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Data for: Martian Sand Dunes as Natural Ice Sensors: How to Identify Ice Composition from Dune-ice Morphology

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Zenodo2026-02-20 更新2026-05-26 收录
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Manuscript Abstract: The seasonal exchange of martian volatiles between the atmosphere and surface drives the formation and modification of gullies, spiders, and other surface features on Mars. Studies of such seasonal ice-driven activity rely on correct interpretations of ice composition and coverage. However, datasets that discriminate ice composition often have coarse resolution or limited spatial coverage. In this work, we investigate whether specific dune-ice morphologies reflect different ice compositions and thus could be used to interpret the meter-scale ice environment over the dunes. Using HiRISE images collected over sand dunes in the northern mid-latitudes (30-65° N), we grouped observations by patterns in dune-ice morphology and interpreted the ice composition of each group. Interpretations of ice composition were then compared to the ice compositions derived from coincident thermal and spectral observations. We found that dunes with both a high surface brightness and sublimation spots or cracks corresponded to CO2 ice whereas dunes that exhibit increased surface brightness without sublimation spots or cracks corresponded to H2O ice. These interpretations are corroborated by prior seasonal ice cap mapping results, surface temperature observations, and by the position of spectrally derived seasonal ice cap edges, despite orders-of-magnitude differences in dataset resolution. This work provides a new opportunity to probe the martian seasonal H2O cycle while also improving landform-scale ice composition interpretations for studies of surface features thought to form from ice-regolith interactions. Dataset: This dataset provides a record of the HiRISE images used to identify dune-ice morphology and additional information on the expected ice composition obtained from analysis. A README file is provided to explain the contents of the dataset. For any additional information on our methods and results, please see the published manuscript.

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Zenodo
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2026-02-20
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