Depth and Distribution of CO2 Snow on Mars
The dynamic role of volatiles on the surface of Mars has been a subject of longstanding interest. In the pre-Viking era, much of the debate was necessarily addressed by theoretical considerations. A particularly influential treatment by Leighton and Murray put forth a simple model relying on solar energy balance, and led to the conclusion that the most prominent volatile exchanging with the atmosphere over seasonal cycles is carbon dioxide. Their model suggested that due to this exchange, atmospheric CO2 partial pressure is regulated by polar ice. While current thinking attributes a larger role to H2O ice than did the occasional thin polar coating this model predicted, the CO2 cycle appears to be essentially correct. There are a number of observational constraints on the seasonal exchange of surface volatiles with the atmosphere. The growth and retreat of polar CO2 frost is visible from Earth-based telescopes and from spacecraft in Mars orbit, both at visible wavelengths and in thermal IR properties of the surface. Recently, variations in Gamma ray and neutron fluxes have also been used to infer integrated changes in CO2 mass on the surface. Measurements made by Viking's Mars Atmospheric Water Detector experiment were sensitive to atmospheric H2O vapor abundance. Surface condensates and their transient nature were detected by the Viking landers. The study here is motivated by recent data collected by the Mars Global Surveyor, affording the opportunity to not only detect the lateral distribution of volatiles, but also to constrain the variable volumes of the reservoirs. We elaborate on a technique first employed by Smith et al. By examining averages of a large number of topographic measurements collected by the Mars Orbiter Laser Altimeter (MOLA), that study showed that the zonal pattern of deposition and sublimation of CO2 can be determined. In their first approach, reference surfaces were fit to all measurements in narrow latitude annuli, and the time dependent variations about those mean surfaces were examined. In their second approach, height measurements from pairs of tracks that cross on the surface were interpolated and differenced, forming a set of crossover residuals. These residuals were then examined as a function of time and latitude. The initial studies averaged over longitude to maximize signal and minimize noise in order to isolate the expected small signal. In this follow-up study we now attempt to extract the elevation change pattern also as a function of longitude, and we focus on the crossover approach.