PCA Analysis Of Ground-based Near- And Mid-ir Observations Of Saturn And Its Rings

Astronomy and Astrophysics – Astronomy

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Scientific paper

Although seasonal variations have been identified in the brightness temperature and near-infrared reflectivity of Saturn and its rings, it is not known if or how these variations are related. Determination of such correlations requires data mining of multivariate ground-based observational data set over a time interval of 10 years, spanning a little over a fourth of Saturn's orbit around the sun. Various science questions that we are interested in exploring are: 1. What is the correlation between brightness temperature and reflectivity for atmosphere and rings? 2. How do various chemical species such as ammonia and phosphine vary with observed temperature fields and albedo variations on the planet? As part of a JPL 10-week summer internship program, we took an independent statistical approach, without the assumption of any a priori models for planet and rings, namely the principal component analysis (PCA) method. The principal components are essentially the eigenvectors of the correlation matrix and the eigenvalues are indicators or weights of the variance associated with the principal components. This allows a multi-dimensional problem to become tractable by reducing it to a smaller number of othrogonal bases, which can be related to the physical variables of the system. We shall apply our results to the evolution of zonal and meridional maps of Saturn; and the diurnal variation of water-ice bands in Saturn's rings. Preliminary results will be presented.

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