This dissertation aims to study the mid-level clouds using satellite observations. It consists of two major parts: characteristics (including cloud top/base heights, cloud top pressure and temperature, and cloud thickness) and thermodynamic phase of mid-level clouds. Each part devotes to a particular issue of significant importance for satellite-based remote sensing of mid-level clouds. The first part of this dissertation focuses on the impacts of three definitions of the mid-level clouds based on cloud top pressure, cloud top height, and cloud base height on mid-level cloud characteristics. The impacts of multi-layer clouds on satellite-based global statistics of clouds at different levels, particularly for mid- level clouds, are demonstrated. Mid-level clouds are found to occur more frequently than underlying upper-level clouds. Comparisons of cloud amounts between a merged CALIPSO, CloudSat, CERES, and MODIS (CCCM) dataset and International Satellite Cloud Climatology Project (ISCCP) climatology are made between July 2006 and December 2009. Midlevel cloud characteristics are shown to be sensitive to perturbations in midlevel boundary pressures and heights. The second part focuses on the thermodynamic phase of mid-level clouds. A new algorithm to detect cloud phase using Atmospheric Infrared Sounder (AIRS) high spectral measurements is introduced. The AIRS phase algorithm is based on the newly developed High-spectral-resolution cloudy-sky Radiative Transfer Model (HRTM). The AIRS phase algorithm is evaluated using the CALIPSO cloud phase products for single-layer, heterogeneous, and multi-layer scenes. The AIRS phase algorithm has excellent performance (>90%) in detecting ice clouds compared to the CALIPSO ice clouds. It is capable of detecting optically thin ice clouds in tropics and clouds in the mid-temperature range. Thermodynamic phase of mid-level clouds are investigated using the spatially collocated AIRS phase and CALIPSO phase products between December 2007 and November 2008. Overall, the statistics show that ice, liquid water, and mixed-phase of the mid-level clouds are approximately 20%, 40%, and 40%, globally.

This thesis evaluates the limitations of passive airborne remote sensing methods to retrieve optical and microphysical properties of Arctic mixed-phase clouds. These limitations are circumvented using a synergy of passive and active remote sensing techniques, and large eddy simulations. Using this synergetic approach, the three-dimensional spatial distribution of the thermodynamic phase of two cloud case studies is characterized. The findings are subsequently applied to a statistical analysis of the cloud properties measured during the Arctic Cloud Observations Using airborne measurements during polar Day (ACLOUD) campaign.

Approved for public release, distribution is unlimited / In this thesis, a fuzzy logic algorithm is developed for the detection of potential aircraft icing conditions using the Moderate-Resolution Imaging Spectroradiometer (MODIS). The fuzzy MODIS algorithm is developed in a manner similar to the cloud mask currently used to process MODIS imagery. The MODIS icing potential detection algorithm uses thresholds for 8 channels in a series of 12 tests to determine the probability of icing conditions being present within a cloud. The MODIS algorithm results were compared to results of the GOES icing potential detection algorithm run on MODIS imagery for 4 cases. When compared to positive and icing pilot reports for the cases, the MODIS algorithm identified regions where icing was encountered more effectively than the GOES algorithm. Furthermore, the use of fuzzy thresholds on MODIS rather than the hard thresholds of the GOES algorithm allowed for less restrictive coverage of potential icing conditions, making the MODIS algorithm more reasonable in assessing all cloud regions for icing potential. The results found here are preliminary, as further statistical analysis with a larger validation dataset would be more effective. Algorithm details are provided in the appendix for reference. / Captain, United States Air Force