Related papers: Towards a Foundation Model for the Martian Atmosph…
Machine learning and deep learning methods have been widely explored in understanding the chaotic behavior of the atmosphere and furthering weather forecasting. There has been increasing interest from technology companies, government…
As artificial intelligence (AI) continues to rapidly evolve, the realm of Earth and atmospheric sciences is increasingly adopting data-driven models, powered by progressive developments in deep learning (DL). Specifically, DL techniques are…
We present an atmospheric model tailored for the interactive visualization of planetary surfaces. As the exploration of the solar system is progressing with increasingly accurate missions and instruments, the faithful visualization of…
We present results from the Met Office Unified Model (UM), a world-leading climate and weather model, adapted to simulate a dry Martian climate. We detail the adaptation of the basic parameterisations and analyse results from two…
The present Martian climate is characterized by a cold and dry environment with a thin atmosphere of carbon dioxides (CO2). In such conditions, the planetary climate and habitability are determined by the distribution of CO2 between…
Data assimilation is an increasingly popular technique in Mars atmospheric science, but its effect on the mean states of the underlying atmosphere models has not been thoroughly examined. The robustness of results to the choice of model and…
Soil assessment is important for mobile robot planning and navigation on natural and planetary environments. Terramechanic characteristics can be inferred from the thermal behaviour of soils under the influence of sunlight using remote…
Global climate models parameterize a range of atmospheric-oceanic processes like gravity waves, clouds, moist convection, and turbulence that cannot be sufficiently resolved. These subgrid-scale closures for unresolved processes are a…
Airborne dust plays an active role in determining the thermal structure and chemical composition of the present-day atmosphere of Mars and possibly the planet's climate evolution over time through radiative--convective and cloud…
On the basis of geological evidence, it is often stated that the early martian climate was warm enough for liquid water to flow on the surface thanks to the greenhouse effect of a thick atmosphere. We present 3D global climate simulations…
Aerial navigation on Mars requires vision-based pipelines that are robust to the diverse illumination conditions and terrain morphology of the Martian surface. A key bottleneck for training and evaluating such methods is the scarcity of…
Surface release of radiatively active particles, with high infrared- (IR-)to-visible extinction ratios, has been proposed as a method of warming Mars. However, to warm Mars using aerosols, particles released locally must disperse globally.…
For the past several decades, numerous attempts have been made to model the climate of Mars with extensive studies focusing on the planet's dynamics and the understanding of its climate. While physical modeling and data assimilation…
This review describes the dynamic phenomena in the atmosphere of Mars that are visible in images taken in the visual range through cloud formation and dust lifting. We describe the properties of atmospheric features traced by aerosols…
The availability of Martian atmospheric data provided by several Martian missions broadened the opportunity to investigate and study the conditions of the Martian ionosphere. As such, ionospheric models play a crucial part in improving our…
The formation of aerosol particles in the atmosphere impacts air quality and climate change, but many of the organic molecules involved remain unknown. Machine learning could aid in identifying these compounds through accelerated analysis…
The Martian atmosphere experiences large diurnal variations due to the ~24.6 h planetary rotation and its low heat capacity. Understanding such variations on a planetary scale is limited due to the lack of observations, which are greatly…
Cloud computing offers an opportunity to run compute-resource intensive climate models at scale by parallelising model runs such that datasets useful to the exoplanet community can be produced efficiently. To better understand the…
Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to impressive increases in generalisation for downstream tasks. Such models, recently coined as foundation…
One-dimensional (vertical) models of planetary atmospheres typically balance the net solar and internal energy fluxes against the net thermal radiative and convective heat fluxes to determine an equilibrium thermal structure. Thus,simple…