The multi-year record of thermal and dust profiles from the mars reconnaissance orbiter mars climate sounder (MCS) contains a rich record of atmospheric structure and dynamics. Previous investigations…

This federal contract award to Southwest Research Institute (SwRI) was issued by the National Aeronautics and Space Administration (NASA) to conduct research on the Mars Climate Sounder (MCS) instrument aboard the Mars Reconnaissance Orbiter. The $327,442.01 grant will fund a systematic study to identify and investigate regional-scale (mesoscale) atmospheric phenomena on Mars, including topographic circulations, gravity waves, clouds, and dust storms. The research aims to characterize these mesoscale features, compare them to model simulations, and provide foundational understanding to improve Mars entry, descent, and landing predictions. SwRI, a prominent nonprofit research organization, will lead this effort to better understand the complex Martian atmosphere by leveraging the rich dataset from the MCS instrument. No set-aside designation was used for this award.

The multi-year record of thermal and dust profiles from the mars reconnaissance orbiter mars climate sounder (MCS) contains a rich record of atmospheric structure and dynamics. Previous investigations have primarily extracted information about largescale waves (e.g., the thermal tide and kelvin waves) and mean structures, have identified seasonal variations in the global dust distribution, including the discovery of extensive detached dust layers in the tropics, and have documented the distribution and some thermal effects of water ICE clouds. However, there have been no comprehensive, systematic studies of regional (mesoscale) systems. Mesoscale circulations and processes are hypothesized to play a major role in the mars dust, water, energy, momentum and chemical cycles. This hypothesis is largely based on model results with little in the way of direct or systematic observational evidence. Confirmation of the extent, structure and nature of mesoscale circulations would be an important scientific advance. Additionally, poorly validated mesoscale models are used as a primary tool to assess entry, descent and landing safety for surface-bound mars spacecraft. A systematic observational study would help to better validate these models, provide a quantitative assessment of model performance, and ultimately improve the predictions that these models make in support of the mars exploration program. The goal of this study is to exploit the MCS data set to identify, investigate and quantify the thermal and dust signatures of local and regional (i.e., mesoscale) phenomena. These phenomena include topographic circulations, regional dust storms, gravity waves, clouds, and likely other systems that have yet to be identified. The objectives that will be achieved in pursuit of the singular proposal goal are: 1. Search and catalog all MCS thermal and dust retrieval profiles showing anomalous* structures indicative of regional/mesoscale dynamics. 2. Categorize profile signatures into suspected slope circulations, gravity waves, plumes, local dust storms, and other phenomena, as discovery mandates. 3. Compare representative profiles of each profile category with mesoscale model simulations, validate model results with observational profile structures, and provide foundational understanding of the observed features. 4. Make available to the community the MCS PDS browsing and vetting software used by this project, and distribute the complete database catalog of characterized MCS profiles. *"anomalous" generally refers to substantial variations from a regional spatial mean, a profile that exhibits vertical structure that deviates substantially from large-scale model predictions, or a profile that is otherwise extraordinary in some way. The overall approach to achieving the goal and objectives for this research is to: 1) search the full MCS thermal and dust profile data set using an automated process to identify and screen for profiles of greatest interest, 2) examine, analyze and catalog profiles within the screened data set; 3) conduct mesoscale modeling to compare with profile anomalies of putative mesoscale origin, and 4) attribute to the profiles causative phenomenon based on consistency with model results. Each of these four steps is described in greater detail below. Also described is the further maturation of a software tool for browsing and accessing MCS data currently archived in the cumbersome PDS file structure.