The presence of sand dunes on planetary surfaces can be indicative of past and present wind regimes that have sculpted cohesionless material into organized landforms. These landforms provide a unique insight into the evolutionary dynamics of planetary surfaces and are a window into past climatic behaviour. Reconstructing patterns of regional wind behaviour from the orientation of aeolian bedforms has had limited success due to, for example, model limitations and the, as yet, unstudied role that the inheritance of bedform morphology from previous climatic conditions may play. Unlike dunes on Earth, we still do not fully understand airflow dynamics over and around Martian dunes at relevant scales. If bedforms (for example, dunes or ripple movement on dunes) are to be used as a wind direction proxy, then a better understanding of the controls on ripple migration is needed. Here we use three-dimensional (3D) computational fluid dynamic modelling to demonstrate that wind flow dynamics over and around large-scale dune forms are complex on Mars. Model output in this study was validated using ripple displacements measured from High Resolution Imaging Science Experiment (HiRISE) data. This work advocates the use of detailed, high-resolution surface modelling of winds before attempting to understand regional wind patterns from contemporary bedforms on Mars. In the absence of a network of in situ instrumentation to measure winds on Mars, our understanding of airflow over the surface of the planet has relied on large-scale, for example, ref. 1, and meso-scale, for example, ref. 2, 3, atmospheric circulation models along with the interpretation of landform features from satellite images, for example, refs 4, 5, 6. The poor spatial scale of such circulation model data, however, has effectively precluded detailed examination of the forcing mechanisms by which windblown features, such as dunes, move on the surface of Mars. Large- to meso-scale atmospheric circulation models are designed to operate only at scales substantially (2–5 times) larger than the landform feature(s) itself, thereby inhibiting a full understanding of the process response in the system. We must, therefore, adopt a much finer resolution (that is, microscale model) approach to examine the driving mechanisms of any aeolian (windblown) system and its associated landforms. With the availability of high-resolution (0.25 m) HiRISE stereo images of Mars in recent years, high-resolution digital terrain models (DTM) of the surface are now available. This topographic surface can be used to run fine-resolution (sub-landform scale) wind models across complex 3D surface topography such as dune fields.

In the southern hemisphere of Mars, dune fields are contained primarily within large crater basins7. The dune sediment is sourced locally from exposed strata in the crater walls and floors8,9. In some cases (for example, Proctor Crater) the large diameter of these craters means that some intracrater dune fields may be far enough from the crater rim to experience a largely localized wind regime. Here we examine dunes within Proctor Crater, a 150-km diameter impact crater, located within the southern highlands of Mars (47.041°S; 30.667°E) where the dune field is made up of transverse dune forms. This study has shown that detailed 3D modelling of wind on Mars enables us, for the first time, to see the importance of large dune ridge shapes and their complex modification of localized airflow over the surface of Martian dune sites. Results show that back modelling of wind flow from actual ripple movement patterns can identify those regional winds that are forcing the migration of sediment over the dunes on Mars today. We find that winds travelling from the east southeast (ESE) (110°) are the dominant sand-transporting winds, whereas winds from east northeast (ENE) (75°) and west southwest (WSW) (239°) directions appear to play a more subordinate role. Wind modelling on a microscale (5 m) now provides us with an effective new tool to accompany surface ripple displacement information to help understand dune dynamics on Mars.