Analysis and Automated Detection of Ice Crystal Icing Conditions Using Geostationary Satellite Datasets and In Situ Ice Water Content Measurements 2019-01-1953
Recent studies have found that high mass concentrations of ice particles in regions of deep convective storms can adversely impact aircraft engine and air probe (e.g. pitot tube and air temperature) performance. Radar reflectivity in these regions suggests that they are safe for aircraft penetration, yet high ice water content (HIWC) is still encountered. The aviation weather community seeks additional remote sensing methods for delineating where ice particle (or crystal) icing conditions are likely to occur, including products derived from geostationary (GEO) satellite imagery that is now available in near-real time at increasingly high spatio-temporal detail from the global GEO satellite constellation. A recent study using a large sample of co-located GEO satellite and in-situ isokinetic evaporator probe (IKP-2) total water content (TWC) datasets found that optically thick clouds with tops near to or above the tropopause in close proximity (≤ 40 km) to convective updrafts were most likely to contain high TWC (TWC ≥ 1 g m-3). These parameters are detected using automated algorithms and combined to generate a HIWC probability (PHIWC) product at the NASA Langley Research Center (LaRC). Seven NASA DC-8 aircraft flights were conducted in August 2018 over the Gulf of Mexico and the tropical Pacific Ocean during the HIWC Radar II field campaign. The convection sampled during four flights was observed by GOES-16 at 1- or 5-minute intervals, providing the first opportunity to analyze product performance from this new satellite. This paper will (1) present initial comparisons between GOES-16 and IKP-2 datasets during HIWC Radar II, (2) demonstrate GOES-16 products for select periods when high TWC was encountered with an emphasis on three flights with 1-minute imagery, (3) compare GOES observations and derived products from the HIWC Radar I and II campaigns.
Citation: Bedka, K., Yost, C., Nguyen, L., Strapp, J. et al., "Analysis and Automated Detection of Ice Crystal Icing Conditions Using Geostationary Satellite Datasets and In Situ Ice Water Content Measurements," SAE Int. J. Adv. & Curr. Prac. in Mobility 2(1):35-57, 2020, https://doi.org/10.4271/2019-01-1953. Download Citation
Kristopher Bedka, Christopher Yost, Louis Nguyen, J. Walter Strapp, Thomas Ratvasky, Konstantin Khlopenkov, Benjamin Scarino, Rajendra Bhatt, Douglas Spangenberg, Rabindra Palikonda
NASA Langley Research Center, Science Systems and Applications, Inc., Met Analytics, Inc., NASA John Glenn Research Center
International Conference on Icing of Aircraft, Engines, and Structures
SAE International Journal of Advances and Current Practices in Mobility-V129-99EJ
Subscribers can view annotate, and download all of SAE's content.
Learn More »