Martian dunes indicative of wind regime shift in line with end of ice age

Orbital observations suggest that Mars underwent a recent 'ice age' (roughly 0.4-2.1 million years ago), during which a latitude-dependent ice-dust mantle (LDM)1,2 was emplaced. A subsequent decrease in obliquity amplitude resulted in the emergence of an 'interglacial period'1,3 during which the lowermost latitude LDM ice4-6 was etched and removed, returning it to the polar cap. These observations are consistent with polar cap stratigraphy1,7, but lower- to mid-latitude in situ surface observations in support of a glacial-interglacial transition that can be reconciled with mesoscale and global atmospheric circulation models8 is lacking. Here we present a suite of measurements obtained by the Zhurong rover during its traverse across the southern LDM region in Utopia Planitia, Mars. We find evidence for a stratigraphic sequence involving initial barchan dune formation, indicative of north-easterly winds, cementation of dune sediments, followed by their erosion by north-westerly winds, eroding the barchan dunes and producing distinctive longitudinal dunes, with the transition in wind regime consistent with the end of the ice age. The results are compatible with the Martian polar stratigraphic record and will help improve our understanding of the ancient climate history of Mars9.

Squeezing Data from a Rock: Machine Learning for Martian Science

Data analysis methods have scarcely kept pace with the rapid increase in Earth observations, spurring the development of novel algorithms, storage methods, and computational techniques. For scientists interested in Mars, the problem is always the same: there is simultaneously never enough of the right data and an overwhelming amount of data in total. Finding sufficient data needles in a haystack to test a hypothesis requires hours of manual data screening, and more needles and hay are added constantly. To date, the vast majority of Martian research has been focused on either one-off local/regional studies or on hugely time-consuming manual global studies. Machine learning in its numerous forms can be helpful for future such work. Machine learning has the potential to help map and classify a large variety of both features and properties on the surface of Mars and to aid in the planning and execution of future missions. Here, we outline the current extent of machine learning as applied to Mars, summarize why machine learning should be an important tool for planetary geomorphology in particular, and suggest numerous research avenues and funding priorities for future efforts. We conclude that: (1) moving toward methods that require less human input (i.e., self- or semi-supervised) is an important paradigm shift for Martian applications, (2) new robust methods using generative adversarial networks to generate synthetic high-resolution digital terrain models represent an exciting new avenue for Martian geomorphologists, (3) more effort and money must be directed toward developing standardized datasets and benchmark tests, and (4) the community needs a large-scale, generalized, and programmatically accessible geographic information system (GIS).

Widespread Megaripple Activity Across the North Polar Ergs of Mars

The most expansive dune fields on Mars surround the northern polar cap where various aeolian bedform classes are modified by wind and ice. The morphology and dynamics of these ripples, intermediate-scale bedforms (termed megaripples and Transverse Aeolian Ridges [TARs]), and sand dunes reflect information regarding regional boundary conditions. We found that populations of polar megaripples and larger TARs are distinct in terms of their morphology, spatial distribution, and mobility. Whereas regionally restricted TARs appeared degraded and static in long-baseline observations, polar megaripples were not only widespread but migrating at relatively high rates (0.13 ± 0.03 m/Earth year) and possibly more active than other regions on Mars. This high level of activity is somewhat surprising since there is limited seasonality for aeolian transport due to surficial frost and ice during the latter half of the martian year. A comprehensive analysis of an Olympia Cavi dune field estimated that the advancement of megaripples, ripples, and dunes avalanches accounted for ~1%, ~10%, and ~100%, respectively, of the total aeolian system's sand fluxes. This included dark-toned ripples that migrated the average equivalent of 9.6 ± 6 m/yr over just 22 days in northern summer-unprecedented rates for Mars. While bedform transport rates are some of the highest yet reported on Mars, the sand flux contribution between the different bedforms does not substantially vary from equatorial sites with lower rates. Seasonal off-cap sublimation winds and summer-time polar storms are attributed as the cause for the elevated activity, rather than cryospheric processes.

Multistage Evolution in Transverse Aeolian Ridges

Transverse aeolian ridges (TARs) are poorly understood relict aeolian Martian surface features. Processes that create TARs are not well-constrained, and understanding their formation is complicated since they appear to share some features of ripples, megaripples, and dunes. While some evidence of multi-stage TAR formation has been documented in Nirgal Vallis, here we present additional evidence for this process at nine locations on Mars using cratering superposition between different ridge morphologies. Most occurrences of multistage evolution will not preserve the precise series of cratering and formation events documented here, which potentially means that this formative process may have been more common than even these new widespread observations suggest. This formative process can help determine the relative similarity of TARs to ripples, megaripples and dunes. Based on our observations, we conclude that primary TAR forms are most like megaripples, and that subsequent ridges formed like aqueous ripple spurs.

PlaNet: A Neural Network for Detecting Transverse Aeolian Ridges on Mars

Transverse aeolian ridges (TARs) are unusual bedforms on the surface of Mars. TARs are common but sparse on Mars; TAR fields are small, rarely continuous, and scattered, making manual mapping impractical. There have been many efforts to automatically classify the Martian surface, but they have never explicitly located TARs successfully. Here, we present a simple adaptation of the off-the-shelf neural network RetinaNet that is designed to identify the presence of TARs at a 50-m scale. Once trained, the network was able to identify TARs with high precision (92.9%). Our model also shows promising results for applications to other surficial features like ripples and polygonal terrain. In the future, we hope to apply this model more broadly and generate a large database of TAR distributions on Mars.

Semiautomated Identification and Characterization of Dunes at Hargraves Crater, Mars

The Mars Global Digital Dune Database (MGD3) contains information on Martian dune fields and prepared manually from the Thermal Emission Imaging System (THEMIS; 100 m/pixel) images. Although the MGD3 outlines dune fields, it overlooks the recognition of smaller dune forms. This paper aims to identify individual dunes from a semiautomated object‐based image analysis technique and characterize dune materials at Hargraves crater, Mars. MGD3 would benefit to be updated for an improved understanding of the Martian surface and its atmospheric mechanisms at a local scale. An object‐based image analysis technique was applied here to the Context Camera (CTX; 6 m/pixel) data set to extract dune data in a more efficient, reliable, and accurate fashion. This study is a test case in validating a remote sensing method that has wide applicability to the entire Martian surface resulting in an update to the dune database at a higher spatial resolution—providing a better understanding of surface and atmospheric behavior of Mars at the local scale. We also explored the wind flow and dune stability—presenting an insight into the dune modification mechanism—within the crater. The prevailing wind inside the crater flows to the west‐northwest. The dunes are labeled as active (stability index of 2) and do not appear to have been influenced by subsurface water ice or volatiles. We emphasize that the technique used here has a wide prospect in temporal monitoring of dune sediment flux, dune migration or erosion rates, improving near‐surface airflow modeling, and dune stability analysis.

Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity

Various natural patterns-such as terrestrial sand dune ripples, lamellae in vertebrate bones, growth increments in fish scales and corals, aortas and lamellar corpuscles in humans and animals-comprise layers of different thicknesses and lengths. Microstructures in manmade materials-such as alloys, perlite steels, polymers, ceramics, and ripples induced by laser on the surface of graphen-also exhibit layered structures. These layered patterns form a record of internal and external factors regulating pattern formation in their various systems, making it potentially possible to recognize and identify in their incremental sequences trends, periodicities, and events in the formation history of these systems. The morphology of layered systems plays a vital role in developing new materials and in biomimetic research. The structures and sizes of these two-dimensional (2D) patterns are characteristically anisotropic: That is, the number of layers and their absolute thicknesses vary significantly in different directions. The present work develops a method to quantify the morphological characteristics of 2D layered patterns that accounts for anisotropy in the object of study. To reach this goal, we use Boolean functions and an N-partite graph to formalize layer structure and thickness across a 2D plane and to construct charts of (1) "layer thickness vs. layer number" and (2) "layer area vs. layer number." We present a parameter disorder of layer structure (DStr) to describe the deviation of a study object's anisotropic structure from an isotropic analog and illustrate that charts and DStr could be used as local and global morphological characteristics describing various layered systems such as images of, for example, geological, atmospheric, medical, materials, forensic, plants, and animals. Suggested future experiments could lead to new insights into layered pattern formation.

Trace Evidence from Mars’ Past: Fingerprinting Transverse Aeolian Ridges

Linear dunes and human fingerprints share many characteristics. Both have ridges, valleys, and defects (minutiae) in the form of bifurcations and termination of ridgeline features. For dunes, determining how defects vary across linear and transverse dunefields is critical to understanding the physics of their formative processes and the physical forcing mechanisms that produce dunefields. Unfortunately, manual extraction of defect locations and higher order characteristics (type, orientation, and quality) from remotely sensed imagery is both time-consuming and inconsistent. This problem is further exacerbated when, in the case of imagery from sensors in orbit around Mars, we are unable to field check interpretations. In this research, we apply a novel technique for extracting defects from multiple imagery sources utilizing a robust and well-documented fingerprint minutiae detection and extraction software (MINDTCT: MINutiae DecTeCTion) developed by the National Institute of Standards and Technology (NIST). We apply our ‘fingerprinting’ approach to Transverse Aeolian Ridges (TARs), relict aeolian features commonly seen on the surface of Mars, whose depositional and formative processes are poorly understood. Our algorithmic approach demonstrates that automating the rapid extraction of defects from orbitally-derived high-resolution imagery of Mars is feasible and produces maps that allow the quantification and analysis of these features.

Distribution and Morphologies of Transverse Aeolian Ridges in ExoMars 2020 Rover Landing Site

Aeolian processes are believed to play a major role in the landscape evolution of Mars. Investigations on Martian aeolian landforms such as ripples, transverse aeolian ridges (TARs), and dunes, and aeolian sediment flux measurements are important to enhance our understanding of past and present wind regimes, the ongoing dust cycle, landscape evolution, and geochemistry. These aeolian bedforms are often comprised of loose sand and sharply undulating topography and thus pose a threat to mobility and maneuvers of Mars rovers. Here we present a first-hand account of the distribution, morphologies, and morphometrics of TARs in Oxia Planum, the recently selected ExoMars 2020 Rover landing site. The gridded mapping was performed for contiguous stretches of TARs within all the landing ellipses using 57 sub-meter high resolution imaging science experiment (HiRISE) scenes. We also provide the morphological descriptions for all types of TARs present within the landing ellipses. We use HiRISE digital terrain models (DTMs) along with the images to derive morphometric information for TARs in Oxia Planum. In general, the average areal TAR coverage was found to be 5.4% (±4.9% standard deviation), increasing from west to east within the landing ellipses. We report the average TAR morphometrics in the form of crest–ridge width (131.1 ± 106.2 m), down-wind TAR length (17.6 ± 10.1 m), wavelength (37.3 ± 11.6 m), plan view aspect ratio (7.1 ± 2.3), inter-bedform spacing (2.1 ± 1.1), slope (10.6° ± 6.1°), predominant orientations (NE-SW and E-W), and height (1.2 ± 0.8 m). While simple TARs are predominant, we report other TAR morphologies such as forked TAR, wavy TAR with associated smaller secondary ripples, barchan-like TAR, networked TAR, and mini-TARs from the region. Our results can help in planning the rover traverses in terms of both safe passage and scientific returns favoring aeolian research, particularly improving our understanding of TARs.

Quantification of layered patterns with structural anisotropy: a comparison of biological and geological systems

Large-scale patterns evident from satellite images of aeolian landforms on Earth and other planets; those of intermediate scale in marine and terrestrial sand ripples and sediment profiles; and small-scale patterns such as lamellae in the bones of vertebrates and annuli in fish scales are each represented by layers of different thicknesses and lengths. Layered patterns are important because they form a record of the state of internal and external factors that regulate pattern formation in these geological and biological systems. It is therefore potentially possible to recognize trends, periodicities, and events in the history of the formation of these systems among the incremental sequences. Though the structures and sizes of these 2-D patterns are typically scale-free, they are also characteristically anisotropic; that is, the number of layers and their absolute thicknesses vary significantly during formation. The aim of the present work is to quantify the structure of layered patterns and to reveal similarities and differences in the processing and interpretation of layered landforms and biological systems. To reach this goal we used N-partite graph and Boolean functions to quantify the structure of layers and plot charts for "layer thickness vs. layer number" and "layer area vs. layer number". These charts serve as a source of information about events in the history of formation of layered systems. The concept of synchronization of layer formation across a 2-D plane is introduced to develop the procedure for plotting "layer thickness vs. layer number" and "layer area vs. layer number", which takes into account the structural anisotropy of layered patterns and increase signal-to-noise ratio in charts. Examples include landforms on Mars and Earth and incremental layers in human and iguana bones.

The physics of wind-blown sand and dust

The transport of sand and dust by wind is a potent erosional force, creates sand dunes and ripples, and loads the atmosphere with suspended dust aerosols. This paper presents an extensive review of the physics of wind-blown sand and dust on Earth and Mars. Specifically, we review the physics of aeolian saltation, the formation and development of sand dunes and ripples, the physics of dust aerosol emission, the weather phenomena that trigger dust storms, and the lifting of dust by dust devils and other small-scale vortices. We also discuss the physics of wind-blown sand and dune formation on Venus and Titan.

Bimolecular rate constant and product branching ratio measurements for the reaction of C2H with ethene and propene at 79 K

The reactions of the ethynyl radical (C(2)H) with ethene (C(2)H(4)) and propene (C(3)H(6)) are studied under low temperature conditions (79 K) in a pulsed Laval nozzle apparatus. Ethynyl radicals are formed by 193 nm photolysis of acetylene (C(2)H(2)) and the reactions are studied in nitrogen as a carrier gas. Reaction products are sampled and subsequently photoionized by the tunable vacuum ultraviolet radiation of the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory. The product ions are detected mass selectively and time-resolved by a quadrupole mass spectrometer. Bimolecular rate coefficients are determined under pseudo-first-order conditions, yielding values in good agreement with previous measurements. Photoionization spectra are measured by scanning the ALS photon energy while detecting the ionized reaction products. Analysis of the photoionization spectra yields-for the first time-low temperature isomer resolved product branching ratios. The reaction between C(2)H and ethene is found to proceed by H-loss and yields 100% vinylacetylene. The reaction between C(2)H and propene results in (85 ± 10)% C(4)H(4) (m/z = 52) via CH(3)-loss and (15 ± 10)% C(5)H(6) (m/z = 66) by H-loss. The C(4)H(4) channel is found to consist of 100% vinylacetylene. For the C(5)H(6) channel, analysis of the photoionization spectrum reveals that (62 ± 16)% is in the form of 4-penten-1-yne, (27 ± 8)% is in the form of cis- and trans-3-penten-1-yne and (11 ± 10)% is in the form of 2-methyl-1-buten-3-yne.