InFlight, Ground and Engine Icing


For the past two decades RAL scientists have worked to improve diagnoses and forecasts of icing conditions that impact aviation. The research areas include icing aloft, jet or turbine engine icing, and ground icing. Much of this work is accomplished as part of the FAA's Aviation Weather Research Program. 

Figure 1. Aircraft undergoing the deicing process.
Figure 1. Aircraft undergoing the deicing process.

One outcome from the icing aloft research performed by the In-Flight Icing (IFI) team is the development of operationally-available, automated in-flight icing forecasts over the CONUS and Alaska. At this time, the Current and Forecast Icing Products (CIP and FIP) developed at RAL are running at the National Weather Service's Aviation Weather Center (AWC) and are approved for unrestricted supplementary use. The outputs include expected icing severity, probability of encounter, and potential for supercooled large drop (SLD, those drops with diameters exceeding 50 microns) at 13-km resolution on flight levels from 1000 ft to 29 kft over the CONUS for 0-18 h.

The engine icing research falls under the FAA’s High Ice Water Content (HIWC) program. This program sponsors research to develop an algorithm called the Algorithm for Prediction of High Ice Water Content Areas (ALPHA) to diagnose atmospheric conditions conducive to engine icing events. Another aspect of the HIWC program is field experiments to characterize the atmosphere where engine icing events will occur. RAL scientists have participated in these experiments that have taken place in Darwin, Australia; Florida; Cayenne, French Guiana; and Florida, California, and Hawaii.

The FAA also funds icing research in the terminal area after a new rule was enacted regarding flight restrictions in known icing conditions. To improve the detection and forecasting of icing in the terminal area, the Terminal Area Icing Weather Information for NextGen (TAIWIN) program is conducting research focused on two key areas: improved ground detection of icing conditions (notably the detection of freezing drizzle) and improved performance and forecasting of freezing drizzle and freezing rain in numerical models. Improved ground detection of icing conditions has focused primarily on automated detection of freezing drizzle and ice pellets and improvements to feature-tracking algorithms for radar and satellite data are also being explored. The numerical modeling tasks funded under TAIWIN have focused on development of a time-lagged ensemble for better forecasts of icing conditions; improved aerosol initialization and fluxes in the models’ identification of shortcomings of model initialization of clouds and precipitation; testing of new data assimilation methods; and improved blending of observations and nowcasts with numerical forecasts of icing conditions.

Ground deicing research continued with a focus on improving the NCAR snow machine to better match the indoor holdover times versus the outdoor holdover times observed in nature. The machine has typically shown more conservative (shorter) holdover times as compared to outdoor times the FAA is interested in determining why that is and correcting for it. Upgrades to the machine were the major focus for improving machine performance and reliability during fluid testing and an entirely new top of the machine is being designed for testing in early 2020.


In 2019, the IFI and TAIWIN teams conducted a field experiment targeting SLD icing conditions. Based in the Chicago-area, the teams collaborated with the FAA and Canadian icing researchers to operate an instrumented aircraft which collected data in winter storms. The In-Cloud Icing and Large drop Experiment (ICICLE) also included surface-based sensors deployed around the region by the TAIWIN team. This unprecedented data set includes numerous events with freezing drizzle and freezing rain which will be used for enhancing our understanding of the processes which lead to icing and for improving icing weather tools.

RAL continued work on a number of icing aloft sub-projects for the FAA: 1) research on high-resolution NWP model with explicit microphysics and improved use of sensor data to develop drop size distribution (DSD) products for icing prediction and severity calculations with the intention of addressing FAA regulations to discriminate between freezing drizzle and freezing rain.  2) an icing product tailored for Alaska that is transitioning to operational use. 3) Improvements to icing diagnosis using NEXRAD dual-polarization data. 4) Engineers worked with NCEP to transfer operational icing products to its WCOSS supercomputing environment.

RAL staff working on the High Ice Water Content (HIWC) project continued to evaluate and refine methods for detecting and nowcasting areas of HIWC using data from a series of field experimentsThe evaluation process has resulted in an upgraded version of ALPHA (Algorithm for Prediction of High Ice Water Content Areas) which uses NWP output combined with satellite and radar data to diagnose cold cloud tops, warm atmosphere (compared to a standard sounding), high radar reflectivity below typical flight cruise altitudes, and other factors to determine regions conducive to the high ice water content hazard. Under a joint effort with the Australian Bureau of Meteorology to implement ALPHA in their operational setting and distribute products to airlines, the HIWC team conducted a preliminary trial of the product in an operational setting.

The TAIWIN project made significant progress in both the modeling and observational areas. The automated algorithm for ground detection of freezing drizzle was modified to include detection of ice pellets and frost utilizing the existing Automated Surface Observing System (ASOS) infrastructure. The algorithm has gone through several iterations now, and the latest results indicate that the algorithm is likely working as expected and can be used to reprocess archived data for determining periods where freezing drizzle, ice pellets and frost may have been occurring. A manuscript describing this algorithm was submitted to the Journal of Atmospheric and Oceanic Technology and is currently under review.

TAIWIN staff also conducted a review of the U.S. present weather reporting capabilities with a focus on the impacts that ASOS has had since its inception in the early 2000s. The study highlighted that reports of freezing drizzle, drizzle and ice pellets were all negatively impacted by ASOS, while reports of snow, rain and freezing rain had been improved. A manuscript has been accepted for publication by the Journal of Applied Meteorology and Climatology and is expected to be in final print by years end.

Radar and satellite tasking focused on automated tracking of possible derived Supercooled Large Drop (SLD) conditions from both radar and satellite data with a goal of providing a near-term nowcast of icing conditions. Considerable effort also went into the model improvement tasks with most of the work focusing on the Time-Lagged Ensembles (TLEs), cloud underproduction, and aerosol tasks. A new TLE of the HRRR model was developed and is currently being run in real-time within RAL. The modeling group is performing an initial verification of the TLE to determine if adjustments need to be made to the weighting of the different model runs. Significant progress was also made on the cloud underproduction task with efforts focused on development of a new cloud-fraction scheme for the WRF model to better forecast cloud development. A journal article summarizing these results was published in late spring.


The In-flight Icing Project will continue its research using state-of-the-art NWP model ouput and observations to develop icing products that provide information about cloud drop size to the aviation community. The data set obtained during ICICLE will support this development and verify products.

The HIWC team will complete evaluation of the diagnostic capabilities of ALPHA and continue research on HIWC forecasting techniques.  A formal HIWC Nowcasting Trial Exercise will be conducted in Australia jointly with the Bureau of Meteorology during the northern Australia monsoon season in early 2020. This trial exercise will provide insight to the FAA sponsors on the feasibility of fielding an operational version of ALPHA in the United States.

TAIWIN will continue to focus its efforts on the aforementioned tasks, with the goal of publishing the results of the freezing drizzle algorithm work. Data analysis from ICICLE will be the primary focus of TAIWIN tasking in the upcoming year. This data will be used to study microphysical cloud properties in order to better understand how icing conditions (particularly freezing rain, freezing drizzle and ice pellets) form and evolve over time.

The snow machine work is expected to continue with a focus on conducting more outdoor versus indoor testing, upgrading the NCAR snow machine, and testing the next design in the cold room by simulating the outdoor tests. If successful, this will clear the way for laboratory testing of aircraft anti-icing fluids in a laboratory environment.