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High Ice Water Content (HIWC) is an atmospheric condition at high altitude that may lead to failure of jet engines. As a potential threat to aviation safety and space launch operation, it has received significant attentions from cross-disciplinary communities. Detecting HIWC conditions with airborne radar is essential to the safe monitoring of this type of hazard, however it has unique and significant challenges. For example, in general, small ice particles and clusters of ice particles do not register strong radar reflectivity, which is a challenge to the sensitivities and resolutions of small aperture airborne radars. Second, it is difficult to discriminate HIWC from other atmosphere conditions, such as general precipitations, and evaluate the threat level (in quantity of Ice Water Content, or IWC) with remote sensing only. In this study, we developed a novel simulation-based approach, which uses the in-situ probe collected HIWC cloud probe data during a series of flight test campaigns, as well as the microphysical particle models retrieved from these data as the basis of simulations. Then, we combine and reconcile these models with the ground-radar measurements, which leads to a three-dimensional truth gird. Using this truth field, we developed a single-cell-Monte-Carlo (SCMC) simulation implementation, which creates and generates airborne weather radar signatures and moments for each individual resolution cell. The simulation has incorporated (1) An initial framework of airborne radar system and sensor modeling, (2) Modeling of ground clutters and effect of antenna patterns. The simulation tool has significant applications in the areas of (1) Guidance of designing and development of next generation airborne hazard sensing and avoidance radars. (2) Support industry standard making and performance evaluations such as FAA, and (3) Support scientific studies on airborne radar signatures and techniques for further understanding of hazardous atmosphere conditions for aviation.
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