With an increase in global commercial air traffic, the occurrence of contrails and contrail-induced cirrus clouds is also projected to increase. An understanding of the role of these anthropogenic clouds in the Earth's radiation budget requires an accurate characterization of their macro and microphysical properties, such as cloud top height (CTH), optical depth (COD), and effective particle size (CPS). In-situ measurements of contrail microphysical properties are difficult, and hence the retrieval of such properties from remotely sensed satellite data is useful. Based on previously published work by Mannstein et al. (1999), we have developed an automated contrail detection algorithm (CDA) to identify linear and spreading linear contrail features using MODIS (Moderate Resolution Imaging Spectroradiometer) data. This study focuses on the analysis of a sampling of daytime and nighttime contrail-containing MODIS granules from 2006. We have derived contrail microphysical properties using an infrared-only heritage algorithm developed at NASA Langley for the Clouds and the Earth's Radiant Energy System (CERES) program. CDA error assessment is provided using independent analysis from four reviewers, who manually analyzed over 50 separate MODIS granules containing contrails. The contrail property retrievals presented here provide a snapshot of the seasonal and diurnal variability of both contrail amount and contrail microphysical properties. Future work will focus on the creation of a global contrail climatology for 2006, 2008, and 2010, complete with uncertainty estimates.