the main lead and silver deposits of the Central Pyrenees, located 7 km westward from the glacier. However, as this is a preliminary study, more robust analysis and results are needed to clarify questions such as the origin of the atacamite, i.e. it can be primary or a product of oxidation processes of other copper minerals.
Moreno and others (Reference Moreno2021) found that detrital-rich laterally extended layers define a primary stratigraphy, identifiable in some areas of the glacier's lower section surface. The particle size ranges from silt (0.002–0.05 mm) to sand (0.05–2 mm), and these particles may have been transported to the glacier surface by wind (e.g. black carbon or dust) or are the result of erosion processes of local outcrops (e.g. frost weathering). Levels with high impurity concentration can reveal episodes of reduced ice accumulation or periods dominated by ablation, as the particles concentrate in specific layers due to the ice melt, promoting the formation of darker-coloured layers.
The most detected mineral in the analyses was quartz (a SiO2 polymorph). Its origin may be weathering processes over local lithologies like the sandstones of the Marboré formation (Robador and others, Reference Robador Moreno, Rodríguez Fernández, Carcavilla Urquí, Samsó Escolà and Martínez Rius2020) or the deposition of mineral dust on the glacier surface. However, there are no sandstone outcrops nearby, increasing the likelihood of mineral dust. Dust particles are usually below tens of micrometres and incorporated into the atmosphere as an aerosol from arid or semi-arid regions, travelling long distances until deposited back to the surface. The composition consists mainly of a mixture of quartz, carbonates, iron oxides, clay minerals, sulphates and feldspars (Engelbrecht and others, Reference Engelbrecht2016), whose relative abundances vary depending on the source area (Caquineau and others, Reference Caquineau2002; Scheuvens and others, Reference Scheuvens, Schütz, Kandler, Ebert and Weinbruch2013; Formenti and others, Reference Formenti2014), accounting for 40% of annual aerosol emissions (IPCC, 2013). The North African region (Sahara and Sahel) is the main dust contributor worldwide (Prospero and others, Reference Prospero, Ginoux, Torres, Nicholson and Gill2002). Pyrenees act as a natural barrier for air masses coming from North Africa, making dust deposition higher in this region than in areas located hundreds of kilometres south (Pey and others, Reference Pey2020). African dust-loaded air masses reach this mountain range 10% of the annual days (Pey and others, Reference Pey, Querol, Alastuey, Forastiere and Stafoggia2013), and the aerosol deposition is greater in cold seasons (from November to April), periods in which there is a predominance of extreme dust events coming from the north African desert (Fig. 1c). Pey and others (Reference Pey2020) estimated that concentrations of mineral dust in the Pyrenees vary between 4.5 and 10.6 g m−2. On the one hand, during these events, particle composition has a mineral signature characterized by clay minerals and quartz, followed by feldspars, carbonates and hematite. On the other hand, in the absence of this phenomenon, the particles have a marked organic nature (Pey and others, Reference Pey2020).
Considering the need for more chemical analyses, the impurities' horizontal arrangement in a layer-like disposition, the reddish colouration (possibly due to the presence of clay minerals) and the high quartz content, we could hypothesize that this layer is made up of mineral dust particles. Besides, if we combine the fact that mineral dust deposition events are more common in winter and that this impurity layer in S 2 is inside a zone with high ρ bn values (indicative of winter, if we consider a primary origin), we could say (with caution) that this layer is indicative of a winter season with a high frequency of mineral dust deposition events (Fig. 2b). Additionally, we cannot exclude the possibility that this layer resulted from a succession of particle reconcentration events during a period characterized by high ablation rates or low snow accumulation.
Finally, cross-polarizer photographs support the last argument for the primary origin. At this point, it is important to emphasize that these interpretations are based on the assumption that variations in the birefringence colours are qualitative approximations of changes in the crystallographic c-axes arrangement. Both samples have an average thickness between 200 and 400 μm, and their birefringence hues are different and homogeneously distributed along each sample, without clusters of any particular colour, hinting that there are no significant changes in the fabrics related to the layering defined by the bubbles or by the impurities (Figs 3e, 4e). If we were dealing with a secondary origin, we would expect changes in the c-axis arrangement in regions where, as a result of shear stresses, basal slip planes tend to be parallel to the shear plane. Moreover, it has been often observed that inside impurity layers, there is a greater tendency for c-axes to approach a single maximum (Paterson, Reference Paterson1991), creating more favourable conditions for ice deformation and flow.
Bearing in mind these facts, we may be facing two possible scenarios: first, nowadays, there are no active deformation processes in the Monte Perdido Glacier, although such processes could have been active in the past. Second, deformation processes could be currently active, but are not strong enough to produce significant changes in the ice fabrics, at least on the level of the qualitative analysis we are working with. In both cases, since it is a temperate glacier, it is exposed to relatively high temperatures that cause recrystallization processes that may obliterate the original fabric deformation signs. For example, recrystallization can entail changes from a single maximum parallel to the foliation plane pole to an arrangement of three or four maxima, with none of them parallel to the foliation plane normal (Rigsby, Reference Rigsby1960). Bader (Reference Bader1951) and Rigsby (Reference Rigsby1951) established the existence of these peculiar fabrics, and subsequent work by Schwarzacher and Untersteiner (Reference Schwarzacher and Untersteiner1953), Rigsby (Reference Rigsby1953) and Meier and others (Reference Meier, Rigsby and Sharp1954) provided new data supporting this investigation, as well as more uncertainty levels.
Secondary origin
Combining the microscopy results, together with the high-resolution photos of the samples, we can observe how in M 1 the domains with low values of ρ bn as D 2, or to a lesser extent D 5, there is a remarkable concentration of sGB (Figs 5, 8a), which could be indicative of heterogeneous deformation (thus, internal stress concentrations) at the microscopic scale (Weertman and Weertman, Reference Weertman and Weertman1992; Figs 9a, b). Recent findings have quantified the ice velocity, concluding that the glacier has an average surface velocity of ~10 m a−1 (López-Moreno and others, Reference López-Moreno2019). Therefore, the sGB could indicate the stress and deformation produced by the ice flow. However, other parts with a low ρ bn values, such as D 3 or D 8, do not present a preferential sGB concentration. There is even an opposite correspondence in the clusters with high ρ bn identified between D 7 and D 8, where the sGB concentration is high (Figs 5, 8b). In the remaining zones, sGB are homogeneously distributed regardless of the number of air bubbles. Besides, there is a lack of direct correspondence between grain size and sGB, since the latter are present in both small grains of G 2 and larger grains of G 1.
Figure 8. Detailed positions of the microstructure outlines in M 1 (a) and M 2 (b) depicted in Figure 5.
Figure 9. Micrographs of M 1 and M 2. (a) The image shows an ice grain delimited by its boundaries (GB; 1), which appear as black or dark grey lines. Inside, several sub-grain boundaries (sGB; e.g. 2 and 3) with a lighter appearance, reveal heterogeneous stresses within the grain. With time, sGB will evolve into GB, therefore multiple grains (A, B, C, D) will differentiate from the original grain (rotation recrystallization; RXX). Additionally, nucleation of a small grain at a GB triple junction (SIBM-N; 4) and dislocation walls (5) which will eventually merge and form an sGB, can be observed. (b) Throughout the grain surface, encompassing most of the micrograph, slip bands (SB; faint and parallel lines) also indicate shear stresses acting on the grain. Besides, examples of different types of sGB: n (6), p (7) and z (8) can be identified. (c) Points 9 and 5, the latter from Figure 9a, exemplify the pinning effect of micro-bubbles (9) or particles (5). Two irregular and opaque particles composing the impurity layer (10 and 11) are also visible. (d) Grain boundaries with sinusoidal shape (12 and 13) and bubbles (14) at the M 2 impurity level.
The second argument relates the effects of the identified flow in the glacier and the occurrence of particles in the ice. When intense stresses act upon an ice grain, the strain energy tends to accumulate along the grain boundaries (GB), stimulating the formation of new grains along those regions (Humphreys and Hatherly, Reference Humphreys and Hatherly2004). Additionally, this strain energy can concentrate around particles in the ice matrix, as they can hinder GB sliding, enhancing dynamic recrystallization and, ultimately, the nucleation of new grains (Song and others, Reference Song, Baker and Cole2005). This last mechanism is known as particle-stimulated nucleation (PSN), sooner identified in studies conducted on metals and alloys (Habiby and Humphreys, Reference Habiby and Humphreys1994; Huang and Humphreys, Reference Huang and Humphreys2000; Somerday and Humphreys, Reference Somerday and Humphreys2003).
In our samples, we can find examples that illustrate both situations. On the one hand, we could identify small grains arranged along GB (Fig. 3c) in certain areas. On the other hand, in addition to the well-defined impurity layer in M 2, there are other regions throughout both samples where particles are present but at low concentrations, rendering them invisible to the naked eye and only detectable under the microscope. The zones where these particles form clusters correspond to round-like accumulations of tiny grains, whose occurrence could be a consequence of the PSN process (Fig. 3d). Both observations support the assumption that GMP ice may be subjected to sufficiently high stresses to trigger such deformation-induced phenomena.
By considering only the evidence that supports a secondary origin of stratification, implying the presence of glacier flow and combining it with the effects of impurities on this process, we encounter a scenario that facilitates an increase in ice-flow rates and deformation. If further comprehensive studies confirm the lateral extension of impurity layers along the glacier (i.e. affecting significant portions of the glacier), it could lead to a higher mass transfer rate from the upper regions of the glacier to the lower ones, specifically from accumulation zones to ablation zone. The visible and laterally extended impurity layers on the glacier's surface, reported by Moreno and others (Reference Moreno2021), provide us with a clue about what we may discover at greater depths through the study of more ice cores.
Grain growth impurities interplay
In M 1, the particle concentration is low, and they are only perceptible under the microscope, unlike M 2, which has a noticeable level of impurities both in visual stratigraphy (Fig. 2b) and microscopy (Fig. 9c). In visual stratigraphy, this level has a characteristic brownish-red colour, while under the microscope, impurities appear as small opaque particles with irregular shapes and an average size of ≤0.05 mm. In addition to the impact these particles have on grain formation (previous section) they can interact with GB during migration (Beck and Sperry, Reference Beck and Sperry1950). The interaction mechanisms that can slowdown or even stop GB migration are known as dragging and pinning, respectively. In the lower section sample (M 2), we can observe what might be examples of these two mechanisms. In the middle and lower thirds of M 2, corresponding to the impurity layer, there is a drastic reduction in grain size and roundness index. Grain size decreases by two orders of magnitude, from average values of 0.12 mm2 in M 1 and in the impurity-free zone of M 2, to 0.006 mm2 within the impurity layer. The roundness index also experiences a decrease, from 0.83 outside the impurity layer to 0.67 within the layer (Figs 4c, d and 5).
In the M 2 impurity layer, there was no preferential concentration of particles along GB. Consequently, we did not observe any pinning effect. However, some GB show pinning processes produced by micro-bubbles (Figs 9c, 10). Despite the absence of particle-induced pinning, the correspondence between the impurity layer and grain size and roundness reduction is clear. Soluble impurities, which could affect GB motion through the drag effect, could explain this correspondence. Likely, evidence of this process is that even in the absence of particles (non-soluble impurities) at GB, a considerable portion exhibits a sinusoidal shape (Fig. 9d), indicating a potential reduction in migration velocity in some points.
Figure 10. Regions where dynamic recrystallization dominates. Evidence of this process is the bulged grain boundaries, indicating the presence of SIBM-O (1, 3 and 4) or the nucleation of new grains SIBM-N (5 and 6). Additionally, point 2 is a clear example of the pinning process, in this case, caused by a micro-bubble.
At this point, it is essential to consider the resolution of the microstructural study, as we are only analysing three bands to observe the overall evolution of grain characteristics. To corroborate our observations and gain a better insight into the contribution of dragging and pinning effects, a more comprehensive analysis expanding the coverage (area) of microscopy would be necessary. This circumstance is similar in the upper 2300 m of EDML deep ice core (Antarctica), where it was also challenging to find a clear interaction between microstructure and particles (Faria and others, Reference Faria, Freitag and Kipfstuhl2010).
Conclusions
This study is the first attempt to characterize the microstructure of the ice from the Monte Perdido Glacier, located in the Central Pyrenees, one of the southernmost glaciers in Europe. Analysing a specific segment (MP1–6), we studied the interactions between impurities and microstructure. One of the most noteworthy features of this segment is the stratification, defined by air bubbles and particles (non-soluble impurities). According to our results, this bubble-defined stratification presents evidence of both a primary (sedimentary) and a secondary origin (deformation-induced). Several factors support the primary origin: MP1 ice core belongs to the lower limit of the accumulation zone, there is no preferential elongation of bubbles or ice grains, the non-variation of birefringence colours along the samples indicates that there is no action of shear stresses, and finally, there is a correspondence between the layer with the maximum concentration of impurities (possibly resulting from Saharan dust deposition, more frequent in winter) and a zone with a high concentration of air bubbles (likely representative of the winter season). On the other hand, proofs supporting a secondary origin derived from some layers show a preferential concentration of sGB (microstructural elements indicative of heterogeneous deformation). Besides, the presence of clusters of tiny grains could be the consequence of the combination of deformation processes and the presence of particles. Both pieces of evidence indicate that the glacier ice is (or has been subjected) to higher stresses, possibly related to glacier flow. If we focus on the evidence supporting a secondary origin (linked to glacier flow processes) and combining it with the effects of the impurities on the natural ice mechanics (increase in flow/deformation), Monte Perdido Glacier could face a scenario of enhanced mass transfer from the accumulation zone to the ablation zone in the long term. This process would involve accelerated mass loss, particularly if the impurity layers extend horizontally.
Regarding the effect of impurities on microstructure, a clear inverse relationship is observed between their concentration and grain size/roundness. The combination of drag and pinning mechanisms, generated by the interaction between insoluble impurities (particles), soluble impurities and micro-bubbles with the GB migration process, could explain this correspondence. The dragging seems to be the prevailing process (as observed in the microscopy bands), whereas only a few GB exhibit pinning by micro-bubbles.
For a preliminary characterization of the particles, we employed a micro-Raman spectrometer. Using this technique, we identified atacamite and anatase, whose presence is consistent with past mining activities in the vicinity and previous chemical studies on the Monte Perdido Glacier. However, quartz was the predominant mineral, and its presence could be related to the arrival of dust-laden air masses from North Africa. If further analysis confirms with greater certainty that this impurity layer is made of mineral dust, it is essential to be aware that since the second half of the 20th century, there has been an increase in Saharan dust transport to Western Europe (Sousa and others, Reference Sousa2019; Cruz and others, Reference Cruz, McDermott, Turrero, Edwards and Martín-Chivelet2021), as a consequence of an average 10% increase in the extension of this desert between 1920 and 2013 (Thomas and Nigam, Reference Thomas and Nigam2018). A greater input of mineral dust into the Pyrenees cryosphere would imply an increased likelihood of preserving some of these particles in the accumulation areas through their incorporation into the glacier ice structure (as likely happened in our study), increasing their influence on ice mechanics. Besides, mineral dust in the Pyrenees cryosphere reduces the albedo of the seasonal snow cover, accelerating its melting. Recent findings have shown that the albedo decreases during years with deposition events, ranging from 0.4 to 0.6 (e.g. 2016–2017), whereas in years without events, the albedo ranges from 0.7 to 0.9 (e.g. 2018–2019; Pey and others, Reference Pey2020).
In addition to the role of impurities, other factors are reinforcing glacier degradation, such as the annual increase in regional temperatures (e.g. López Moreno and others, Reference López-Moreno, Vicente-Serrano, Angulo-Martínez, Beguería and Kenawy2010; El Kenawy and others, Reference El Kenawy, López-Moreno and Vicente-Serrano2012; Pérez-Zanón and others, Reference Pérez-Zanón, Sigró and Ashcroft2017), the widespread predominance of ablation processes over accumulation events (López Moreno and others, Reference López-Moreno2019), and the decrease in thickness and surface area of the seasonal snow cover during the second half of the 20th century, especially at lower elevations (López-Moreno and others, Reference López-Moreno2005, Reference López-Moreno, Goyette and Beniston2009).
Acknowledgements
This research was supported by the Spanish Government through the María de Maeztu excellence accreditation 2018–2022 (MDM-2017-0714) and by the Spanish Agencia Estatal de Investigación (AEI Spain) through the projects PaleoICE EXPLORA (CGL2015-72167-EXP) and iMechPro (RTI2018-100696-B-I00). NGS acknowledges a PhD grant from the Basque Government (PRE-2018-1-0116). We thank the directorate of the Parque Nacional de Ordesa y Monte Perdido (Spain) for permission to investigate the Monte Perdido glacier. We also thank Ibai Rico (https://basquemountainguides.com/, UPV/EHU), Maria Leunda (UPV/EHU), and Juan Ignacio López-Moreno (IPE-CSIC) for their help during the sampling of the MP1 ice core, and Pedro Sanchez Navarrete (IPE-CSIC) for transporting the ice samples. Finally, we would like to extend our appreciation to the anonymous reviewers, the Scientific Editor, Christine Hvidberg, and the Chief Editor, Hester Jiskoot, for their valuable comments on this manuscript.
Open access
