Determining the effects of ice crystals on a satellite-based flight icing threat product in single-layer and multi-layer cloud conditions

The threat of ice buildup on aircraft surfaces from super-cooled liquid water (SLW) in clouds is one of the major safety concerns of the aviation community, especially for smaller, low-flying planes. Using satellite data to detect areas of potential aircraft icing is desirable since pilot icing reports tend to be subjective and their spatial coverage is limited, often to areas near large airports. A theoretically based flight-icing threat algorithm has been developed for application to current GOES and other operational satellite data and is being tested and improved for the next-generation GOES-R satellite program. The primary elements used to infer the flight icing threat from satellites are retrievals of the cloud phase, effective temperature, liquid water path and effective droplet size. Across the mid and high latitudes, it is a common occurrence for lower level clouds to be composed of SLW near their tops, which contributes to the high probability of detecting icing conditions when these clouds are in view of the satellite. However, it is also expected that some of these clouds are composed of mixed phase hydrometeors or of a layer of ice crystals below the SLW layer which may reduce the icing threat to aircraft, a phenomena which is currently not accounted for in the current satellite flight icing threat algorithm and has not been adequately studied. In this paper, cloud parameters derived from the NASA Glenn Icing Remote Sensing System (NIRSS), a suite of active and passive ground-based sensors deployed at NASA Glenn Research Center in Cleveland, Ohio are used to improve our understanding of mixed-phase clouds and their potential impact on satellite-based flight icing threat estimates. The NIRSS provides information on temperature, water vapor and liquid water content profiles inferred from a microwave radiometer, cloud structure inferred from radar, and cloud base height derived from radar and ceilometer data. An experimental icing intensity product is also available which has been derived from the ground-based remote sensing data. The NIRSS data are also used to evaluate a new satellite algorithm designed to estimate the flight icing threat in certain multi-layered conditions where cirrus clouds exist between the satellite and the SLW layer. Infrared channel data and cloud properties derived from Terra and Aqua MODIS, similar to what GOES-R will provide, are examined to help refine the current algorithm for GOES-R. The analyses presented here may result in improved flight icing threat estimates from satellite data.