The Martian magnetosphere is a product of the interaction of Mars with the interplanetary magnetic field and the supersonic solar wind. The location of the bow shock has been previously modeled as conic sections using data from spacecraft such as Phobos 2, Mars Global Surveyor, and Mars Express. The Mars Atmosphere and Volatile EvolutioN (MAVEN) mission spacecraft arrived in orbit about Mars in November 2014 resulting in thousands of crossings to date. We identify over 1,000 bow shock crossings. We model the bow shock as a three-dimensional surface accommodating asymmetry caused by crustal magnetic fields. By separating MAVEN's bow shock encounters based on solar condition, we also investigate the variability of the surface. We find that the shock surface varies in shape and location in response to changes in the solar radiation, the solar wind Mach number, dynamic pressure of the solar wind, and the relative local time location of the strong crustal magnetic fields (i.e., whether they are on the dayside or on the nightside).Plain Language Summary A shock wave forms when the supersonic solar wind flows around objects in the Solar System. We studied the shape of this bow shock at Mars; the obstacle to the solar wind at Mars is the upper atmosphere and the patches of the crust that have localized strong magnetic fields. Previous studies have shown that the Martian bow shock can change due to changing solar wind or the location of crustal magnetic fields. Two-dimensional equations have been used to create mathematical models of the Martian bow shock, but they have implicit assumptions about the symmetry of the surface. Using over 2 years of observations from Mars Atmosphere and Volatile Evolution Mission, we have used a general surface equation to model the Martian bow shock fully in three-dimensions, which is able to represent the asymmetric shape of the surface. We find that while changes in the solar wind change the size of the Martian bow shock, the location of the crustal fields are most important factor in producing the asymmetric shape of the shock. Investigating how the bow shock varies under different solar wind conditions can be important toward understanding of how the Sun impacts the Martian magnetosphere that can drive important processes, such as atmospheric.

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The Martian magnetotail is a complex regime through which atmospheric particles are lost to space. Our current understanding of Mars' tail continues to develop with the comprehensive particle and field data collected by Mars Atmosphere and Volatile EvolutioN (MAVEN). In this work, we identify periods when MAVEN encounters multiple current sheet crossings through a single tail traversal in order to understand tail dynamics. We apply an analysis technique that has been developed and validated by using multipoint measurements in order to separate the spatial and temporal properties associated with current sheet flapping. Events are classified into periods of steady flapping, due to a global motion of the current sheet, and kink‐like flapping, resulting from localized wave propagation along the tail current sheet. Out of 106 periods during which multiple current sheet crossings were observed, 20 were due to steady flapping and 10 from kink‐like flapping. A majority of the kink‐like events resulted from waves propagating in the opposite direction of the solar wind convection electric field, regardless of their location in the tail, unlike at Earth and Venus. This finding suggests that possible magnetosphere energy sources, whereby plasma is accelerated and removed from the Martian environment, are not located in the central magnetotail; rather, these waves may be driven by a source located at the tail flank based on the direction of the solar wind electric field. Therefore, by identifying potential sources of impulsive energy release in the tail, we may better understand mechanisms that drive atmospheric loss at Mars.

Abstract. The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, we carried out intensive field studies over multiple years for two small (2017–2019; ∼ 2.5 km2) sub-Arctic study sites located on the Seward Peninsula of Alaska. Using an intensive suite of field observations (> 22 000 data points), we developed simple models of the spatial distribution of snow water equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based on greenness (normalized different vegetation index, NDVI), and a simple metric for approximating winds. The most successful model was random forest, using both study sites and all years, which was able to accurately capture the complexity and variability of snow characteristics across the sites. Approximately 86 % of the SWE distribution could be accounted for, on average, by the random forest model at the study sites. Factors that impacted year-to-year snow distribution included NDVI, elevation, and a metric to represent coarse microtopography (topographic position index, TPI), while slope, wind, and fine microtopography factors were less important. The characterization of the SWE spatial distribution patterns will be used to validate and improve snow distribution modeling in the Department of Energy's Earth system model and for improved understanding of hydrology, topography, and vegetation dynamics in the sub-Arctic and Arctic regions of the globe.

Abstract. Thawing permafrost can alter topography, ecosystems, and sediment and carbon fluxes, but predicting landscape evolution of permafrost-influenced watersheds in response to warming and/or hydrological changes remains an unsolved challenge. Sediment flux and slope instability in sloping saturated soils have been commonly predicted from topographic metrics (e.g., slope, drainage area). In addition to topographic factors, cohesion imparted by soil and vegetation and melting ground ice may also control spatial trends in slope stability, but the distribution of ground ice is poorly constrained and hard to predict. To address whether slope stability and surface displacements follow topographic-based predictions, we document recent drivers of permafrost sediment flux present on a landscape in western Alaska that include creep, solifluction, gullying, and catastrophic hillslope failures ranging in size from a few meters to tens of meters, and we find evidence of rapid and substantial landscape change on an annual timescale. We quantify the timing and rate of surface movements using a multi-pronged, multi-scalar dataset including aerial surveys, interannual GPS surveys, synthetic aperture radar interferometry (InSAR), and climate data. Despite clear visual evidence of downslope soil transport of solifluction lobes, we find that the interannual downslope surface displacement of these features does not outpace downslope displacement of soil in locations where lobes are absent (downslope movement means: 7 cm yr−1 for lobes over 2 years vs. 10 cm yr−1 in landscape positions without lobes over 1 year). Annual displacements do not appear related to slope, drainage area, or modeled total solar radiation but are likely related to soil thickness, and volumetric sediment fluxes are high compared to temperate landscapes of comparable bedrock lithology. Time series of InSAR displacements show accelerated movement in late summer, associated with intense rainfall and/or deep thaw. While mapped slope failures do cluster at slope–area thresholds, a simple slope stability model driven with hydraulic conductivities representative of throughflow in mineral and organic soil drastically overpredicts the occurrence of slope failures. This mismatch implies permafrost hillslopes have unaccounted-for cohesion and/or throughflow pathways, perhaps modulated by vegetation, which stabilize slopes against high rainfall. Our results highlight the breadth and complexity of soil transport processes in Arctic landscapes and demonstrate the utility of using a range of synergistic data collection methods to observe multiple scales of landscape change, which can aid in predicting periglacial landscape evolution.