An objective classification of Saturn cloud features from Cassini ISS images
Anthony D. Del Genio, John M. Barbara

TL;DR
This paper applies a clustering algorithm to Cassini images of Saturn to classify cloud features, revealing six distinct types and their association with Saturn's atmospheric dynamics, providing new insights into giant planet meteorology.
Contribution
It introduces an objective classification method for Saturn's cloud features based on Cassini data, linking cloud morphology to atmospheric dynamics.
Findings
Six distinct cloud clusters identified with unique morphology and vertical structure.
Three latitude bands on Saturn are dynamically characterized by different cloud types.
Upper tropospheric haze in the northern hemisphere appears to have thickened by 2014.
Abstract
A clustering algorithm is applied to Cassini Imaging Science Subsystem continuum and methane band images of Saturns northern hemisphere to objectively classify regional albedo features and aid in their dynamical interpretation. The procedure is based on a technique applied previously to visible-infrared images of Earth. It provides a new perspective on giant planet cloud morphology and its relationship to the dynamics and a meteorological context for the analysis of other types of simultaneous Saturn observations. The method identifies six clusters that exhibit distinct morphology, vertical structure, and preferred latitudes of occurrence. These correspond to areas dominated by deep convective cells; low contrast areas, some including thinner and thicker clouds possibly associated with baroclinic instability; regions with possible isolated thin cirrus clouds; darker areas due to thinner…
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