Evaluation of the AROME model's ability to represent ice crystal icing using in situ observations from the HAIC 2015 field campaign

• Published in: Quarterly journal of the Royal Meteorological Society 2021-07, Vol.147 (738), p.2796-2817
• Main Authors: Wurtz, Jean, Bouniol, Dominique, Vié, Benoît, Lac, Christine
• Format: Article
• Language: English
• Subjects: atmosphere; Atmospheric and Oceanic Physics; convection; Convective clouds; Crystals; Earth Sciences; High altitude; Ice; Ice crystals; ice/icing; Icing; mesoscale modeling; Meteorology; Microphysics; Moisture content; observational data analysis; Particle size distribution; Physics; Sciences of the Universe; Shape; Size distribution; Snow; Temperature; Tropical climate; Tropical convective systems; Water content
• ISSN: 0035-9009; 1477-870X
• DOI: 10.1002/qj.4100

Since pilots generally avoid intense convective areas, ice crystals icing (ICI) is an aeronautical weather incident that mainly occurs in the anvil of tropical deep convective clouds. Samples of favorable conditions for the occurrence of ICI and data from the High Altitude Ice Crystals (HAIC) 2015 field campaign in French Guiana are investigated and compared with simulations of the French operational mesoscale forecast system Application of Research to Operations at Mesoscales (AROME). To this end, a contextualization of convective systems into convective, stratiform, and cirriform regions is employed for both observations and AROME. General features of the microphysics of deep tropical convective systems are identified. The number concentration of crystals larger than 125 μm and total water content (TWC) are strongly correlated at each temperature level, and both decrease with increasing distance from convective cores. AROME can reproduce the general behavior of the observed microphysics, especially TWC, but seems unable to simulate extreme ICI events. Reasons are sought in the assumptions performed in the microphysical scheme ICE3, and guidelines are proposed to enhance its skills in the context of ICI. In particular, the representation of the snow particle size distribution is adjusted across observations using a generalized gamma shape. This shape is found to outperform the usual Marshall–Palmer and gamma shapes. Additionally, a temperature and snow content dependence of generalized gamma parameters is found. These changes are found to significantly improve the snow concentration diagnostic of ICE3, and these modifications open the way for improvements in the ICE3 scheme. In some deep tropical convective clouds, ice crystal icing is an unavoidable threat for aeronautics. The possibility to forecast such events using the French mesoscale model AROME is investigated in this article on the basis of the HAIC 2015 field campaign and a contextualization of the deep convective clouds into convective, stratiform, and cirriform parts. Guidelines including modifications on the snow particle size distribution and snow concentration diagnostic are provided to improve the skills of microphysical schemes.