Decoding Mars' Aeolian Features: Mesoscale Models for Wind and Climate Analysis

Aeolian features on Mars, ranging from active granular bedforms to relict cohesive outcrops, reveal the spatially diverse and temporally extensive influence of wind across the planet. Deciphering the climatic signals encoded in these features requires careful consideration of the interaction between the force of the wind and interaction with surface material.

Studies elucidating aspects of the modern wind climate for a particular study site or aeolian feature typically use global circulation models (GCMs) to relate aeolian orientations to modelled wind directionality. However, the efficacy of the modelled data is complicated when one considers that the scale of the GCM output (typically run at hundreds of kilometres) is vastly different than the scale of the study (often tens of kilometres). The scale of GCMs means topographically complex surfaces (valleys, craters, etc.) are unable to be fully accounted for. For these types of studies, higher resolution models – mesoscale models – are necessary.

Our overarching objective is to provide Mars geomorphology researchers with reliable wind data at topographically-relevant scales for use in studies of aeolian features. To evaluate our approach and demonstrate the feasibility and appropriateness of our methodologies, we present our mesoscale modelling outputs against mapped aeolian features at three locations on Mars: Ares Valis (wind streaks), Mawrth Vallis (dunes), and Syrtis Major (wind streaks).  

The publicly available Open access to Mars Assimilated Remote Soundings (OpenMARS) dataset [1] provides the initial and hourly-updated boundary conditions for the mesoscale simulations, which were performed using the Laboratoire de Météorologie Dynamique Mars Mesoscale Model [2]. We configured the mesoscale model to run with 40 unevenly spaced levels from the surface up to 50 km. A 3000 by 3000 km domain was evaluated at Syrtis Major at a horizontal resolution of 14 km; a 1000 by 1000 km domain was used at the other four locations at a horizontal resolution of 5 km. At each location, we performed four sets of simulations, each lasting 12 sols and starting at a different time of year (initialised at L_S= 0°, 90°, 180° and 270°), to capture seasonal variability. The data from the four simulations were combined and mean eastward and northward winds calculated for each grid point. Given the long formation timescales of some aeolian features studied, we focused on the average wind field over a year.

The results of our modelling efforts in these regions, which show good agreement between modelled outputs and aeolian feature orientation, will be presented. Our analysis demonstrates that this approach will serve as a useful tool for geomorphologists to request and handle reliable mesoscale modelling outputs to interpret aeolian features in terms of present-day or paleoclimate conditions.  

[1] Holmes, J. A. et al. (2020) Planet. Space Sci., 188, 104962. [2] Spiga, A. and Forget, F. (2009) JGR-Planets, 114(E2).