# Lateglacial and Holocene mountain glacier fluctuations near Cape Farewell South Greenland inferred from 10 Be moraine dating

Vincent Jomelli, Joanna Charton, José Fernández-Fernández, Régis Braucher, Didier Swingedouw, Amen Al Yaari, Marc Oliva, Stephanie Gairoard, Julia García-Oteyza

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Vincent Jomelli, Joanna Charton, José Fernández-Fernández, Régis Braucher, Didier Swingedouw, et al.. Lateglacial and Holocene mountain glacier fluctuations near Cape Farewell South Greenland inferred from 10 Be moraine dating. Journal of Quaternary Science, 2025, 10.1002/jqs.70015. hal-05338532

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# Lateglacial and Holocene mountain glacier fluctuations near Cape Farewell South Greenland inferred from ¹⁰Be moraine dating

VINCENT JOMELLI,<fnref n="1" />* JOANNA CHARTON,<fnref n="1" /> JOSÉ M. FERNÁNDEZ-FERNÁNDEZ,<fnref n="2" /> RÉGIS BRAUCHER,<fnref n="1" />

DIDIER SWINGEDOUW,<fnref n="3" /> AMEN AL YAARI,<fnref n="3" /> MARC OLIVA,<fnref n="4" /> STEPHANIE GAIROARD,<fnref n="1" /> JULIA GARCÍA-OTEYZA<fnref n="4" /> and
ASTER TEAM

Received 27 November 2024; Revised 25 August 2025; Accepted 26 August 2025

**ABSTRACT:** We report 43 new ¹⁰Be exposure ages and six ²⁶Al/¹⁰Be measurements from replicates from a small piedmont mountain glacier located at Cape Farewell (south Greenland) and temperature anomalies estimated from equilibrium-line altitude (ELA) changes derived from 3D glacier reconstruction carried out using the 'GlaRe' toolbox. Both ELA-derived temperature estimations and climate conditions documented from the transient simulation TraCE-21ka help us to explore the causes of glacier changes during the investigated period. Exposure ages span from the Oldest Dryas to the Late Holocene, revealing that the GrIS retreat in this valley permitted the individualisation or formation of a mountain glacier early in the Lateglacial. Interestingly, four of the six ²⁶Al/¹⁰Be ratios come from samples located on the oldest moraines do not reveal inheritance. The two other ratios suggest inheritance up to 6 ka. The oldest moraine combining a frontal and a lateral remain is dated to 18.4 ± 0.8 ka. Between 18 ka and ~14.7 ka, the glacier experienced a significant retreat interrupted by at least three minor advances or stillstands. We did not find any moraine formed either during the Younger Dryas, or during the Early and the Mid Holocene. The largest Holocene glacier advance occurred ~4.4 ka. Two other younger moraines were formed at ~2.9 ka and probably during the LIA. Temperatures of 3.3°C and 1.7°C colder than today may explain the glacier extent during the Lateglacial and the Holocene, respectively. Complementary dry regional climate conditions estimated from TraCE-21ka simulations during the Early Holocene may explain why the glacier was smaller than during the Late Holocene. © 2025 The Author(s). *Journal of Quaternary Science* Published by John Wiley & Sons Ltd.

**KEYWORDS:** Holocene; Lateglacial; moraine chronology; mountain glacier; south Greenland

## Introduction

Our understanding of the evolution of the ~18 500 mountain glaciers situated along the periphery of the Greenland Ice Sheet (GrIS) (Rastner et al., 2012) (referred as local glaciers by Kelly and Lowell (2009)) during the Lateglacial period (19–11.7 ka (thousands of years)) is only loosely constrained. The few existing studies about these mountain glaciers have mostly focused on the Holocene, that is, the last ~11.7 ka (for instance, Levy et al., 2014, 2016; Jomelli et al., 2016; O’Hara et al., 2017; Biette et al., 2020, 2022), leaving earlier phases of their fluctuations largely unexplored. Glacier changes were either constrained by radiocarbon and/or cosmic-ray exposure (CRE) dating applied to moraines or indirectly documented using lake sediment proxies (Andresen et al., 2004; Balascio et al., 2015; Larocca et al., 2020a, 2020b). Moreover, while the spatial distribution of the investigated lake records is roughly uniform at the scale of the island, most direct glacier chronologies from the CRE dating method come from glacial valleys located above 65° N, with only a few records in the southern part of Greenland (Biette et al., 2022). Additionally, palaeoclimate studies in

Greenland (Larsen et al., 2019) reveal a north-south gradient in the timing of Holocene thermal maximum (HTM) conditions, as well as a later onset of the Late Holocene (4.2 ka to present), also referred to as neoglacial cooling (Solomina et al., 2015; Palacios et al., 2024). Consequently, southern Greenland experienced a delayed warming/cooling relative to other regions of Greenland (Briner et al., 2016). This shift in climatic conditions may be responsible for a possible asynchrony in the evolution of mountain glaciers during at least the last 4 ka.

In southern Greenland, changes in mountain glacier remain poorly understood largely due to the limited and sometimes contrasting results from data derived from lake sediments or CRE dating. Insights into the timing of glacier formation or separation are often inferred indirectly from the retreat chronology of the GrIS. Throughout this sector, a variety of geomorphological indicators such as erosional and depositional (e.g., erratic boulders) features on islands suggest that during the last glacial maximum (LGM; 26.5–19 ka, Clark et al., 2009), ice covered nearly all currently ice-free terrain and extended onto the continental shelf. The Qassimiut lobe, located ~160 km northwest of the CHA glacier, was coalescent with the Julianehab Ice Cap, which occupied the alpine mountain chain in southern Greenland during the LGM (Fig. 1). It is widely inferred that the individualisation/formation of the

<footnote n="1">¹CNRS, IRD, Coll. France, INRAE, CEREGE, Aix-Marseille University, Aix-en-Provence, France</footnote>

<footnote n="2">²Department of Geography, Facultad de Geografia e Historia, Universidad Complutense de Madrid, Madrid, Spain</footnote>

<footnote n="3">³Environnements et Paleoenvironnements Oceaniques et Continentaux (EPOC), UMR CNRS 5805, EPOC-OASU Université de Bordeaux, Pessac, France</footnote>

<footnote n="4">⁴Department of Geography, Universitat de Barcelona, Barcelona, Catalonia, Spain</footnote>

<footnote>*Correspondence: Vincent Jomelli, as above. E-mail: jomelli@cerege.fr</footnote>

<footnote>ASTER TEAM: G. Aumaître, K. Keddadouche, F. Zaidi.</footnote>
mountain glaciers occurred relatively late and quickly perhaps from ~14 to 12 ka (Bennike et al., 2002; Weidick et al., 2004) based on ¹⁴C minimum ages obtained from sediments at the base of over 20 lakes cores around Nanortalik (Bennike and Bjorck 2002; Bennike et al., 2002). The oldest of these ages is provided by sample Ua-14844 from the base of Lake 14 dated to 13 500 ± 258 cal BP (Leger et al., 2024).

This hypothesis is further supported by ¹⁰Be CRE ages, ranging from 15.5 to 11 ka obtained from erratic boulders and roche moutonnées near the present-day coastline (Winsor et al., 2015a, 2015b; Andersen et al., 2020; Larocca

et al., 2020a) (Fig. 1). These data suggest that by ~15–14 ka, the southern part of GrIS had already retreated from the coastal areas, with the ice margin reaching its modern-day position by ~11.1–10.5 ka (Larsen et al., 2011, 2016b; Carlson et al., 2014; Leger et al., 2024). Consequently, the formation/individualisation with the GrIS of the mountain glaciers in this region is estimated to have begun at ~15–14 ka. However, no Lateglacial glacier chronologies based on moraine boulder dating have been published as yet for mountain glaciers in this sector. The evolution of mountain glaciers during the Holocene in this part of southern Greenland has been investigated by Larocca et al. (2020a),

<figure><img src="image_2.png" /></figure>

**Figure 1.** Location maps. The red frame shows the study area displayed in Fig. 2. Sites referred in the text are annotated, in particular, the CRE data sites (violet dots) and the lake multiproxy records (green diamond). (1) Jomelli et al. (2016), O’Hara et al. (2017), Schweinsberg et al. (2019); (2) Larocca et al. (2020b); (3) Balascio et al. (2015); (4) Biette et al. (2022); (5) Håkansson et al. (2007, 2011), Kelly et al. (2008), Lowell et al. (2013), Levy et al. (2014, 2016), Medford et al. (2021); (6) Biette et al. (2020), Garcia-Oteyza et al. (2022). The background map is from the Greenland QGIS data package (Fisher et al., 2023; Moon et al., 2023 and references therein; made with Natural Earth [On line: https://www.naturalearthdata.com/; Accessed on: 2021-12-23]). Greenland coastlines are from Gerrish (2020) and global coastlines are from Wessel and Smith (1996). Orange arrows symbolise warmer Atlantic-origin water, while blue arrows represent colder Arctic-origin water. IC, EGC and WGC stand for Irminger, east Greenland and west Greenland currents, respectively. [Color figure can be viewed at wileyonlinelibrary.com]
who analysed sediment records from three lakes that received glacial meltwater input during this period. Two periods of glacier advance of approximately equal amplitude were detected during the Early Holocene (11.7–8.2 ka) and the Late Holocene (<4.2 ka). Interestingly, these lakes continued receiving glacial meltwater input until ~7 ka, that is, during the Mid Holocene. The survival of these local glaciers implies that south Greenland remained relatively cool until this time. From ~7.1 to 5.5 ka, glaciers at these locations became very small or, more likely, melted away completely. During the Late Holocene, these lake records show sustained glacier regrowth at ~3 ka and before the Medieval warm anomaly (MWA) at ~1.3 ka. These lake sediment records also suggest that mountain glaciers reached their maximum Late Holocene extent during the Little Ice Age (LIA; ~0.6–0.1 ka; Solomina et al., 2015, 2016) Larocca et al. (2020a, 2020b).

Direct evidence of mountain glacier fluctuations from CRE dating also remains particularly limited in this region (Kjær et al., 2022). The single published chronology in this region covers only the Late Holocene (Biette et al., 2022). In this study, CRE moraine dating from a glacier located about 70 km north of Cape Farewell showed glacier advances synchronous with those reported from lake sediments (considering age uncertainties) at ~2.8, ~1.4 ka and during the LIA. However, the moraine record reveals that the LIA glacier extent does not correspond to the maximum Late Holocene glacier extent. Such a difference in glacier amplitude during the LIA remains unclear and may be due to the specific topographic and geomorphological context of each glacier, as rare examples cannot be used as representative of a more regional pattern.

To contribute to a better understanding of mountain glacier fluctuations from the Lateglacial to the Late Holocene, we investigated a glacial valley near Cape Farewell in southernmost Greenland. We report 43 new ¹⁰Be exposure ages and six ¹⁰Be ²⁶Al measurements from replicates. These ages come from samples collected on moraine boulders, a sand deposit between two moraine ridges and a sample from a vertical rockwall of the small mountain glacier CHA (informal name). We also report temperature conditions estimated from changes in Equilibrium-Line Altitude (ELA) derived from the GlaRe GIS toolbox (Pellitero et al., 2015, 2016) during the Lateglacial and Late Holocene periods combined with climate conditions estimated from the transient climate TraCE-21ka model simulations. As climate conditions estimated for such a small mountain glacier are less influenced by lag effects and complex ice dynamics compared to the GrIS, such an analysis provides an interesting and complementary picture of climate change in this region.

The physical and climatic settings of the investigated glacier are presented in Section 2. Based on the methodology described in Section 3, the results of CRE moraine ages, along with ELA and associated temperature changes, are presented in Section 4. In Sections 5.1 and 5.2, we discuss our moraine record and our temperature changes estimated from ELA variations. In Section 5.3, we compare our results with TraCE-21ka results and other studies conducted on mountain glaciers in Greenland.

# Geographic setting and climate

## Physical setting

The study area is located in the southernmost part of Greenland. It has an alpine topography with peaks above 2300 m a.s.l. This region contains roughly 1000 small

mountain glaciers (<smaller than 1 km²), mostly located on north-facing slopes. The mean minimum elevation of these glaciers is about 880 m a.s.l. and the mean maximum elevation is about 1300 m a.s.l. (Larocca et al., 2020b). The investigated CHA glacier is located in the Itillersuaq valley, about 40 km northeast of Nanortalik and 17 km east of Tasiusaq (60°15 N; 44°53 W; cf. Figs. 1–3). The bedrock in the Nanortalik region consists of Precambrian gneisses that were heavily ice-scoured during glaciations, and sparse unconsolidated Quaternary deposits. The CHA glacier is a debris-free, winter-accumulation glacier type, currently covering an area of ~0.87 km². It spans elevations from a maximum of 1740 m a.s.l. to a minimum of 200 m a.s.l. Presently, the glacier is divided into three separate ice masses and extends roughly 1.7 km in length towards the north, with an average slope of ~31°. Another adjacent glacier shows similar topographic characteristics and its tongue may have coalesced with that of the investigated glacier during some periods in the past. Several moraines are visible in the forefield of the CHA glacier, downhill from the current position of the ice front. In the past, the glacier reached a flatter and much larger valley. In fact, some of the oldest moraines reveal that the CHA glacier was of piedmont type at certain times. As the glacier retreated to steeper slopes in younger periods, the difference in altitude between the youngest (highest) and the oldest (lowest) moraine exceeds 100 m.

## Climate setting

Climate in southernmost Greenland is low-arctic oceanic, and winter weather is highly influenced by the Icelandic Low, with low-pressure systems crossing southern Greenland from the southwest to the northeast. This region is also strongly influenced by ocean surface currents. Near Cape Farewell, the cold and fresh East Greenland Current (EGC), which brings Arctic water and sea ice from the north, mixes with the warm and saline Irminger Current (Cappelen, 2020). At the Qaqortoq meteorological station, located on the outer west coast, about 80 km from the study site, the mean annual air temperature is 0.6°C (1990–2020). The mean summer (June–August) and winter (December–February) temperatures are 6.5°C and –5°C, respectively. The mean annual precipitation from 1981 to 2020 is 850 mm.

# Methods

## Field sampling

The field campaign took place in 2022. Eight well-preserved moraines (>1 m high and >20 m long) were identified up to 1–1.5 km from the current front and named looking uphill, that is, M1 for the oldest to M1 for the youngest (Table 1; Fig. 3). Using a hammer and a chisel, 41 samples were collected in the field to constrain the evolution of the CHA glacier. The granitic boulders (>1 m high) were sampled from the crest of the identified moraines and another sand sample was collected on a flat surface in between two moraine ridges, probably related to the erosion of moraine ridges. Each boulder was photographed (Fig. 3). The last sample was collected from a subvertical rockwall just above the current ice front on the right side of the glacier at an altitude of 300 m a.s.l. (Fig. 3). A Suunto compass clinometer PM-5 was used to *in situ* measure topographic shielding for each sample in the field. Sample elevation was obtained from the handheld Garmin GPS instrument (Table 1). We considered and selected boulders and locations on the moraine with no evidence of disturbance
<figure><img src="image_3.png" /><figcaption>**Figure 2.** Regional setting of the CHA glacier. (1) Winsor et al. (2014); (2) Biette et al. (2022) (3–4, 6) Larocca et al. (2020a); (5) Andresen et al. (2004); Erratic boulder and bedrock samples come from Winsor et al. (2015a, 2015b); Andersen et al. (2020); Larocca et al. (2020a) and Levy et al. (2020). Radiocarbon ages were provided by Bennike and Bjorck (2002), Bennike et al. (2002); Weidick et al. (2004); and Sparrenbom et al. (2013). [Color figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

caused by the action of other slope processes (snow avalanche, rockfall or debris flow; Jomelli and Francou, 2000).

## Laboratory procedures and exposure-age calculation

All samples were processed at LN2C (Laboratoire National des Nucléides Cosmogéniques) (CEREGE; Aix-en-Provence, France) in two distinct rounds carried out in 2023 and 2025, respectively. In 2023, 42 samples were crushed and sieved to collect the 250–1000 µm fraction. Quartz was first concentrated by magnetic separation and then isolated by successive leaching in a 2/3 hexafluorosilicic (H₂SiF₆) and 1/3 hydrochloric (HCl) acid mixture. The quartz fraction obtained was leached at least three times in a 10% hydrofluoric acid (HF) solution, in order to remove any remaining feldspars and to clean the grains from atmospheric ¹⁰Be. Purified quartz (ranging from 7 to 25 g) was completely dissolved in concentrated (48%) HF acid after the addition of ~450 mg of a ⁹Be carrier VHG solution (Tables S1 and S2). Beryllium was extracted by successive alkaline precipitations of beryllium hydroxide (Be(OH)₂) alternated with separations on anionic and cationic resins. Samples were then oxidised at 700°C for 1 h, and the final BeO was mixed with niobium powder and finally loaded into copper cathodes. In 2025, eight replicates G3r, G4r, G29r, G41r, G42r, G43r, G48r and G52r and an additional sample 25G1 were included in the data set. These samples were leached with HF acid at least three times. Aliquots with 0.1 g of purified quartz were dissolved in concentrated HF and tested for purity with regard to major elements (Al, Ca, Fe, K, Mg, Na and Ti) using a CP-OES method. Quartz samples with high Al concentration

(>150 ppm) were re-leached with additional acid volumes and were then tested again until the concentration in Al and other elements remained <150 ppm for subsequent AMS measurements. These samples were then processed using a slightly modified protocol. After anion column chromatography, we evaporated the HCl and newly converted samples to sulphate form. We then used the above-mentioned protocol and performed cation column chromatography to remove B and Ti, and separate Be from Al. ²⁶Al was also extracted for six of the samples (except for G3r and G4r) to detect possible complex exposure histories.

AMS measurements of the ¹⁰Be/⁹Be and ²⁶Al/²⁷Al ratios were performed at the French national AMS facility ASTER (Arnold et al., 2010) (Tables 1 and 2). Measurements were calibrated against the in-house standard STD-11 (¹⁰Be/⁹Be = 1.191 ± 0.013 × 10⁻¹¹; Braucher et al., 2015) and a ¹⁰Be half-life of 1.387 ± 0.0012 10⁶ yr (Chmeleff et al., 2010; Korschinek et al., 2010). Aluminium measurements were performed against an in-house standard SM-Al-11 with ²⁶Al/²⁷Al = (7.401 ± 0.064 × 10⁻¹²), which has been cross-calibrated against the primary standards certified by a round-robin exercise (Merchel and Bremser, 2004). Analytical uncertainties combine ASTER counting statistics, standard uncertainty, external uncertainty (0.5% for ¹⁰Be; Arnold et al., 2010) and machine blank correction. ¹⁰Be and ²⁶Al concentrations in the sample were calculated from their corresponding ¹⁰Be/⁹Be and ²⁶Al/²⁷Al ratios and were corrected from associated chemical blanks. ²⁶Al/²⁷Al ratios were calibrated against the ASTER in-house standard SM-Al-11, cross-calibrated with KNSTD10650 (Merchel and Bremser, 2004; Arnold et al., 2010). This procedure implies an effective ²⁶Al/¹⁰Be production ratio of 6.61 ± 0.50, consistent with the update of Nishiizumi et al.
<figure><img src="image_4.png" /><figcaption>**Figure 3.** (a) View of the rockwall located on the right side of the glacier where Gre54 was collected (Fig. 4). (b) Boulder Gr20 on moraine M8. (c) View from M3R towards M4R with a man on the ridge. (d) Sampling M4R. (e, f) Views from the flat surface towards M6R. (g) View of the sandy deposit between M5 and M6L. (h) Boulder on moraine M3R. [Color figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

(1989). This value is applied for normalisation at ASTER. For burial modelling, we use the constant spallation production ratio of ~7.0–7.1, which lies within the 1σ range of the AMS normalisation and does not affect our interpretations. Scaling to the sample locations was made according to the recent, physically based, LSD model (Lifton et al., 2014), which performs similarly to older empirical models (Borchers et al., 2016). Selected parameters include the ERA-40 atmospheric reanalysis (Uppala et al., 2005), the VDM 2016 geomagnetic database. Exposure ages were calculated using the Arctic/Baffin Bay ¹⁰Be production rate calibration dataset (Young et al., 2013; Young et al., 2020a, 2020b), as archived on ICE-D (https://www.ice-d.org/production%20rate%20calibration%20data/cal_data_set/1). This data set corresponds to a production rate of ~4.03–4.05 atoms g⁻¹ yr⁻¹ depending on the calculator version (e.g., CRONUS v3, CREp).

Exposure ages were computed using the online CREp programme (Martin et al., 2017; http://crep.crpg.cnrs-nancy.fr) and are presented in Table 1. ¹⁰Be CRE ages are reported with 1σ ‘external’ uncertainties, which include measurement, production rate and scaling uncertainties (e.g., Balco et al., 2008), in the main text and on the figures (Figs. 4 and 6) for better comparison with other proxies. Both internal and external uncertainties are reported in Table 1. For a given moraine, its assigned age corresponds to the weighted mean of the sample ages that successfully passed a Chi² test (calculated with the internal uncertainties) used to identify potential outliers (Ward and Wilson, 1978), as it is more conservative than other tests such as Chauvenet's or Peirce's criteria (Jomelli et al., 2023). Based on field observations, we also considered the stratigraphic relationships to identify outliers. Finally, in cases where moraine age calculations
<figure><img src="image_5.png" /><figcaption>**Figure 4.** Chronology of the CHA glacier's evolution. Geomorphological features are mapped on aerial imagery of the investigated glacier. White boxes show the individual $^{10}$Be ages of moraine boulder samples, replicated and $^{26}$Al ages. The green box shows $^{10}$Be ages of a sand sample and the blue box shows $^{10}$Be age of a sample collected on a rockwall. All the ages are displayed with their inferred external uncertainties. Samples written in strike-through italic text are rejected as outliers and therefore excluded from the discussion. The weighted mean ages for moraine groups, solely based on $^{10}$Be ages, are shown in red/pink/purple-coloured boxes. [Color figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

involved a replicate sample, we used the weighted mean of the original $^{10}$Be age and its replicate.

The GrIS has experienced a considerable reduction in its ice volume since the time of the LGM. Consequently, the isostatic rise of the land since deglaciation amounts to about 110 m during the last 14 ka (Bennike et al., 2002; Long et al., 2008; Sparrenbom et al., 2013). These effects are estimated to cause older ages (up to 0.5 ka) when the correction is applied to the ages in the investigated region (Jones et al., 2019; Young et al., 2020a, 2020b), which is smaller than the uncertainties reported in this study.

## Palaeoglacier reconstruction

Glacier reconstruction was performed following the procedures proposed by Benn and Hulton (2010), based on the reconstruction of longitudinal equilibrium ice profiles supported by a physical-based model describing ice rheology and glacier flow (Van der Veen, 1999), aiming to achieve a robust glacier reconstruction. This kind of model operates on completely ice-free areas, which is not the case of the CHA cirque. It is occupied by three small ice masses detached from each other and accounts for 0.87 km² in total. To obtain the bedrock topography, the ArcGIS toolbox 'VOLTA' (Volume and Topography Automation; James and Carrivick, 2016) was run in the work interface of ESRI ArcMap (version 10.4). This toolbox allows to model the spatial distribution of ice masses by assuming perfect plasticity of ice. It only requires the glacier outlines and a digital elevation model (DEM). Glacier outlines were manually drawn through visual inspection of a false infrared colour Sentinel-2 L2A satellite image (spatial resolution: 10 m) collected on August 21, 2023, when the study area was mostly snow-free. Here, we use the ArcticDEM (Porter et al., 2022, 2023), derived from stereo autocorrelation applied to overlapping pairs of high-resolution (0.3–0.5 m)

optical satellite images (Maxar, WorldView 1-3 and GeoEye-1). To avoid the potential impact of some local artefacts, the DEM was smoothed through the 'Focal Statistics' command in ArcMap, considering a rectangular 10×10 cell neighbourhood (statistics type: mean). Then, 'VOLTA' routines were applied in two steps: (1) drawing the centrelines of the current ice masses, and (2) calculating ice thickness along the centrelines. The default tool parameters were considered (ice density = 900 kg m⁻³; effective slope limit = 30°; and minimum slope limit = 4°). For more details of the full calculation process, the reader is referred to James and Carrivick (2016). Then, ice thickness was interpolated from the centreline ice thickness points through the ANUDEM 5.3 interpolation routine ('Topo to Raster' command) in ArcGIS, and the resulting raster was subtracted from the current DEM to produce an ice-free DEM.

Over this 'deglaciated' DEM, glacier reconstruction was conducted using the 'GlaRe' toolbox devised by Pellitero et al. (2016). It implements the methods proposed by Benn and Hulton (2010) in the ArcMap (version 10.8) work interface. The application of this tool required the glacier constraints, a flowline network and an ice-free DEM. A tentative palaeoglacier geometry was manually drawn by considering geomorphic evidence (frontal and lateral moraines) at the lower sector and the water divide at the upper area, in the cirque scarp. On the other hand, flowlines were manually drawn from the terminus to the headwall following the central axis main thalwegs and tributaries. To circumvent the limitations of the model when reconstructing a piedmont lobe, two auxiliary flowlines were added, following the westward and eastward ice flow divergence inferred from geomorphic evidence. Then, ice thickness was calculated along flowlines from bed elevation and a shear stress range from 50 to 120 kPa, tuned to fit the former ice thickness revealed by the relative position of lateral moraines when possible; otherwise, a standard 100 kPa
<table><caption>**Table 1.** ¹⁰Be Cosmogenic data from the Cha glacier. The mean age of the landforms is calculated with external uncertainties. The prefix 25 (25G1 for instance) means that the sample was processed in 2025 with a new chemistry protocol (see method section), while the others were processed in 2023. The index *r* indicates a replicate such as G50r.</caption><thead><tr><th>Sample name</th><th>Latitude (°N)</th><th>Longitude (°W)</th><th>Elevation (m)</th><th>[¹⁰Be] (atoms g⁻¹)</th><th>[¹⁰Be] uncertainty (atoms g⁻¹)</th><th>Shielding factor</th><th>Thickness (cm)</th><th>Exposure ages (ka)</th><th>External uncertainty (ka)</th><th>Internal uncertainty (ka)</th><th>Chi² test</th></tr></thead><tbody><tr><td colspan="12"><strong>M1 moraine: 19.9 ± 1.3</strong></td></tr><tr><td>G48</td><td>60.16235</td><td>44.53610</td><td>142</td><td>92.927</td><td>10.807</td><td>0.956</td><td>2</td><td>18.84</td><td>2.29</td><td>2.18</td><td>Accepted</td></tr><tr><td>G48r</td><td>60.16235</td><td>44.53610</td><td>142</td><td>106.538</td><td>11.088</td><td>0.956</td><td>2</td><td>21.62</td><td>2.38</td><td>2.24</td><td>Accepted</td></tr><tr><td>AlG48r</td><td>60.16235</td><td>44.53610</td><td>142</td><td></td><td></td><td>0.956</td><td>2</td><td>21.7</td><td>2.9</td><td>1.7</td><td>Accepted</td></tr><tr><td>G50</td><td>60.16226</td><td>44.53373</td><td>136</td><td>94.005</td><td>11.564</td><td>0.956</td><td>2</td><td>19.17</td><td>2.45</td><td>2.35</td><td>Accepted</td></tr><tr><td colspan="12"><strong>M2 moraine: 17.7 ± 0.8</strong></td></tr><tr><td>G51</td><td>60.16071</td><td>44.51907</td><td>86</td><td>83.159</td><td>6565</td><td>0.970</td><td>2</td><td>17.53</td><td>1.52</td><td>1.38</td><td>Accepted</td></tr><tr><td>G52</td><td>60.15992</td><td>44.51843</td><td>86</td><td>90.481</td><td>9009</td><td>0.970</td><td>2</td><td>19.10</td><td>2.02</td><td>1.89</td><td>Accepted</td></tr><tr><td>G52r</td><td>60.15992</td><td>44.51843</td><td>86</td><td>98.405</td><td>11.706</td><td>0.970</td><td>2</td><td>20.78</td><td>2.58</td><td>2.46</td><td>Accepted</td></tr><tr><td>AlG52r</td><td>60.15992</td><td>44.51843</td><td>86</td><td></td><td></td><td>0.970</td><td>2</td><td>23.7</td><td>3.0</td><td>1.6</td><td>Accepted</td></tr><tr><td>G53</td><td>60.15940</td><td>44.51797</td><td>86</td><td>72.900</td><td>6056</td><td>0.970</td><td>2</td><td>15.36</td><td>1.39</td><td>1.27</td><td>Accepted</td></tr><tr><td colspan="12"><strong>M3 moraine: 15.6 ± 0.7</strong></td></tr><tr><td>25G1</td><td>60.15877</td><td>44.51994</td><td>100</td><td>63.303</td><td>5309</td><td>0.935</td><td>2</td><td>13.65</td><td>1.25</td><td>1.14</td><td>Accepted</td></tr><tr><td>Al25G1</td><td>60.15877</td><td>44.51994</td><td>100</td><td></td><td></td><td>0.935</td><td>2</td><td>13.0</td><td>1.6</td><td>0.9</td><td>Accepted</td></tr><tr><td>G2</td><td>60.15908</td><td>44.52000</td><td>96</td><td>81.728</td><td>7774</td><td>0.935</td><td>2</td><td>17.71</td><td>1.80</td><td>1.68</td><td>Accepted</td></tr><tr><td>G3</td><td>60.16011</td><td>44.52054</td><td>97</td><td>85.852</td><td>11.100</td><td>0.970</td><td>2.5</td><td>17.99</td><td>2.41</td><td>2.32</td><td>Accepted</td></tr><tr><td>G3r</td><td>60.16011</td><td>44.52054</td><td>97</td><td>81.487</td><td>14.301</td><td>0.970</td><td>2.5</td><td>17.06</td><td>3.05</td><td>2.98</td><td>Accepted</td></tr><tr><td>G4</td><td>60.16044</td><td>44.52083</td><td>100</td><td>72.910</td><td>8219</td><td>0.970</td><td>2.5</td><td>15.21</td><td>1.79</td><td>1.71</td><td>Accepted</td></tr><tr><td>G4r</td><td>60.16044</td><td>44.52083</td><td>100</td><td>74.732</td><td>7882</td><td>0.970</td><td>2.5</td><td>15.51</td><td>1.73</td><td>1.64</td><td>Accepted</td></tr><tr><td colspan="12"><strong>M4 moraine: 15.3 ± 0.3</strong></td></tr><tr><td colspan="12"><strong>M4-R moraine: 16.4 ± 0.8</strong></td></tr><tr><td>G6</td><td>60.16039</td><td>44.52247</td><td>107</td><td>92.051</td><td>6457</td><td>0.961</td><td>2</td><td>19.21</td><td>1.52</td><td>1.34</td><td>Accepted</td></tr><tr><td>G7</td><td>60.15928</td><td>44.52170</td><td>102</td><td>76.808</td><td>10.197</td><td>0.961</td><td>2</td><td>16.09</td><td>2.21</td><td>2.13</td><td>Accepted</td></tr><tr><td>G8</td><td>60.15974</td><td>44.52203</td><td>100</td><td>73.196</td><td>8499</td><td>0.961</td><td>2</td><td>15.36</td><td>1.86</td><td>1.78</td><td>Accepted</td></tr><tr><td>G9</td><td>60.16065</td><td>44.52526</td><td>129</td><td>77.673</td><td>8914</td><td>0.961</td><td>2</td><td>15.85</td><td>1.91</td><td>1.81</td><td>Accepted</td></tr><tr><td>G10</td><td>60.16060</td><td>44.52479</td><td>129</td><td>74.736</td><td>8390</td><td>0.961</td><td>2</td><td>15.25</td><td>1.79</td><td>1.70</td><td>Accepted</td></tr><tr><td colspan="12"><strong>M4-L moraine: 15.0 ± 0.7</strong></td></tr><tr><td>G41</td><td>60.16060</td><td>44.53468</td><td>130</td><td>77.232</td><td>11.156</td><td>0.962</td><td>2</td><td>15.72</td><td>2.34</td><td>2.26</td><td>Accepted</td></tr><tr><td>G41r</td><td>60.16060</td><td>44.53468</td><td>130</td><td>81.846</td><td>11.781</td><td>0.962</td><td>2</td><td>16.67</td><td>2.46</td><td>2.39</td><td>Accepted</td></tr><tr><td>AlG42r</td><td>60.1606</td><td>44.53374</td><td>138</td><td></td><td></td><td>0.962</td><td>2</td><td>15.7</td><td>1.9</td><td>0.8</td><td>Accepted</td></tr><tr><td>G44</td><td>60.16055</td><td>44.53485</td><td>129</td><td>75.566</td><td>9703</td><td>0.962</td><td>2</td><td>15.40</td><td>2.05</td><td>1.97</td><td>Accepted</td></tr><tr><td>G47</td><td>60.17450</td><td>44.56497</td><td>129</td><td>83.129</td><td>8193</td><td>0.972</td><td>2</td><td>16.78</td><td>1.76</td><td>1.65</td><td>Accepted</td></tr><tr><td>G43</td><td>60.16045</td><td>44.53317</td><td>134</td><td>73.181</td><td>7447</td><td>0.970</td><td>3</td><td>14.84</td><td>1.60</td><td>1.51</td><td>Accepted</td></tr><tr><td>G43r</td><td>60.16045</td><td>44.53317</td><td>134</td><td>68.372</td><td>5121</td><td>0.970</td><td>3</td><td>13.86</td><td>1.15</td><td>1.04</td><td>Accepted</td></tr><tr><td>AlG43r</td><td>60.16045</td><td>44.53317</td><td>134</td><td></td><td></td><td>0.970</td><td>3</td><td>13.4</td><td>2.0</td><td>1.3</td><td>Accepted</td></tr><tr><td colspan="12"><strong>Flat surface: 12.2 ± 0.6</strong></td></tr><tr><td>G21</td><td>60.15920</td><td>44.53281</td><td>137</td><td>64.285</td><td>8190</td><td>0.959</td><td>2</td><td>13.03</td><td>1.73</td><td>1.66</td><td>Accepted</td></tr><tr><td>G22</td><td>60.15936</td><td>44.53134</td><td>135</td><td>64.618</td><td>6635</td><td>0.959</td><td>2</td><td>13.13</td><td>1.43</td><td>1.34</td><td>Accepted</td></tr><tr><td>G24</td><td>60.15954</td><td>44.53182</td><td>136</td><td>73.370</td><td>9000</td><td>0.959</td><td>2</td><td>14.89</td><td>1.90</td><td>1.82</td><td>Accepted</td></tr><tr><td>G38</td><td>60.15923</td><td>44.53532</td><td>138</td><td>59.609</td><td>5827</td><td>0.959</td><td>2</td><td>12.07</td><td>1.26</td><td>1.18</td><td>Accepted</td></tr><tr><td>G39</td><td>60.15930</td><td>44.53459</td><td>138</td><td>52.811</td><td>7343</td><td>0.959</td><td>2</td><td>10.67</td><td>1.53</td><td>1.49</td><td>Accepted</td></tr><tr><td>G40</td><td>60.15980</td><td>44.53382</td><td>132</td><td>53.090</td><td>6358</td><td>0.959</td><td>2</td><td>10.79</td><td>1.36</td><td>1.30</td><td>Accepted</td></tr><tr><td colspan="12"><strong>M5 moraine: 14.7 ± 0.8</strong></td></tr></tbody></table>
<table><caption>**Table 1.** (Continued)</caption><thead><tr><th>Sample name</th><th>Latitude (°N)</th><th>Longitude (°W)</th><th>Elevation (m)</th><th>[<sup>10</sup>Be] (atoms g<sup>-1</sup>)</th><th>[<sup>10</sup>Be] uncertainty (atoms g<sup>-1</sup>)</th><th>Shielding factor</th><th>Thickness (cm)</th><th>Exposure ages (ka)</th><th>External uncertainty (ka)</th><th>Internal uncertainty (ka)</th><th>Chi<sup>2</sup> test</th></tr></thead><tbody><tr><td>G29</td><td>60.15721</td><td>44.54180</td><td>154</td><td>70 250</td><td>10 164</td><td>0.959</td><td>2</td><td>14.02</td><td>2.09</td><td>2.02</td><td>Accepted</td></tr><tr><td>G29r</td><td>60.15721</td><td>44.54180</td><td>154</td><td>75 805</td><td>7276</td><td>0.959</td><td>2</td><td>15.13</td><td>1.55</td><td>1.45</td><td>Accepted</td></tr><tr><td>AlG29r</td><td>60.15721</td><td>44.54180</td><td>154</td><td></td><td></td><td>0.959</td><td>2</td><td>8.9</td><td>1.3</td><td>0.9</td><td>Accepted</td></tr><tr><td>G30</td><td>60.15774</td><td>44.54070</td><td>156</td><td>71 000</td><td>9070</td><td>0.959</td><td>2</td><td>14.14</td><td>1.87</td><td>1.80</td><td>Accepted</td></tr><tr><td>G36</td><td>60.15816</td><td>44.53586</td><td>143</td><td>70 488</td><td>5875</td><td>0.959</td><td>2</td><td>14.21</td><td>1.29</td><td>1.18</td><td>Accepted</td></tr><tr><td>G37</td><td>60.15816</td><td>44.53614</td><td>146</td><td>89 400</td><td>9030</td><td>0.959</td><td>2</td><td>17.99</td><td>1.93</td><td>1.81</td><td>Accepted</td></tr><tr><td>G32</td><td>60.15780</td><td>44.53887</td><td>157</td><td>69 859</td><td>8390</td><td>0.970</td><td>4</td><td>13.97</td><td>1.75</td><td>1.67</td><td>Accepted</td></tr><tr><td>M6-R moraine: 4.3 ± 0.4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>G13</td><td>60.15742</td><td>44.53284</td><td>160</td><td>20 478</td><td>4475</td><td>0.922</td><td>2</td><td>4.25</td><td>0.96</td><td>0.95</td><td>Accepted</td></tr><tr><td>G14</td><td>60.15742</td><td>44.53284</td><td>160</td><td>21 431</td><td>3082</td><td>0.922</td><td>2</td><td>4.45</td><td>0.68</td><td>0.66</td><td>Accepted</td></tr><tr><td>G15</td><td>60.15742</td><td>44.53284</td><td>160</td><td>14 256</td><td>4589</td><td>0.922</td><td>2</td><td>2.92</td><td>0.98</td><td>0.97</td><td>Accepted</td></tr><tr><td>G16</td><td>60.15742</td><td>44.53284</td><td>160</td><td>24 965</td><td>3867</td><td>0.922</td><td>2</td><td>5.21</td><td>0.82</td><td>0.80</td><td>Accepted</td></tr><tr><td>M6-L moraine: 4.8 ± 0.5</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>G34</td><td>60.15786</td><td>44.53618</td><td>154</td><td>20 107</td><td>4375</td><td>0.959</td><td>3</td><td>4.07</td><td>0.92</td><td>0.90</td><td>Accepted</td></tr><tr><td>G35</td><td>60.15790</td><td>44.53500</td><td>146</td><td>24 589</td><td>3502</td><td>0.959</td><td>2</td><td>4.99</td><td>0.73</td><td>0.71</td><td>Accepted</td></tr><tr><td>M7 moraine</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>G33</td><td>60.15769</td><td>44.53522</td><td>154</td><td>19 100</td><td>4753</td><td>0.959</td><td>2</td><td>3.81</td><td>0.99</td><td>0.98</td><td>—</td></tr><tr><td>M8 moraine: 2.9 ± 0.3</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>G17</td><td>60.15698</td><td>44.53410</td><td>159</td><td>16 754</td><td>3586</td><td>0.941</td><td>2</td><td>3.37</td><td>0.75</td><td>0.74</td><td>Accepted</td></tr><tr><td>G19</td><td>60.15701</td><td>44.53365</td><td>159</td><td>14 396</td><td>1180</td><td>0.941</td><td>2</td><td>2.89</td><td>0.26</td><td>0.24</td><td>Accepted</td></tr><tr><td>Bedrock</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>G54</td><td>60.15198</td><td>44.53087</td><td>301</td><td>42 290</td><td>11 315</td><td>0.940</td><td>2</td><td>7.47</td><td>1.96</td><td>1.94</td><td>—</td></tr><tr><td>Sand</td><td>60.15740</td><td>44.54047</td><td>154</td><td>17 873</td><td>1930</td><td>0.959</td><td>0.5</td><td>3.51</td><td>0.41</td><td>0.39</td><td>—</td></tr></tbody></table>
<table><caption>**Table 2.** AMS analytical data, $^{10}$Be exposure ages and $^{26}$Al/$^{10}$Be ratios. $^{10}$Be/$^{9}$Be and $^{26}$Al/$^{27}$Al ratios were inferred from measurements at the ASTER AMS facility.</caption><thead><tr><th>Sample name</th><th>Quartz weight (g)</th><th><sup>9</sup>Be mass in carrier (mg)</th><th><sup>10</sup>Be/<sup>9</sup>Be</th><th>1σ <sup>10</sup>Be/<sup>9</sup>Be</th><th>Blank corrected [<sup>10</sup>Be] (at/g)</th><th>1σ uncertainty (at/g)</th><th>total <sup>27</sup>Al mass (mg)</th><th><sup>26</sup>Al/<sup>27</sup>Al</th><th>Blank corrected [<sup>26</sup>Al] (at/g)</th><th>1σ uncertainty (at/g)</th><th><sup>26</sup>Al/<sup>10</sup>Be</th><th><sup>26</sup>Al/<sup>10</sup>Be uncertainty</th></tr></thead><tbody><tr><td>GRE 1 R</td><td>32.6578</td><td>0.4851</td><td>6.931E-14</td><td>5.4161E-15</td><td>64.477</td><td>5403</td><td>4.3511</td><td>1.3269E-13</td><td>8.2199E-15</td><td>393 500</td><td>24 482</td><td>6.10</td><td>0.64</td></tr><tr><td>GRE 29 R</td><td>29.0211</td><td>0.4601</td><td>7.7212E-14</td><td>8.7384E-15</td><td>76 936</td><td>9278</td><td>7.2457</td><td>5.1513E-14</td><td>4.5862E-15</td><td>285 841</td><td>25 593</td><td>3.72</td><td>0.56</td></tr><tr><td>GRE 42 R</td><td>43.8433</td><td>0.4650</td><td>1.5555E-13</td><td>1.3988E-14</td><td>107 018</td><td>9929</td><td>2.9129</td><td>3.3523E-13</td><td>1.3852E-14</td><td>496 302</td><td>20 633</td><td>4.64</td><td>0.47</td></tr><tr><td>GRE 43 R</td><td>21.7759</td><td>0.4650</td><td>5.3262E-14</td><td>4.9876E-15</td><td>69 516</td><td>7157</td><td>1.7654</td><td>2.3395E-13</td><td>2.1784E-14</td><td>421 711</td><td>39 588</td><td>6.07</td><td>0.85</td></tr><tr><td>GRE 48 R</td><td>15.4659</td><td>0.4665</td><td>5.8168E-14</td><td>3.9295E-15</td><td>108 111</td><td>7995</td><td>2.1950</td><td>2.1677E-13</td><td>1.5315E-14</td><td>684 377</td><td>48 763</td><td>6.33</td><td>0.65</td></tr><tr><td>GRE 52 R</td><td>13.9218</td><td>0.4642</td><td>4.9439E-14</td><td>4.7169E-15</td><td>100 013</td><td>10 575</td><td>1.7378</td><td>2.5452E-13</td><td>1.4529E-14</td><td>706 577</td><td>40 840</td><td>7.06</td><td>0.85</td></tr><tr><td>Bk</td><td></td><td>0.4615</td><td>4.5788E-15</td><td>4.9132E-16</td><td></td><td></td><td>1.3972</td><td>1.1321E-15</td><td>1.1321E-15</td><td></td><td></td><td></td><td></td></tr></tbody></table>

value was used (Paterson, 1994). The impact of lateral drag was considered by calculating the shape factor (Nye, 1952) at several cross sections established at the locations where bed topography significantly changes, and then ice thickness and ice surface elevation were recalculated along flowlines. Finally, ice surface elevation was interpolated from the flowline points through the 'Topo to Raster' routine, and the DEM of the palaeoglacier was obtained for different glacial stages. Here, we selected for the two investigated Lateglacial and Holocene periods two frontal well-preserved moraines to constrain glacier extent and derived climate conditions.

## ELA and temperature estimates

The equilibrium-line altitude (ELA) is a glaciological concept representing the dividing line between the accumulation and ablation zones. ELA variations of mountain glaciers are a sensitive indicator of climate change that have been commonly used to reconstruct palaeoclimates at different temporal and spatial scales (Jomelli et al., 2011; Sagredo et al., 2014; Biette et al., 2018). It corresponds to the altitude at which snow accumulation is exactly balanced by ablation (net mass balance equals zero) (Porter, 1975; Benn et al., 2005). Rupper and Roe (2008) and Rupper et al. (2009) demonstrated that ELA sensitivity to changes in temperature and precipitation is strongly related to the dominant ablation process. ELAs respond linearly to changes in temperature, with the magnitude of the response determined by the local lapse rates. In Greenland, a robust relationship between glacier fluctuations and summer air temperature has been documented over the past century, confirming the significance of ELA variability to temperature changes (Bjørk et al., 2012; Leclercq et al., 2012).

In this study, we investigated minimum past temperature anomalies relative to the present by comparing modern glacier ELAs estimated from RGI (2017) between 2000 and 2016 with palaeo-ELA estimates. Various methods have been proposed to reconstruct palaeo-ELAs (Benn and Evans, 1998). The more comprehensive reconstruction methods take into account the size, shape and distribution of the total ice surface area versus elevation (i.e., hypsometry). For example, the accumulation area ratio (AAR) method assumes that the accumulation area of a glacier occupies a fixed proportion of a glacier's total surface area. The ELA is then determined by applying an estimated AAR value to a hypsometric plot. Temperate glaciers have an average AAR of approximately 0.65. Therefore, palaeo-ELA was calculated assuming such AAR for the two reconstructed glacial stages using the 'ELA calculation' GIS toolbox (Pellitero et al., 2015), which only required the DEM of the (reconstructed) glacier. Considering an atmospheric lapse rate of ~0.68°C 100 m⁻¹ on average in modern-day Greenland (e.g., Nesje et al., 1991; Dahl and Nesje, 1992; Fausto et al., 2009) and assuming that precipitation remained constant through the considered period, temperature change (ΔT) responsible for an ELA elevation shift (ΔELA) was estimated (ΔT = ΔELA * 0.68).

## TraCE-21ka simulations

To gain a better understanding of local climate conditions, we also used TraCE-21ka simulation from the CCSM3 model that covers the last deglaciation and the Holocene (Liu et al. 2009). The TraCE-21ka simulation includes variations in insolation, greenhouse gas (GHG) concentrations, ice-sheet extension and altitude from the ICE5-G reconstruction and also a crude estimate of associated freshwater release in the North Atlantic. To attribute the role played by each individual forcing, we
also use the attribution experiments from TraCE-21ka. These simulations are named ICE when only the effect of ice sheet variations is included, GHG when only greenhouse gases changes are included, ORB when only orbital changes is included, MWP when only the melt water release from the land ice is included and Full when the simulation includes all of those individual forcings (cf. Liu et al. 2009).

# Results

## CHA glacier chronology

We present 43 new ¹⁰Be CRE ages, eight ¹⁰Be CRE ages replicates and six ²⁶Al CRE ages (57 CRE ages in total) collected from moraine boulders, a vertical bedrock surface polished by glacial erosion and a sand deposit in an intramoraine depression from the CHA glacier forefield. Sample G1 and six out of eight replicates (G29r, G41r, G42r, G43r, G48r and G52r) were processed in 2025 to obtain both ¹⁰Be and ²⁶Al CRE ages in order to detect complex exposure histories. In the next paragraphs, ²⁶Al CRE ages will be used to detect possible inheritance but will not be used to calculated the mean moraine ages based on ¹⁰Be measurements only.

Along the longitudinal axis of the glacier flow, at ~1.4 km from the current front position, an arcuate deposit corresponds to the furthest downstream frontal moraine of the glacier observed in the field. This moraine remains (M1) consists of large boulders (>2 m high) at an altitude of 135 m a.s.l. The two samples collected from it and processed in 2023 show ¹⁰Be CRE ages of 19.2 ± 2.5 ka (G50) and 18.8 ± 2.3 ka (G48), respectively, yielding a weighted mean age of 20.2 ± 1.5 ka (n = 2). G48r was reprocessed in 2025 and yielded a ¹⁰Be CRE age of 21.6 ± 2.4 ka, which is consistent with its corresponding ²⁶Al CRE age of 21.7 ± 1.7 ka (AlG48r). Combining the ¹⁰Be CRE mean of the G48 and G48r ages with the ¹⁰Be CRE age of G50 would yield a weighted mean of 19.9 ± 1.3 ka (n = 2).

On the right side of the CHA glacier, we identified the most distant lateral moraine, labelled M2, located approximately at ~1.1 km from the current ice front position. Composed of large boulders, this 300-m-long moraine disappears near the longitudinal axis of the glacier flow (Fig. 4). This ridge is covered by vegetation, and large lichens (<8 cm in diameter) are visible on the surface of the boulders. Three samples with one replicate (G52r) were collected on this M2 ridge, ranging in age from 20.8 ± 2.6 ka (G52r) to 15.4 ± 1.4 ka (G53). G52 dated to 19.1 ± 2.0 ka is comparable to its replicate G52r (20.8 ± 2.6 ka), and G52r is not significantly different from its ²⁶Al CRE age dated to 23.7 ± 1.3 ka. With an age of 19.7 ± 1.5 ka for the weighted mean of G52 and G52r, the moraine shows a ¹⁰Be mean age of 17.7 ± 0.8 ka (n = 3). Considering the topographic position of the lateral moraines M2 and the frontal moraine M1 described above and their ages, it can be assumed that these two moraines correspond to the same glacier advance, with a weighted mean age of 18.4 ± 0.7 ka (n = 5).

About 120 m above the M2 moraine is the M3 moraine. Four samples were collected from the lateral M3 moraine, including two replicates: G3r and G4r. G3, G4 and their replicates G3r and G4r do not show significantly different ages, yielding a ¹⁰Be CRE mean age of 18.0 ± 2.2 ka for G3–G3r and a mean age of 15.3 ± 1.4 ka for G4–G4r. Interestingly, the ¹⁰Be age of 25G1 (13.7 ± 1.3 ka) is similar to its ²⁶Al CRE age of 13.0 ± 0.9 ka. The weighted mean age of the M3 moraine is 15.5 ± 0.7 ka based on the ¹⁰Be ages of 25G1, G2 and the means of G3–G3r and G4–G4r (n = 4).

The lateral moraine M4-R on the right side of the glacier, about 30 m horizontally upstream from M3, is composed of

large blocks that are visible for 200 m and also disappears near the longitudinal axis of the glacier flow. On this lateral moraine, five samples were taken from stable boulders with ages varying from 19.2 ± 1.5 ka (G6) to 15.3 ± 1.8 ka (G10), yielding a weighted mean of 16.4 ± 0.8 ka (n = 5).

On the left side of the glacier, the M4-L moraine, located about 10 m in altitude above M1, is an arcuate rampart stretching more than 300 m, consisting of an alignment of large dark-coloured blocks perpendicular to the direction of the palaeo-ice flow at an altitude of about 130 m a.s.l. On this moraine, five samples were taken near the longitudinal axis of the glacier. Additional replicates G41r, G42r and G43r with enough purified quartz remaining were processed, with ages ranging from 21.3 ± 2.5 ka (G42r) to 13.9 ± 1.2 ka (G43r). The ages of the three replicates G41r, G42r and G43r are similar to their original ages and the ²⁶Al CRE age of G43r (13.4 ± 1.3 ka) is identical to its ¹⁰Be age (13.9 ± 1.2 ka). On the contrary, the ²⁶Al CRE age of G42r (15.7 ± 0.8 ka) is significantly younger than its ¹⁰Be age (21.3 ± 2.5 ka), suggesting a complex exposure or post-depositional history for this boulder that will be discussed in the next section. Moreover, the ¹⁰Be mean age of the samples G42 and G42r is considered as an outlier when it is combined with the other samples based on the Chi² test. Thus, this sample can be rejected from the calculation of the weighted mean age of the moraine M4-L, yielding an age of 15.0 ± 0.7 ka (n = 4). Grouping samples from M4-L with those from M4-R would yield a weighted mean age of 15.3 ± 0.3 ka (n = 9).

The M5 moraine, located on the left side of the glacier, about 600 m from the current ice front, is another visible rampart in the landscape at about 140 m a.s.l. M5 towers above M4 by about 10–15 m. On this M5 moraine, five samples (with a replicate G29r with its ¹⁰Be and ²⁶Al ages) were taken from large dark-coloured blocks. The ¹⁰Be age of G29r (15.1 ± 1.6 ka) does not differ from its original age but is significantly older than its ²⁶Al age (8.9 ± 0.9 ka), which suggests nuclide inheritance, which will be discussed in the next section. The weighted mean of this M5 moraine is 14.7 ± 0.8 ka (n = 5) and 14.8 ± 0.8 ka (n = 4) excluding the mean age of G29–G29r, which is affected by inheritance. From a chronological point of view, this M5 moraine cannot be distinguished from the M4 moraine, but its topographic position closer to the front and located higher in altitude explains why these two geomorphological units are considered distinct here.

Between moraines M4 and M5, along the longitudinal axis of the glacier's flow, six samples were taken from a flat landscape consisting of large, white boulders covered with smaller lichens compared to the boulders sampled on the previous stratigraphically older moraines. On this flat landscape, the six samples show ages ranging from 14.9 ± 1.9 ka (G24) to 10.7 ± 1.5 ka (G39), with a weighted mean of 12.2 ± 0.6 ka (n = 6).

Upstream of M5, another flat sandy fluvioglacial surface about 100 m long, likely corresponding to the surface of a former lake caused by a morainic dam, was sampled. An exposure age of 3.5 ± 0.4 ka was determined here.

On the left side of the glacier, the summit of moraine M6-L is about 10 m above the flat surface. Two samples, G34 and G35, were collected from this moraine, with ages of 4.1 ± 0.9 and 5.0 ± 0.7 ka, respectively, accounting for a weighted mean age of 4.8 ± 0.5 ka (n = 2). On the right side of the glacier, four samples were collected on M6-R, ranging from 5.2 ± 0.8 ka (G16) to 2.9 ± 1.0 ka (G15). Consequently, the weighted mean of M6-R moraine is 4.3 ± 0.4 ka (n = 4), statistically consistent with M6-L, if the uncertainties associated with the ¹⁰Be weighted means are considered. Grouping moraine samples
from the left and the right sides of the glacier yielded a mean age of 4.4 ± 0.3 ka (n = 6).

On the left side of the glacier, a moraine boulder was sampled on the M7 moraine, just upstream of M6-L moraine. Its ¹⁰Be CRE age is 3.8 ± 1.0 ka (G33).

Finally, four samples taken from a more recent moraine on the right side of the glacier yielded scattered ages ranging from 12.3 ± 3.0 ka (G20) to 2.9 ± 0.3 ka (G19). As the two samples G18 (11.7 ± 2.6 ka) and G20 disagree with the chronostratigraphic arrangement, they were considered as outliers. Thus M8 moraine yielded a weighted mean of 2.9 ± 0.3 ka based on the two samples G17 (3.4 ± 0.8 ka) and G19. At an altitude of 300 m a.s.l., a sample was collected in the rockwall located on the right side of the glacier, 50 m upright of the current front position. This sample collected on a polished subvertical roche moutonnée is dated to 7.5 ± 2.0 ka (G54).

## *Glacier reconstruction, ELAs, and palaeoclimatic inferences*

From geomorphic evidence (i.e., prominent moraines) and numerical modelling, we reconstructed the CHA glacier extent for two different glacial stages constrained by ¹⁰Be CRE ages. First, during the Lateglacial at 18.4 ± 0.7 ka (M1 and M2 lateral moraine), our results show that the glacier occupied 2.9 km² and reached the bottom of the main valley (130 m a.s.l.) as a piedmont lobe, flowing mostly eastwards, following slope direction (Fig. 5). The ELA during that phase was at

288 m. Second, during the Late Holocene at 4.4 ± 0.4 ka (M6 moraine), glacier reconstruction results show that the glacier had lost one-third of its surface, barely reaching the main valley, with its terminus 50 m higher and the ELA at 523 m. According to the satellite image collected in August 2023, the current glacier extends over only 0.87 km², which represents ~46% of the surface that it occupied during the maximum ice extent of the Late Holocene.

The use of the ELA shifts between the stages identified from the two moraines M1 and M6, and a lapse rate of 0.68°C 100 m⁻¹ allowed us to infer summer temperature depressions assuming that long-term precipitation has remained constant. During the 2000–2019 period, the ELA has greatly fluctuated from 464 m (2014) to 1078 m (2009) in the area (RGI6 https://www.glims.org/RGI/), with an average value of 771 m. Therefore, the Lateglacial and Late Holocene ELA depressions, of 284 and 483 m, respectively, compared to present-day conditions, account for a summer temperature cooling of 3.3°C and 1.7°C, respectively (Table 3).

## Discussion

### Uncertainties of the ¹⁰Be ages

In 2023, a total of 42 samples were prepared at LN2C CEREGE using a standardised protocol that typically results in analytical uncertainties of less than 10%. The CRE ages from the CHA glacier have larger uncertainties than those generally document-

<figure><img src="image_6.png" /><figcaption>**Figure 5.** Aerial (left) and frontal (right) views of the CHA glacier extent for the Lateglacial (up) (18.4 ± 0.7 ka, M1 and M2 lateral moraine), and the Late Holocene (down) (4.4 ± 0.3 ka, M6 moraine) periods reconstructed from the GlaRe toolbox. [Color figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>
<table><caption>**Table 3.** Surface and equilibrium-line altitude of the CHA glacier and palaeoclimatic inferences for the different stages compared with present-day conditions.</caption><thead><tr><th>Stage</th><th>Glacier area (km²)</th><th>ELA (m a.s.l.) (AAR = 0.65)</th><th>ELA lowering (m) compared to present day</th><th>Summer temperature cooling (°C)</th></tr></thead><tbody><tr><td>Present day</td><td>0.87</td><td>771</td><td>—</td><td>—</td></tr><tr><td>Late Holocene</td><td>1.90</td><td>523</td><td>248</td><td>1.7</td></tr><tr><td>Lateglacial</td><td>2.85</td><td>288</td><td>483</td><td>3.3</td></tr></tbody></table>

**Figure 6.** Plot comparing measured $^{10}$Be concentrations (X-axis) to the $^{26}$Al/$^{10}$Be ratios (Y-axis). Ratios are measured $^{26}$Al and $^{10}$Be concentrations for the six replicates, normalised to their surface production rates. White dots show the sample replicates with their internal uncertainties. The grid shows isolines of erosion and burial. [Color figure can be viewed at wileyonlinelibrary.com]

<figure><img src="image_7.png" /></figure>

ted for this period and this region (~10%–6%). Here, the data show up to 20% analytical uncertainties, with blank values ranging from $4 \times 10^{-15}$ to $1 \times 10^{-15}$ (Table S1). These high percentages are due to a lower current than generally measured in the target at ASTER facility. For instance, the mean current values for this batch of samples are ~600–900 nA, whereas usual currents measured at the ASTER facility are >1 µA (including blanks with values >5 µA). The causes for such high uncertainties remain elusive. One hypothesis would be related to the lithology of the CHA catchment, which is described as ‘rotten granite’ on local geological maps (Allaart, 1976; Chadwick and Garde 1996). This would suggest an unexpected unperfect purification at the end of the process. These large uncertainties imply that for some landforms, the mean age must be considered with caution, since most samples passed the Chi² test with large uncertainties. However, this would not change our palaeoclimatic interpretations. Assuming an uncertainty of about 10%, classically observed in the literature, would not affect the age of the moraines significantly. For instance, M4-R would show a mean age of 16.6 ka instead of 16.4 ka. On M6-R lateral moraine, this would affect the number of samples considered in the mean age calculation but would not change our interpretation. On this moraine, G15 dated to 2.9 ka would be rejected, but the new age of the moraine would be almost the same at ~4.6 ka instead of 4.3 ka. To improve the robustness of our chronology, eight replicate samples were processed in 2025 using a slightly modified protocol. Notably, all replicates had Al concentrations before quartz total dissolution, which remained below 0.200 ppm prior to complete quartz dissolution—a threshold typically associated with beam currents exceeding 1 µA. While a detailed evaluation of the modified protocol’s potential advantages is beyond the scope of this paper, it is worth noting that the 2025 measurements yielded lower analytical uncertainties than those from 2023. However, currents still remained lower than usual (except for blanks) despite a more drastic purification process (more leaching, ICPOES tests), in 2025. Importantly, results from both 2023 and 2025 are consistent, yielding comparable exposure ages.

## Cosmogenic nuclide inheritance of the $^{10}$Be ages

Cosmogenic exposure ages of moraine boulders at the base of the CHA glacier suggest that moraines M1–M4 were deposited during the Lateglacial, about ~4 ka before the earliest documented retreat of the GrIS or the Julianhab ice cap retreat in this sector. This timing is inferred from minimum ages derived from $^{14}$C at the base of lake sediment cores and from CRE ages from roche moutonnees or erratic boulders closer to the coast (Fig. 2; Bennike et al., 2002; Andersen et al., 2020; Levy et al., 2020). One possible explanation for the discrepancy between the CHA glacier chronology and the retreat timing of the GrIS is the presence of cosmogenic nuclide inheritance in the $^{10}$Be ages reported from CHA glacier moraines. Interestingly, Andersen et al. (2020) reported 50 new paired *in situ* cosmogenic paired $^{26}$Al/$^{10}$Be measurements from bedrock and erratic boulders assumed to have been eroded and transported by the GrIS in the same region. Their study identified a clear elevation-dependent gradient in nuclide inheritance in bedrock sites. Sites below 800 m a.s.l. generally showed minimal or no inheritance (i.e., no significant pre-LGM exposure), whereas sites at higher elevations showed a wide range of inheritance levels, from negligible to >90 ka, depending on local topography. All moraine boulders sampled in this study are located below 170 m a.s.l. G54 dated to 7.5 ka is the only high elevated sample that is not collected on a moraine but on the rockwall ~50 m above the current glacier front. In 2025, $^{26}$Al and $^{10}$Be concentrations were measured in samples from four old CHA moraines (M1, M2, M3 and M5). $^{26}$Al/$^{10}$Be ratios are presented in Fig. 6 and summarised in Table 2. The samples (G29 and G48) show $^{26}$Al/$^{10}$Be ratios of 3.7 and 4.2, respectively, suggesting a complex history. The four others show $^{26}$Al/$^{10}$Be ratios between 6.4 and 7.1, suggesting that these samples were not affected by inheritance. No significant age discrepancies were observed between $^{10}$Be and $^{26}$Al in G48r on M1 (~21.6 and ~21.7 ka, respectively), in G52r on M2 (20.8 ± 2.5 ka vs. 23.7 ± 1.6 ka considering analytical uncertainties), in 25G1 on
M3 (13.6 ± 1.1 ka vs. 13.0 ± 1.6 ka) or on the same moraine in G43r (13.9 ± 1.1 ka vs. 13.4 ± 2.0 ka). These results suggest little to no nuclide inheritance in these samples, therefore consistent with earlier findings from low-elevation sites in southern Greenland (Andersen et al., 2020). However, on M4, while G43r shows no significant difference between ¹⁰Be and ²⁶Al ages (13.9 vs. 13.4 ka), G42r reveals a clear discrepancy, with a ²⁶Al age significantly younger than its ¹⁰Be counterpart, suggesting potential nuclide inheritance up to ~6 ka. Similarly, sample G29r on M5 also shows an ~6 ka discrepancy, also indicating nuclide inheritance.

Overall, among the six samples with paired ²⁶Al and ¹⁰Be data, two (approximately one-third of the data set) show evidence of inheritance. Consequently, while CRE ages reported in that study may be influenced by nuclide inheritance, our paired ¹⁰Be and ²⁶Al ages suggest that such inheritance is not systematic. Nonetheless, it is noteworthy that the boulders without signs of nuclide inheritance are located on the oldest moraines.

Some evidence of cosmogenic nuclide inheritance in LIA moraines has been reported in Greenland by Larsen et al. (2021). The retreat of the GrIS beyond its present-day margin occurred during the Holocene Thermal Maximum, followed by a readvance to near-modern extents during the Neoglacial or the LIA (Larsen et al., 2015). This retreat was likely driven by a combination of atmospheric warming and the incursion of warm ocean waters into deep fjords, which facilitated rapid GrIS retraction during the Lateglacial and Early Holocene (Larsen et al., 2011; Carlson et al., 2014; Winsor et al., 2015a, 2015b). Given these dynamics, it is plausible that nuclide inheritance may also affect Late Holocene moraines of the CHA glacier. However, the fresh morphology of some landforms—particularly moraines M7 and M8—supports their interpretation as LIA deposits; the more developed vegetation cover and subdued appearance of moraine M6 suggest an older formation, possibly predating the LIA.

## Fluctuations of the CHA glacier during the Lateglacial and Holocene

The 43 ¹⁰Be CRE ages and eight replicates from samples collected on moraine boulders, intramoraine sand deposit and rockwall from the CHA glacier near Cape Farewell provide novel insights about the Lateglacial and Holocene mountain glacier fluctuations and their related climate conditions in southern Greenland. Large uncertainties associated with the CRE ages do not significantly affect our interpretations discussed thereafter. Based on our understanding of GrIS fluctuations, our data set offers an independent mountain glacier chronology that spans a notably long-time interval compared to what is typically available across Greenland. This study is particularly distinctive, as much of Greenland was covered by the ice sheet proper during the last glacial cycle, making the development of isolated mountain glacier chronologies both rare and valuable in terms of climate sensitivity.

The oldest documented frontal and lateral moraines (M1, M2, M3 and M4) are dated to ~18–15 ka, respectively, suggesting glacier culmination during the cold event of the Oldest Dryas (18.5–14 ka). Between ~18 and ~15 ka, the glacier experienced a significant retreat interrupted by minor advances or standstills long enough to create at least three moraines (M2–M3–M4).

The retreat of the CHA glacier as early as ~18 ka seems to occur about 4–3 ka earlier than the land-terminating outlet glaciers of the GrIS in the southernmost part of the island. The causes of such discrepancy remain unclear. While we do not rule out the possibility that some boulders at the base of the CHA glacier may be affected by cosmogenic nuclide inheritance, we

propose that the oldest moraines (M1–M3) were deposited during the Lateglacial. This interpretation is supported by the observation that all boulders showing consistent ¹⁰Be and ²⁶Al ages—indicating no inheritance—are located on these older moraines. These exposure ages suggest that the CHA glacier became individualised from the GrIS or the Julianehåb Ice Cap during the Lateglacial, with moraines M1–M3 forming during this period. We further speculate that at least part of the CHA valley constituted a pocket of southern Greenland that remained ice-free several thousand years earlier than currently documented. This would imply that (i) the CHA valley either remained untouched by the main ice sheet; (ii) the de-coupling occurred as early as ~18 ka; or (iii) the GrIS persisted in the main fjord outlets, while the CHA glacier existed more or less independently. The orientation of the valley—perpendicular to the dominant GrIS flow direction—may have favoured such an early individualisation of the CHA glacier. The retreat of the GrIS or the Julianehab ice cap retreat in this region may have been spatially heterogeneous, which could account for the age discrepancy between boulders at the base of the CHA glacier and those reported in earlier studies (Andersen et al., 2020; Levy et al., 2020). Notably, Levy et al. (2020) observed a clear asynchrony in deglaciation patterns: South Greenland (south of 61.5° N) deglaciated between ~14.8 and 11.9 ka, whereas Southeast Greenland (61.5° N to 68.2° N) experienced deglaciation later: between ~11.4 and 11.3 ka. This spatial variation in ice retreat timing supports the possibility of earlier deglaciation in southwestern Greenland, consistent with the ages observed in the CHA valley.

Between the Lateglacial moraines and the Late Holocene moraine (M6), a flat topographic surface was dated to 12.2 ± 0.6 ka ($n=6$). The process (es) that created this landform remains difficult to identify. Currently, the right part of the surface is incised by two proglacial streams and covered by shrubs. The white surface of the sampled boulders may correspond to erosion related to these two streams or to the draining of a temporary shallow lake that may have formed in the past. This could explain why the apparent exposure ages of boulders on this surface are anomalously young compared to those on upstream moraines and do not follow the expected stratigraphic order. Another hypothesis would be related to inheritance of boulders sampled on M5 moraine.

On the left side of the glacier, the sand deposit is interpreted as another temporary shallow lake that formed behind M5 moraine. The age of the sand sample (~3.8 ka) may either correspond to the drying phase of the lake probably due to change in the active layer thickness across the area, changing the drainage patterns, or could be related to the erosion of moraine M6 upstream, which shows a palaeochannel cutting through the moraine ridge. Interestingly, we did not find any moraines formed during either the Early or the Mid Holocene, suggesting that the glacier was smaller during both periods than during the Late Holocene. However, this observation should be interpreted with caution, as boulders on moraine M5 may be affected by cosmogenic nuclide inheritance. Indeed, the ²⁶Al age of Gre29r revealed at least 6 ka of inheritance. Additional paired ²⁶Al/¹⁰Be measurements would be necessary to confirm this interpretation and obtain a more definitive chronology. The age of the sample collected on a polished part of the rockwall is interpreted here as a minimum age reflecting ice thickness. In other words, the surface of the glacier was at least 50 m higher than today for periods older than ~8 ka, that is, and most probably earlier than the Early Holocene considering the fact that no moraine from that period was observed in the field. Several moraines were formed during the Late Holocene. The oldest one, corresponding to the largest Holocene glacier advance, occurred at ~4.4 ka. One sample collected on the inner moraine M7 dated to ~3.5 ka
suggests that the CHA glacier experienced minor retreat and re-
advances and/or stagnation following this larger Late Holocene
culmination. Unfortunately, periglacial and/or paraglacial pro-
cesses or inheritance caused age scatter on moraine M8 located
at the base of a high rockwall of about 200 m height (Figs. 3
and 4), which was dated to ~2.9 ka according to the mean of the
two dated samples. Inner moraines have been observed on the
field and mapped in Fig. 4, but could not be sampled. Due to
their proximity to the current ice front position, this moraine may
have been formed during the LIA.

Comparing the evolution of the CHA glacier with
other mountain glaciers in Greenland

Comparing the evolution of the CHA glacier with other
mountain glaciers in Greenland reveals an interesting pattern.

Palaeo mountain glacier records documenting the Lateglacial
period remain limited in Greenland, in particular in its
southernmost fringe. Moraines at the base of the CHA glacier
suggest that the retreat phase during the Lateglacial was
discontinuous through time and climatic conditions enabled
the glacier to record several (at least three) phases of minor
readvances or stabilisations. Available data of past glacial
oscillations of local glaciers from other regions of Greenland
revealed a rather synchronous phase of retreat at the onset of
the Lateglacial. In eastern Greenland, ¹⁰Be exposure ages from
eratics suggest that the deglaciation occurred around ~18.5 ka
in Jameson Land and around ~16.6 ka at Kap Brewster
(Håkansson et al., 2007, 2011; Fig. 1). At Clavering Island,
near Zackenberg, local glaciers recorded a deglaciation phase
starting from ~18 to 17 ka (Biette et al., 2020; Garcia-Oteyza
et al., 2022) (Fig. 7). In these eastern sectors of Greenland,

<figure><img src="image_8.png" /></figure>

**Figure 7.** Glacier moraine chronologies, glacier variations estimated from lake sediment record and regional climate conditions estimated from TraCE-21ka model results (Liu et al., 2009). Moraine records and lake sediments are shown from the north to the south of Greenland. (a) JJA temperature and DJF precipitation changes near Cape Farewell from the TraCE-21ka experiment; (b), (c), (f), glaciers change at Clavering (Biette et al., 2020), at Kulusuk (Biette et al., 2022) and at Narsarsuaq (Biette et al., 2022 (DV2C glacier green)) and Winsor et al., 2014 (Kiagtut sermia black line) and from the CHA glacier, respectively, (this study) expressed as relative probability density functions from CRE moraine chronologies; and (d), (e) glacier changes derived from lake sediments in the Kulusuk region (Balascio et al., 2015) and PC1 scores of Alakariqssoq showing fluctuations in glacier size at Narsarsuaq (Larocca et al., 2020a) regions, respectively. [Color figure can be viewed at wileyonlinelibrary.com]
minor readadvances during the Lateglacial have rarely been documented, as the occurrence of nuclide inheritance is often mentioned as being responsible for the large scatter in reported CRE ages, affecting glacier chronologies (Søndergaard et al., 2020; Skov et al., 2020; Garcia-Oteyza et al., 2022). Generally, thermal conditions at the base of the glacier are proposed to explain such inheritance, as cold-based glaciers do not erode rock surfaces deeply enough, therefore leading to the preservation of ¹⁰Be atoms accumulated from previous ice-free periods (Garcia-Oteyza et al., 2022).

From the end of the Lateglacial, mountain glacier fluctuations are, to some extent, better constrained by more frequent moraine and lake sediment proxy records. However, several questions remain unsolved. First, the Younger Dryas cold event (YD; 12.8–11.7 ka) documented in the NGRIP ice core record did not cause any visible glacier advance at the base of the CHA glacier (Fig. 7) (Larsen et al., 2016a). Climate models and new ice core reconstructions also show that the cooling during the YD may be overestimated by the δ¹⁸O in the ice core records (e.g., Ayache et al., 2018; Jomelli et al., 2022). This is particularly true in models for what concerns the Atlantic Meridional Overturning Circulation (AMOC) responses that have had a strong impact on the GrIS (Rainsley et al., 2018). Also, considering the fact that in response to changes in oceanic circulation, much of the cooling occurs in winter (Jackson et al., 2015; Swingedouw et al., 2009), it would have a minor impact on local glacier changes, at least in the south of Greenland (Buizert et al., 2014), that are mainly driven by ablation in summer.

The occurrence of a large glacier advance during the Early Holocene needs to be better constrained in this part of Greenland. Such an advance has been demonstrated in northern parts of Greenland by moraine dating (Lowell et al., 2013; Levy et al., 2016; O'Hara et al., 2017; Biette et al., 2022; Jomelli et al., 2022). In southern Greenland, however, this remains ambiguous, depending on the type of proxy record (moraine vs. lake sediment record). It can also be assumed that topographic and geomorphological factors (elevation, slope, aspect) may have a strong influence on the palaeo glacial extent and may explain why some divergences exist between proxy records. Moraine records do not support a large advance of the CHA glacier during the Early Holocene, that is, larger than those that occurred during the Late Holocene. If an Early Holocene advance of the CHA glacier occurred, its footprints may have been subsequently erased by more extensive glacier advances during the Late Holocene, or its signature may be obscured due to cosmogenic nuclide inheritance on the M5 moraine. In contrast, evidence for a substantial Early Holocene advance has been identified by Levy et al. (2020) at the base of a larger mountain glacier located northeast of the CHA glacier, closer to the east coast—a region that currently receives greater snowfall. However, such muted glacier advance during the Early Holocene has also been detected in other sectors of southernmost Greenland or in southeastern Greenland (Biette et al., 2022) (Fig. 7).

During the Mid Holocene, both moraine and lake sediment records suggest that mountain glaciers became very small or even completely melted away, in the context of the Holocene Thermal Maximum (cf. Renssen et al., 2012). Interestingly, the GrIS also experienced a significant retreat at different places (Winsor et al., 2015a, 2015b; Larsen et al., 2017; Young et al., 2021).

The Late Holocene glacier advance is a widely observed pattern in Europe but also in other mountain regions including Asia, Antarctica and Greenland (Kelly and Lowell, 2009; Solomina et al., 2015, 2016; Briner et al., 2016; Palacios et al., 2020; Jomelli et al., 2024a, 2024b). However, the timing of the maximum Late Holocene ice extent in southernmost

Greenland is again ambiguous, depending on the nature of the proxy record, and again may vary from glacier to glacier. The CHA glacier has recorded at least three advances, the oldest dated to ~4.4 ka. Field observations suggest that at least one advance may have occurred during the LIA. However, this advance was necessarily smaller in amplitude than the two advances that occurred at ~4.4 ka and ~3.8 ka. This general trend of a smaller CHA glacier advance during the LIA than those occurring during older Late Holocene periods is concordant with previous moraine records in this region and in northeastern Greenland (O'Hara et al., 2017; Biette et al., 2022; Jomelli et al., 2022) (Fig. 7).

In southwestern Greenland, renewed ice growth is recorded in the Badesø and Langesø lake catchments at ~3.5 ka (Larsen et al., 2017), and in the southeast at Kulusuk Lake, where renewed ice growth is recorded at ~4.1 ka, followed by several centennial-scale glacier advances between ~4.1 and 1.3 ka (Balascio et al., 2015). Conversely, differences between lake sediment records located near Qaqortoq (Larocca et al., 2020a) and the CHA glacier evolution can be observed. Larocca et al. (2020a) suggest that these glaciers reached their maximum Late Holocene extent during the second phase of the LIA (~0.2–0.1 ka), while it occurred earlier on the CHA glacier.

This Late Holocene long-term evolution of the CHA mountain glacier may differ from the changes in the GrIS. Indeed, CRE dating results from southwestern Greenland indicate that the minimum Holocene extent of the GrIS likely occurred after ~5 ka (Larsen et al., 2018; Schweinsberg et al., 2019; Larocca et al., 2020a, 2020b; Young et al., 2021) or during an event that occurred between 0.9 and 0.4 ka in the low-lying central part of the Qassimiut Lobe. At higher elevations, an earlier Neoglacial advance between 3.0 and 1.8 ka is recorded, followed by a retreating trend until the onset of the LIA (Kaplan et al., 2002; Larsen et al., 2011, 2015). Near Narsarsuaq, a larger-than-LIA glacier culmination is dated to 1.5 ka on the Kiagtût Sermia outlet glacier (Winsor et al., 2014).

## Temperature estimated from GlaRe reconstructions during the Lateglacial and Late Holocene periods

In this paper, we used the GlaRe package to reconstruct the CHA glacier and subsequently derive ELA changes from two distinct glacier areas constrained by moraine dating during the Lateglacial and the Late Holocene, respectively. Assuming that precipitation did not change over time relative to today, summer temperatures may have been 3.3°C and 1.7°C cooler, respectively. It is interesting to note that in the southernmost part of Greenland, Brooks et al. (2022) reported an ELA depression of 122 ± 64 m between the current period and the maximum advanced position of the glacier during the LIA, corresponding to a summer temperature change of -1.1°C ± 0.6°C, assuming no change in precipitation. Comparison of temperature estimates from the CHA glacier with those from Brooks et al. (2022) would suggest that about 0.5°C of warming occurred between the Late Holocene and the LIA. Such temperature changes during the LIA are consistent with those estimated in southeast Greenland, using the same AAR method for ELA calculation (Biette et al., 2022). A temperature 0.8°C cooler than present day with no change in precipitation can be assumed to explain the LIA advances at the base of the DV2L mountain glacier (Biette et al., 2022). In Disko Island (west of Greenland), Biette et al. (2018) used a positive degree-day (PDD) model constrained by the output of the regional climate MAR atmospheric model to estimate the climate conditions responsible for a glacier advance during the LIA at the base of Lyngmarksbræen glacier (Jomelli et al., 2016).
Biette et al. (2018) estimated that the most likely scenarios are based on air temperatures in the range of 1.3°C to 1.6°C cooler than today, considering a decrease of precipitation of ~10% over the same period. However, these estimates from CHA glacier ELA changes must be considered with caution for several reasons. In the examples of glaciers resting on a gently sloping bed at ‘position I’, and advancing across a flat area to ‘position II’, Nesje (1992) reported that the ELA depression is underestimated by an average of 80% compared to those examples with a constantly sloping subglacial bed. This situation corresponds to the Lateglacial period when the CHA glacier was a piedmont glacier. During the Late Holocene, the CHA glacier shows a more constant sloping subglacial bed, suggesting more robust estimates of temperature changes. However, even in such topographical conditions, temperature estimates suppose constant precipitation through time, a hypothesis that seems to be fragile, as shown by the TraCE-21ka regional climate changes over the last 20 ka (Fig. 7).

In addition, comparison of the temperature estimates from the GlaRe approach with regional climate conditions documented by TraCE-21ka is difficult for several reasons. ELA shifts derived from the GlaRe toolbox 3D reconstructions provide local temperature changes (and do not take into account changes in precipitation), while simulated TraCE-21ka climate conditions are given at a regional scale and do not cover the last decades. Nevertheless, temperature and precipitation changes estimated by TraCE-21ka show good consistency with the moraine record of the CHA glacier (see below).

## Possible climate forcings responsible for CHA evolution during the Lateglacial and Holocene

In an attempt to explain CHA glacier variations during the Lateglacial, we analyse results from TraCE-21ka simulations covering the entire deglaciation period. Temperature increased progressively between ~19 ka and 13 ka, interrupted by the abrupt and warm event at ~14 ka. Then, summer temperature progressively decreases from ~13 to ~12 ka. Winter and annual precipitation show comparable changes. Precipitation

started to increase from ~19 ka to the Late Holocene, interrupted by an event of stronger precipitation at ~14 ka and a period of drier conditions from ~13 to ~12 ka. While uncertainties of CHA CRE ages do not permit correlating these climate changes with each documented moraine, we can argue based on those simulations that the long-term glacier decline between 19 ka and 12 ka might have been partly driven by warmer conditions (Fig. 7). Ablation related to warmer summer temperature exceeded strong accumulation related to an excess in winter precipitation. In this respect, the changes in glaciers can be explained by climatic response to changes in external forcings.

To go one step further in the analysis of the role of external forcing, we use the attribution simulations available from NCAR. Those simulations are run with only one individual external forcing evolving among the set that has been included in the Full simulation, meaning greenhouse gases concentrations, melt water flux from land ice, ice sheet cover and height and orbital variations. In Fig. 8, the sum of the different simulations with only one forcing activated is very close to the simulation including all of them at once for the variables that we analyse. Thus, the climatic response to those forcing is relatively linear (compare the red and black curve to observe non-linearities in the response). The rapid events between ~15 k and ~12 ka are mainly driven by melt water release. From ~15 ka to ~10 ka, the summer warming trend over Greenland is driven by reduction of the ice sheets, the increase in greenhouse gas concentrations and the orbital forcing with very close amplitude. The same is true for the increase in precipitation.

Summer temperatures estimated from the TraCE-21ka model are slightly lower (<1°C) in the Early Holocene than in the Late Holocene but winter precipitation is also much lower (>20%) in the Early Holocene (the driest over the Holocene) than in the Late Holocene. Thus, drier conditions during the Early Holocene may explain why the CHA glacier did not expand that much compared to the rest of the Holocene. This relatively colder summer temperature in the Early Holocene compared to the Late is mainly related to the huge cooling impact due to the presence of remnant land ice at that time (Fig. 7), which has a strong impact on albedo notably. Between ~10 ka and

<figure><img src="image_9.png" /><figcaption>**Figure 8.** Temperature and precipitation anomalies (relative to the 0–15k period) over lat 60.15 and lon –44.52, calculated for the individual attribution experiments in TraCE-21ka simulations with a 300-year running average (a, b). Sum stands for sum of the individual forcings (orbital + meltwater flux + ice sheet height and land cover + greenhouse gas forcings). [Color figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>
~8 ka, Fig. 8 shows that the orbital forcing starts to act to reduce temperature, but this is overcome by the warming effect of ice sheet reduction, while there is a cooling event that can be related to melt water release around 8.2 ka. A similar evolution can be described for what concerns precipitation, with stronger changes around the 8.2 ka event. Lastly, between ~8 ka and ~0 ka (before the industrial era), there is a slight cooling trend driven by insolation that is slightly damped by the increase in greenhouse gas concentrations.

## Conclusions

In this paper, we investigated the Lateglacial and Holocene evolution of a small mountain glacier near Cape Farewell in southernmost Greenland. The evolution of the glacier was constrained by 43 ¹⁰Be CRE ages and six replicates with ²⁶Al/¹⁰Be measurements collected on eight moraines. We also estimated temperature changes responsible for the glacier extent during the Lateglacial and the Late Holocene from glacier reconstruction through the ELAs derived from the 3D reconstructions conducted through the GlaRe GIS toolbox and complementary with TraCE-21ka climate model output. Results show that the oldest moraine is dated to 18.4 ± 0.8 ka. Such a glacier advance would be associated with air temperature ~3.3°C cooler than today, assuming no change in precipitation, while output from the TraCE-21ka climate model suggests much drier conditions. Between ~18.0 and ~14.8 ka, the glacier experienced a significant retreat possibly due to a significant warming, interrupted by minor advances or standstills long enough to create at least three moraines. We did not evidence any moraines formed during the Younger Dryas, the Early Holocene and the Mid Holocene, assuming that the age of the moraines was not significantly affected by inheritance, while TraCE-21ka model results suggest cold but dry conditions at these times. To reconcile this, it might be suggested that precipitation had also played a crucial role. During the Late Holocene, at least three advances occurred at ~4.4 ka, 3.8 ka and probably during the LIA. ELA changes from glacier reconstruction suggest a climate 1.7°C cooler than today that can explain the largest Late Holocene glacier advance. The timing of the maximum Late Holocene glacier extent is similar to that of other mountain glaciers in southern Greenland but differs from that of land-terminating outlet glaciers in the GrIS and from reconstructions based on lake sediments, which are suggested to have occurred during the LIA.

*Acknowledgements.* ASTER AMS, national facility (CEREGE, Aix en Provence), is supported by the INSU/CNRS and IRD and member of AIX MARSEILLE PLATFORMS and REGEF networks. The field work was conducted with the help of IPEV and founded by the 1249 Deglac project. Special thanks are due to L. Larocca, who gave us PC1 scores at Alakariqssoq. We are grateful to the ANTALP (Antarctic, Alpine Environments; 2021-SGR-00269) research group funded by the Generalitat de Catalunya.

## Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

## Supporting information

Additional supporting information may be found in the online version of this article at the publisher's web-site.

**Table S1.** Chemistry data for the sample's preparation.

**Table S2.** Chemistry data for the blank's preparation.

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