Holistic Mapping of the Present-day Martian Seasonal CO2 Frost: Part 1, Frost Detection within Global Visible, Thermal, and Spectral Datasets

A dominant driver of Martian atmospheric, landscape, and landform activity is the annual cycle of CO2 and water, seasonally moving between atmospheric gases and surface frost. Orbital dataset-based maps of the distribution of seasonal frost provide a broad look at how these volatiles move through time and space, as documented in past analyses. These past works typically take the form of a global study using a single, coarse resolution, global dataset or a spatially targeted site study combining data from multiple instruments. However, there does not yet exist a global map incorporating datasets from both the kms-resolution maps of the contiguous seasonal cap with landform-scale (about 10-100s-m) patches of frost. Therefore, we produce a comprehensive, global map of the seasonal distribution of CO2 frost through a single Mars year, integrating the information contained in visible (HiRISE/CTX), thermal (MCS/THEMIS), and spectral (CRISM) datasets so as to generate 2.4 billion frost probability estimates. Combining global instrument data across diverse spectral, spatial, and temporal regimes required the rigorous application of multiple data science methods and a multi-disciplinary collaboration between data scientists and planetary scientists. We produce two papers: this first focuses on analysis of the individual datasets, highlighting key data science techniques and metrics used to capture the underpinning physical science intuition within robust and efficient autonomous “frost detection” methods. We generate, for each dataset, 36 frost probability maps showing the distribution of surface CO2 frost through a Mars year, with a temporal resolution of 10 degrees Ls and a spatial resolution of 64 points-per-degree.