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Instrumentation that has been used for characterization of mixed-phase and glaciated conditions in the past, like the OAP probes, are subject to errors caused by variations in diffraction on the images away from the object plane and by the discrete nature of their particle detection and sizing. Correction methods are necessary to consider their measurements adequate for high ice water content (IWC) environments judged to represent a significant safety hazard to propellers and turbofan engine operability and performance. For this reason, within the frame of EU FP7 HAIC project, instrumentation characterization and validation is considered a major element need for successful execution of flight tests campaigns. Clearly, instrumentation must be sufficiently reliable to assess the reproducibility of artificial clouds with high ice water content generated in icing tunnels.

In response to the ice crystal icing hazard identified twenty years ago, aviation industry, regulation authorities, and research centers joined forces into the HAIC-HIWC international collaboration launched in 2012. Two flight campaigns were conducted in the high ice water content areas of tropical mesoscale convective systems in order to characterize this environment conducive to ice crystal icing. Statistics on cloud microphysical properties, such as Ice Water Content (IWC) or Mass Median Diameter (MMD), derived from the dataset of in situ measurements are now being used to support icing certification rulemaking and anti-icing systems design (engine and air data probe) activities. This technical paper focuses on methodological aspects of the derivation of MMD. MMD are estimated from PSD and IWC using a multistep process in which the mass retrieval method is a critical step.

Glaciated icing conditions potentially leading to in-service event are often encountered in the vicinity of deep convective clouds. Nowcasting of these conditions with space-borne observations would be of a great help for improving flight safety and air-traffic management but still remains challenging. In the framework of the HAIC (High Altitude Ice Crystals) project, methods to detect and track regions of high ice water content from space-based geostationary and low orbit mission are investigated. A first HAIC/HIWC field campaign has been carried out in Australia in January-March 2014 to sample meteorological conditions potentially leading to glaciated icing conditions. During the campaign, several nowcasting tools were successfully operated such as the Rapid Development Thunderstorm (RDT) product that detects the convective areas from infrared geostationary imagery.

This study presents the results of the ICE GENESIS 2021 Swiss Jura Flight Campaign in a way that is readily usable for ice accretion modelling and aims at improving the description of snow particles for model inputs. 2D images from two OAP probes, namely 2D-S and PIP, have been used to extract 3D shape parameters in the oblate spheroid assumption, as there are the diameter of the sphere of equivalent volume as ellipsoid, sphericity, orthogonal sphericity, and an estimation of bulk density of individual ice crystals through a mass-geometry parametrization. Innovative shape recognition algorithm, based on Convolutional Neural Network, has been used to identify ice crystal shapes based on these images and produce shape-specific mass particle size distributions to describe cloud ice content quantitatively in details. 3D shape descriptors and bulk density have been extracted for all the data collected in cloud environments described in the regulation as icing conditions.

The simulation of natural-like snow conditions in a controlled environment such as an Icing Wind Tunnel (IWT) is a key component for safe, efficient and cost-effective design and certification of future aircraft and rotorcraft. Current capabilities do not sufficiently match the properties of natural snow, especially in terms of size and morphology. Within the Horizon 2020 project ICE GENESIS, a new technology has been developed aiming to better recreate natural snowflakes. The focus of the newly developed system was the generation of falling snow in a temperature range of +1°C to -4°C. Ground measurements and flight test campaigns have been performed to better characterize these conditions and provide requirements for wind tunnel facilities. The calibration results of the new snow generation system as well as snow accretion data on a NACA0012 test article with a chord length of 0.377 m are presented.