Scalloped Cliff Formations and Association with Radar Reflectors, a Radar - Imagery Integrated Approach
Bibliographic record
Abstract
The North Polar Layered Deposits (NPLD) of Mars preserve a valuable record of the planet’s climatic history through stacked layers of water ice and dust [1]. These layers are exposed at the surface and can be observed in the optical imagery [2], while subsurface stratigraphy is revealed through radar sounding data [3]. Our study aims to integrate these datasets, to gain a more complete understanding of the geomorphology of NPLD.We identify and catalog 98 Scalloped Cliffs (SC) across the NPLD using optical imagery (Fig.1), exposed by the troughs using the High-Resolution Imaging Experiment (HiRISE) and Context Camera (CTX) imagery. We use a three-dimensional Shallow Radar (SHARAD) dataset [4] to understand the subsurface stratigraphy of the NPLD. After mapping the scalloped cliffs in JMARS, they are converted as shapefiles to a SeisWare format for comparison with a 3D SHARAD data volume for integrating the topography features with the subsurface stratigraphy. We compared the elevation of the outcropping reflections to exposures at the same elevations and found unique surface morphology of cliffs that immediately overlie angular unconformities.A SC is a geomorphological feature formed by the protrusion of layers tens of meters tall along several kilometers with a unique wavy appearance. SCs may be isolated or appear in multiples at the same NPLD outcrop and most are associated with identifiable stratigraphic unconformities. The spatial distribution of the identified cliff's location suggests that the scalloped cliffs are more concentrated in the Gemini Scopuli region of Planum Boreum, Mars. We observe that, in some locations, SHARAD reflectors of NPLD reach the surface coinciding with a SC location (Fig. 2), providing an opportunity to investigate if any stratigraphic anomalies like lag deposits can make a bright reflection . Some bright reflections may indicate the presence of relatively erodible beds, possibly at lag deposits, between resistant units [5].In this study, we examine radar profiles corresponding to the cliffs to assess whether these cliffs coincide in x,y,z with bright subsurface reflectors, and/or a stratigraphic angular unconformity. Some cliffs are not associated with any identifiable unconformities in the imagery, possibly because they manifest as disconformities at the surface, so we examine in the radar data to investigate any subsurface unconformities at the same stratigraphic level. Our technique is to identify the elevation of SCs from MOLA data and unconformities or bright reflectors in SHARAD data with the intent of testing the hypothesis that there is a connection between the exposed bright reflector in the NPLD outcrop and the unconformities. Most SCs are associated with the reflector 15 (R15, counting from the top) located in the upper NPLD and previously identified as an unconformity and reveals a major climatic shift [6]. A few cliffs are associated with R40, another unconformity in the lower NPLD. Some cliffs are found to be associated with R35, it could be a simple rich deposition layer. Alternate deposition and erosion can lead to unconformities and unconformities can make a lag. These associations between scallop cliffs, unconformity, and bright radar reflectors give strong evidence that the reflectors in the radar are caused by lag deposits. It is not a coincidence that these correspond in position to SHARAD-observed reflections. Our analysis highlights a consistent spatial association between scalloped cliff locations, angular unconformities and strong subsurface reflections, providing a better insight into the erosional and depositional history of the NPLD and is consistent with the findings of Smith et al 2025 [6].Fig. 1: Optical imagery showing a scalloped cliff directly associated with an exposed outcrop in the NPLD. Location and Image details are highlighted.Fig. 2: The radar profile shows the scalloped cliff (Fig. 1) associated with a bright reflector (R35) within the exposed outcrop of the NPLD.References: [1] Phillips, R.J., Zuber, M.T., Smrekar, S.E., Mellon, M.T., Head, J.W., Tanaka, K.L., Putzig, N.E., Milkovich, S.M., Campbell, B.A., Plaut, J.J., others, 2008. Mars north polar deposits: Stratigraphy, age, and geodynamical response. Science 320, 1182.[2] Smith, I.B., Holt, J.W., 2015. Spiral trough diversity on the north pole of Mars, as seen by Shallow Radar (SHARAD). J. Geophys. Res. Planets 120, 2014JE004720. https://doi.org/10.1002/2014JE004720[3] Smith, I.B., Putzig, N.E., Holt, J.W., Phillips, R.J., 2016. An ice age recorded in the polar deposits of Mars. Science 352, 1075–1078. https://doi.org/10.1126/science.aad6968[4] Foss, Frederick J., et al. “3D Imaging of Mars' Polar Ice Caps Using Orbital Radar Data.” The Leading Edge, vol. 36, no. 1, 2017, pp. 43–57., https://doi.org/10.1190/tle36010043.1.[5] Lalich, D. E., et al. “Radar Reflectivity as a Proxy for the Dust Content of Individual Layers in the Martian North Polar Layered Deposits.” Journal of Geophysical Research: Planets, vol. 124, no. 7, 2019, pp. 1690–1703., https://doi.org/10.1029/2018je005787.[6] Smith, I. B., et al. (2025), A Major Climatic Change of the North Polar Layered Deposits of Mars, LPSC LVI, abst 1452.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".