13.6 A Satellite-Based Nowcasting Method for Estimating Probability of High Ice Water Content Aviation Hazards

Thursday, 26 January 2017: 2:45 PM
Conference Center: Skagit 2 (Washington State Convention Center )
Patrick Minnis, NASA LaRC, Hampton, VA; and C. R. Yost, K. Bedka, L. Nguyen, R. Palikonda, D. A. Spangenberg, J. W. Strapp, and A. Protat

In addition to the threat of standard supercooled cloud droplet airframe icing, the phenomenon known as ice crystal icing (ICI) has been identified as the cause of more than 100 jet engine power loss events since the 1990s. High concentrations of smaller-than-average ice particles ingested into aircraft engines are thought to cause these events. Because of the small ice crystals, current on-board weather radar systems have been unable to detect the conditions that might cause ICI. Thus, identifying when and where high ice water content (HIWC) occurs is a pressing need for aviation safety. In addition to newer land-based scanning radars, geostationary satellite imager data offer the only non-in-situ potential for monitoring HIWC. The challenge is determining what is within the cloud based on the measured radiances and retrieved cloud properties. The High Altitude Ice Crystals – High Ice Water Content (HAIC-HIWC) field campaigns in Darwin, Australia and Cayenne, French Guiana have produced datasets of in-situ total water content (TWC) measurements valuable for studying the conditions that produce HIWC. During the HAIC-HIWC campaigns, cloud physical and optical properties such cloud top height, temperature, optical depth, and ice water path were derived from MTSAT-1R and GOES imagery acquired using NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS). The cloud properties and brightness temperatures were collocated with the in-situ TWC measurements to characterize cloud properties in the vicinity of HIWC. Additionally, satellite-derived overshooting cloud tops (OT) detected in the imager data were used to determine the proximity of HIWC measurements to convective cores. Certain cloud properties show some sensitivity to increasing TWC and a multivariate probabilistic indicator of HIWC was developed from these datasets. This paper describes the method developed to determine the probability of HIWC and shows examples from the HAIC-HIWC campaigns.  Vertically resolved IWC retrievals from active sensors such as the Cloud Profiling Radar (CPR) on CloudSat and the Doppler Radar System Airborne (RASTA) provide IWC profiles that can be used to validate and potentially enhance the satellite-based HIWC indicator. This method shows significant potential for identifying HIWC conditions in a nowcasting mode. It will be especially valuable for satellites such as Himiwari-8 and GOES-R that have high temporal and spatial resolutions.
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