The record of warm-based glaciation on ancient Mars
Notice bibliographique
Résumé
THE RECORD OF WARM-BASED GLACIATION ON ANCIENT MARS. A. Grau Galofre.1,2, K. X. Whipple2, P. R. Christensen2, S. J. Conway1 1Laboratoire de Planétologie et Géosciences CNRS UMR 6112, Nantes Université, France (anna.graugalofre@univ-nantes.fr) 2School of Earth and Space Exploration, Arizona State University, Tempe, AZ, US Introduction: The missing evidence for large-scale glacial scouring landscapes on Mars has led to the belief that past martian glaciations were frozen to the ground [1,2]. Indeed, whereas warm-based ice masses (with presence of basal meltwater), produce some of the most striking erosional patterns on Earth (Figure 1, panels 2 and 3), these same morphologies are notoriously rare on Mars [1,2]. Two issues arise with this perspective. First, Mars’ climate in the Noachian-Hesperian (~3.8-3.5 Ga) allowed for surface liquid water [3,4]. The transition from this early climate to the current day global cryosphere with no presence of basal meltwater under ice masses poses a problematic transient [1]. Second, the presence of eskers in the Dorsa Argentea formation (DAf) [5,6,7], and in the mid-latitudes [8] shows that basal melting occurred in spite of the lack of glacial sliding. Our work hypothesizes that the fingerprints of Martian warm-based glaciation are the remnants of the ice sheet drainage system (channel and eskers), instead of the scoured regions associated with terrestrial Quaternary glaciation (Figure 1). Figure 1. Fingerprints of terrestrial warm-based glaciation. (1) Subglacial channels (Nunavut). (2) Mega-scale lineations (Québec). (2) Scouring marks and striae (Finland). (4) Esker (66.1N, 104.50W). To make progress, we use models of terrestrial glacial hydrology to interrogate how the Martian surface gravity modifies glacial drainage, ice sliding velocity, and glacial erosion rates. Taking as reference the geometry of the ancient southern circumpolar ice sheet (ASCIS) associated with the DAf [6], we model the behavior of identical ice sheets on Mars and Earth. We show that, whereas Earth’s largely inefficient glacial drainage produces glacially scoured landscapes, the lower gravity favors the formation of subglacial channelized drainage on Mars. The lack of martian glacial sliding landforms, including grooves, drumlins, lineations, etc., could then be explained. Terrestrial analogue landscapes in the Canadian Arctic (Figure 1, panel 1) further showcase the role of glacial hydrology in landscape evolution. The presence of subglacial meltwater even after the early Mars period has important implications for the history of climate, hydrology, and presence of habitable environments. Methods: We use the terrestrial glacial hydrology framework [9,10,11] to interrogate subglacial drainage on Earth and Mars (figure 2), using an ice sheet parametrized after the ASCIS [6]. We then evaluate glacial sliding rates on Mars and Earth, for identical ice sheet geometries, by coupling glacial drainage with a model of glacial sliding [9,10]. Fig. 2. Glacial drainage scenarios. Upper a,b,c panels show subglacial channels and efficient basal drainage, and their landscape expression (d). Bottom a,b,c panels show inefficient, distributed drainage by cavities, and their landscape expression (d). When no efficient subglacial drainage exists, basal water accumulates in cavities where water pressure builds up, decreasing basal friction and accelerating ice (Figure 2) [9]. Glacial sliding then leads to highly directional, scoured landscapes (Figure 1). The opposite occurs when basal meltwater drains efficiently through subglacial channel networks [10]. Water pressure drops, basal friction increases, and ice sliding slows down. The fingerprints of channelized drainage are incised subglacial channels intertwined with depositional landforms such as eskers [12]. The feedback that defines sliding velocity as a function of effective pressure (ice overburden minus basal water pressure) and subglacial drainage efficiency (cavities/ channels) is controlled by a competition between sliding velocity and drainage system evolution [9,10,11]. Results: Figure 3 shows our results [13]. Comparing Earth and Mars curves, we notice that sliding rates are a factor ~20-90 slower for an ice sheet of the same characteristics on Mars, when the effects of glacial hydrology and drainage are considered. We also find that whereas Earth’s gravity favors less efficient drainage, subglacial drainage on Mars is dominated by channels to much larger subglacial conduit cross-section (compare arrows). Figure 3: Results showing glacial sliding rates on Earth (blue line) and Mars (red line) vs. subglacial drainage cross-section. Cv arrows indicate the point where cavities open, Ch where channels open. Discussion: Glacial erosion scales with ice sliding velocity to a power 1-2, so that erosion rates on Mars could be up to ~102-104 smaller than Earth according to our results. Erosion under warm-based ice masses would thus occur in channels on Mars, leading to glacial landscapes similar to those of the high Arctic (Figure 1) [12,13,14]. Conclusions: To understand the lack of martian warm-based glacial landforms we use the terrestrial glacial hydrology theoretical framework. We show that martian glacial sliding is comparatively inhibited (20-90X slower), and that glacial drainage should be dominated by channels. Hence, we infer that the fingerprints of warm-based glaciation are different between Mars and Earth, with the former being characterized by subglacial channels and eskers and the later by areal scouring by glacial sliding. This work supports the possibility that some valley networks may have formed beneath ice sheets [14], explaining the lack of warm-based glacial erosion in the Martian highlands [15] and in the Dorsa Argentea formation [5,6,7]. References: [1] Wordsworth R. (2016) Ann. Rev. EPS 44, 381-408. [2] Kargel et al. (1995) JGR : Planets 100(E3), 5351-5368. [3] Carr M. (1995) JGR: Planets, 100(E4) 7479-7507. [4] Hynek B. et al. (2010) JGR: Planets, 115(E9). [5] Head J.W. and Pratt S. (2001) JGR: Planets, 106(E6), 12275-12299. [6] Fastook et al. (2012) Icarus, 219(1), 25-40. [7] Butcher, F.E.G. et al. (2016) Icarus, 275, 65-84. [8] Butcher et al. (2017) JGR: Planets, 122(12). 2445-2468. [9] Schoof, C. (2005) PNAS A. 461(2055), 609-627. [10] Schoof, C. (2010) Nature, 468(7325), 803. [11] Cuffey, K. M., and Paterson, W. S. B. (2010). The physics of glaciers. Academic Press. [12] Grau Galofre, A. et al. (2018), TC, 12(4), 1461. [13] Grau Galofre et al., In review. [14] Grau Galofre et al. (2020) Nat. Geosci. 13(10), 663-668. [15] Fastook, J. L., and Head, J. W. (2015). PSS, 106, 82-98.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».