Martian Cloud Modeling using NIR Spectral Images

Astronomy and Astrophysics – Astronomy

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Scientific paper

In the near-infrared (NIR), disentangling surface and aerosol spectral features is a difficult, iterative process. In order to be able to use radiative transfer to model clouds you need to know the surface reflection characteristics; but to get the surface reflection, you need to be able to subtract off the atmospheric spectral contribution. One way to attempt to solve this is to "simply" create a monolithic system with a large number of parameters - one for each surface component, each aerosol species, and each gas constituent. Such a multi-dimensional space is no doubt complex with large difficulties in solution uniqueness.
Using ground-based NIR spectral images acquired over several oppositions from the NASA IRTF, we have been able to show that a principle components analysis is able to find two surface components without any a priori inputs [1, 2]. Further work has shown that these surface spectral components are fairly uniform across all seasons [3, 4]. Additionally, we have been able to create a radiative transfer modeling system that was previously used to calculate aphelion cloud optical depths using only the 3 μm spectral region [5].
In this presentation I will present preliminary results from combining the radiative transfer with the recovered surface spectral signatures as inputs to measure martian cloud optical depths in the NIR.
This work was supported by grants from the NASA Mars Data Analysis and the NSF-RUI programs.
References: [1] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [2] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [3] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [4] Klassen, D. R. and Bell III, J. F. (2007) in preparation. [5] Klassen, D. R. and Bell III, J. F. (2002) BAAS, 34, 865.

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