GIS-based quantitative integration of global climate model simulations and geodatabases of gullies on Mars

Global climate models (GCMs) allow planetary scientists to test physical explanations for the formation and modification of climate-related features on planetary bodies. This method of analysis depends upon two data sources: the GCM itself and a catalog of features under investigation. Integrating these two inputs provides a novel approach for testing climate-related hypotheses for the formation of geological features of interest. An integration pipeline has been developed and a proof-of-concept application is tested on martian gullies, small erosional channels that may provide evidence for the recent flow of liquid water on the surface of Mars.;The end-to-end GCM/data integration approach includes three primary components: (1) generation of a geodatabase with coded domains of all imaged gullies in the southern hemisphere of Mars from Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) images, (2) incorporation into a Geographic Information System (GIS) framework of three GCM simulations that quantitatively predict surface conditions over one martian year under three different starting scenarios thought to have occurred in Mars' recent geologic history, and (3) the integration of the geodatabase and GCM simulations to create dynamic visualizations of surface conditions over time and quantitative extraction of temperature/pressure values at gully sites to test whether or not liquid water could exist at these locations.;The newly developed approach in this study demonstrates that the formation of gullies by liquid water is unlikely under present atmospheric conditions at most locations, but is predicted to have been achievable under more favorable orbital scenarios thought to have occurred in the recent geologic history of Mars. If these associations are valid, this increases the potential of primitive biology having existed in the recent history of Mars. More broadly, this technique represents a potentially valuable tool within a GIS framework for increasing confidence in data/model comparisons at global, hemispheric and regional scales.