Multispectral images of Mars, taken at the NASA Infrared Telescope Facility (IRTF) near and at the 1995 opposition, are used to identify and track its atmospheric clouds and ground ices. Band depth mapping is used to help distinguish between the composition of volatiles and provide a check for the techniques of principal components analysis (PCA) and linear mixture modeling (LMM). PCA/LMM are used to create maps that track clouds and volatiles, a technique that requires no a priori spectral information in order to create these maps. Band depth maps at 3.33 μm, which have been shown to trace CO2frosts, show some transient features which could indicate polar CO2clouds at the time of these observations. We show that band depth maps at 2.25 μm are good tracers of H2O frosts and that band depth maps at 3.69 μm can distinguish between coarse- and fine-grained water frosts. These maps have allowed the detection of fine-grained water frosts in the north polar region and along the morning and evening limb regions. From the PCA technique we find that just two principal components can account for over 99% of the data variance. The first of these is an infrared albedo unit and the second is an ice/thermal unit. Plotting the spectral data cubes in this new vector space, we find that most of the martian disk can be modeled by spectrally mixing three endmember spectra having extreme values of these principal components. The morning and evening regions of Mars are composed of 40-60% of the north polar ice/thermal component endmember, indicating a frost component there consistent with the band depth mapping results. With a combination of these techniques it is possible to not only identify the extensive martian clouds, but to also determine composition. These new results are particularly relevant in light of recent Mars Pathfinder descent temperature profile data that indicated upper atmosphere temperatures below the CO2frost condensation point, implying that CO2ice clouds may be an important radiative component of the current martian climate.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science