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Record W4296836094 · doi:10.5194/epsc2022-442

The record of warm-based glaciation on ancient Mars

2022· preprint· en· W4296836094 on OpenAlexaboutno aff
Anna Grau Galofre, K. X. Whipple, P. R. Christensen, Susan J. Conway

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsAdenylate kinaseChemistryBiochemistryEnzyme

Abstract

fetched live from OpenAlex

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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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.241
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2022
Admission routes1
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